Verisk Analytics Stock

Great. Hello, everyone. My name is Alex Hess, and I'm a Vice President on Andrew Steinerman's U.S. Business and Information Services Equity Research team. It is great to be here today with Verisk's CFO, Elizabeth Mann. Elizabeth has been Verisk's CFO for 4 years now and has played a massive role in many of the firm's key initiatives during her time at Verisk.

At this point, many of you in the room and many of you listening know Elizabeth quite well. That being said, it's still very much a privilege to welcome you here to All Stars as well.

It's great to be here. Great to see so many of you here. Thank you for having me in this beautiful room today.

So I want to start with the Verisk's performance historically in hard markets for insurance versus soft markets. It's about 20%, 25% of your revenues have some linkage to some element of net written premium growth, and you've historically averaged about on an OCC organic constant currency basis, about 6.8% growth in soft markets and 7.3% top line growth in hard markets.

Help us understand, as you see the P&C market presently, it's been softening. Will the next move be towards continued softening, will be de firming? And what impact does that have for Verisk?

Yes. Thanks for the question, Alex. So -- this goes back to, Verisk was founded as a consortium of the U.S. property and casualty insurers over 50 years ago. And one of the benefits of coming out of that historical model, as we separated from the industry, we set the expectation and we set the revenue model for that business, that we would grow as our clients' businesses grew. And so our pricing component on some of our contracts have an input from premium growth. That is a good thing in the long run because that has tied us to a large, stable and growing market. But it means that we have a correlation to pricing growth in some years.

Now it is -- there are also various pricing components. There is also the fact that we sell our business according to the value that it creates. And there is also -- there are also kind of cross-sell and upsell and other product dynamics. All of which has contributed to the stability of our revenue growth being in the 6% to 8% organic constant currency range very consistently over time, in fact, each and every year since we went public back in 2009.

But there is -- yes, there is a slight tailwind to our pricing in strong premium, hard premium years, and maybe a modest headwind in softer premium years so that when we take an average going back to 2009, you get this stats that Alex quoted, which is 7.3% growth in hard market years, 6.8% in soft market years, modest differential there, still very consistent with the average of about 7% organic constant currency revenue growth.

As to where we are right now in the cycle, we are coming off a couple of years of very strong premium growth and entering a period with more normalized premium growth. So premium growth over a historical average period being in the mid or low to mid-single-digit range, but can range from negative premium in, sort of in the early -- in the mid-2010s, I think, to very strong, almost double-digit premium growth. Again, we have a consistent track record of delivering growth in all of those premium environments.

Understood. Understood. So maybe we'll dive into the performance of the subscription business versus the transactional non-subscription piece, if you will. It's about -- I think last quarter, 83% of your revenues were subscription-driven, so 17% aren't. 80-plus percent is a very high number for an info services firm.

And obviously, over time, you've focused a bit on transitioning products from transactional pricing to subscription-based models. But maybe just lay out for us where -- is the revenue growth story today in subscription still as strong as it was a year or 2 ago, where you were realizing good price increases and pricing to value nicely. Has there been any change in the underlying drivers of this year?

Yes. Yes, it is as strong as it was a couple of years ago. We think that is coming from the importance of our products for our customers' business and the need in this environment to continue to have the best possible data and analytics to select the right risk and to price it accordingly. And so you've seen us kind of consistently throughout report our subscription revenue growth, which has been fairly strong.

Got it. And the underlying drivers of that, is it still pricing led to the same degree it was 2, 3 years ago or the last 2, 3 years? Or is it leaning more on, say, new product innovation? Or how do we think about the balance there?

Yes. It is both of those things over time. The pricing -- we give a build to our overall 6% to 8% organic constant currency growth rates based on kind of pricing versus new products versus cross-sell and upsell. Pricing contributes slightly more than half of the growth. So I think 350 to 450 basis points is our target for the 3-year cycle starting in 2026. There may be just a hair less contribution from pricing as we move into a more normalized premium environment and more coming from new products and from cross-sell and upsell.

Got it. And then conversely, whereas the subscription business in many periods in recent years run above that 6% to 8% number. The transaction business has sort of been -- again, a smaller piece, has been in retreat a bit. And part of that is by design. You guys have switched a lot of products to the subscription model, maybe as they've matured and grown, sort of, into the market and developed market adoption. But just help us think about, if I look at the last 12 months, $510 million of those transactional products, that's down a couple of tens of millions from peak. Obviously, there's discrete headwinds like weather, usage in some small products. But should investors think of this level, this $510 level as a floor of which that transaction business can return to growth and be a quality contributor?

Yes. So we don't -- first of all, we don't run the business separately by transaction and subscription. We have a number of different businesses and products, and each of those is looking to maximize revenue according to whatever model fits that customer set best. So that's our overall goal, is point one.

There have been some puts and takes on the transactional side that you've heard us talk about over time. The largest one probably being a lighter weather year in 2025. And so far, appearing to be slightly light versus average in 2026 as well.

Let me maybe level set with an example that has been helpful for investors as they think about the mix of our subscription and transactional revenues. And this comes particularly on our claims -- some of our claims businesses, which provide property estimates for carriers and contractors for property repair that's associated with an insurance claim. So a tree falls on a house, the contractor goes on site, they develop the estimate of what materials and labor are going to be needed, and therefore, what the price of that repair is going to be for the carrier. That is a product that is sold both to the carriers and to the contractors. The carriers use that product on a subscription basis -- on a subscription for a certain number of claims assignments. And above that number, they go into overage.

So they pay more per claim above their subscription level, at a price that is more attractive on the overage and the overage is a transactional revenue. So simplistically, if you have, let's say, if a customer with a $100 subscription, GBP 100, I should say, here. So GBP 100 subscription, and they have GBP 10 of overage charges. We're going to go back to them the next year and say, well, actually -- and so this has been our focus of, yes, converting some products from transactional to subscription, but also just increasing the subscription tier for customers, which is good for them. It gives them more visibility and certainty.

So if you've got a customer that has the GBP 10 of overage 1 year, we'll go to them and say, "Don't you want to resubscribe at GBP 105 next year and have more volume included in that, and then you could have overages above that." If, let's say, the following year, the volume is lower than it was before, now we've locked in GBP 105 of subscription revenue but the transactional may go to 0, because the volume is lower. That's probably better -- in that situation, it's better for us. If the volumes have been higher, it would be better for the customer, because they have more included in their overall. But either way, it looks like -- if you just break out the transactional piece, it looks like a lot of variability on that. GBP 10 of excess when we were looking to maximize the whole.

I got it. That makes sense. So you mentioned that, obviously, weather has played a big impact in your results of late, sort of should we say, benign weather?

Yes.

So it's as simple as fewer named storms, fewer hailstorms in Texas means fewer trees falling over, means fewer claims means fewer opportunities to set these pricing structures in motion.

That's right. It is a lighter weather is a good thing for policyholders. It's a good thing for homeowners. It's a good thing for our customers, the carriers who have had very strong profitability in this environment and which has maybe given them room to invest in other ways in data and analytics that also flows through as a benefit for us. But yes, but for those businesses that have a revenue component from number of claims processed, it is a modest headwind.

Understood. So I think this all comes in the context of 4 consecutive quarters of sub 6% organic constant currency revenue growth, obviously, against that 6% to 8% target. That's an unusual streak for Verisk. Is it as simple as, hey, look, we're going to get to -- from really benign, notably benign weather to normalized weather? And then, this is all sort of -- well, that was a weird year, weird 12 months? Or -- is there anything else that gives you confidence that the return to that 6% to 8% number is super imminent, or not super, let's say, imminent.

Yes. So we talked about the headwinds from weather, and that did reduce our overall volumes. We are anniversarying what I would say was -- it was really the summer hurricane season of 2025 that was uniquely benign. 2026 is also potentially looking to be a modest year from a weather standpoint. But from a year-over-year standpoint, that is not necessarily at this point as significant as a headwind. So from a growth standpoint, with 83% of our revenues coming from subscription, we think we have visibility -- enough visibility, for example, that at our March Investor Day, yes, we recommitted or continued to commit to our expectations for 6% to 8% as an annual organic constant currency growth target.

Great. So let's maybe talk about those Investor Day targets. And you mentioned briefly within that 6% to 8%, which was provided at Investor Day in early '23 and then again in early '26. So this year, 6% to 8%, both times, and you've done a very good job sort of being in that band. But you did tweak some of the underlying drivers. So you increased your sort of framework for price realization, but also took down your framework cumulatively as cross-sell, upsell and new product innovation. What were some of the learnings that influence those tweaks? And then maybe how should investors be thinking about new product innovation at Verisk?

Yes. So we are very excited about our new product innovation. There's a couple of things. We did slight -- when we increased the target on price, we slightly decreased those targets to get to the same total. But let me explain a little bit about the drivers of that. It is not that we are less bullish on innovation, because we still have a lot of excitement and a lot of things we are launching, a lot of things in process.

Two factors. One is we did sell, for example, our Verisk Marketing Solutions business. And so that had been one category that was included at the time in new products. And so it just -- it's a lower base that we have sort of fewer shots on goal that we have to deliver that portfolio relative to the whole. So that's one area. And that may be one of the biggest pieces.

I think the other element is an acknowledgment of the rate of adoption within the insurance industry is a measured rate just relative to the size of our whole. And then finally, there's the point that quite a bit of our new products and innovation, for example, our Core Lines Reimagine, reinvestment in our core product and content, that came in that is being monetized through price increases.

Okay. So for anybody in the room or listening who doesn't have the context, Core Lines Reimagine functionally, this is the core lines businesses are those that have been with Verisk since day 1 and really make the firm foundational. And over the last, I don't know, 4, 5 years, you've gone on sort of this program. It's now winding down -- it's reaching its end state to really get that product where you want it to be for the future. We'll touch a bit on that in a minute, but I think that's a good reminder on the marketing piece being out of the equation, means, fewer shots on goal.

But just to stay on new product innovation for a second. There were 3 areas that we thought that being Andrew, Rohan, and I, on the JPMorgan research team thought were really interesting as pertains to you guys, and those were auto insurance, aerial and then the excess and surplus.

I'd like to talk briefly about the auto side. It's about 10% of your revenues. Can you give investors a sense for what sits within that 10% and where you stand today as far as competitive positioning versus where you want to be?

Yes. Our auto business, so it sits -- we touch it a couple of different places across our portfolio. Of course, our core forms, rules and loss cost business covers auto and our anti-fraud businesses also cover auto. But we have specific data products for it in what we call our underwriting data and analytics solutions part of our portfolio. And that, I think, is what people think of when they think about kind of our auto business.

And now I will say the historical -- the historical view of that business, Verisk historically had great strength in property and one of our competitors has great strength on the auto side of the insurance market. And so they are probably still the incumbent in that space. We have been a bit of a challenger. And so we have some products that are compete directly against the competitor and then others that are new innovations that are built on some of the data sets that we have elsewhere that we think are unique. And so those are some of the areas that enable -- that have had strong traction.

And those are still the areas for innovation for you guys, those sort of products that help people buying quotes faster to help them review their portfolio for missing data inputs that could let you.

Yes. Yes. That's right. Yes, Alex is referring to our LightSpeed product, which enables a carrier to quote and price a policy for a consumer shopping for auto insurance online in real time.

Got it. So then aerial imaging, really sort of interesting business here. Obviously, if you go in the U.S., you get a home quote, I'll send a drone over your house. But you guys don't own the drones, you have no interest in owning the drones, you want to own an aggregate the data that underpins the image as those drones return, right? Talk a bit more about your positioning, your innovation in aerials. Is this a needle mover for you guys? Or how to think about that business from the context of your portfolio?

Yes. We do think of aerial imagery as one of the elements of -- one of the growth drivers in our property data sets. Aerial imagery is becoming more and more, well, cost effective and more and more important as a way to measure particularly roof condition and external conditions around the house. And so we don't need to own or operate the hardware that is measuring the aerial imagery, but we can use that combined with our other property data sets to give insights about a roof.

For example, when you're underwriting a new policy, one analytic that we produce from this aerial imagery. So historically, you would produce roof -- you would provide a roof age report, meaning this house was the roof we built in 2010 or 2015 or 2020. But we can now provide a more enhanced, effectively a remaining roof life statistic, which based on the aerial imagery and based on knowledge of what else has transpired in that environment and in that neighborhood, this roof may have been built in 2015, but does it act like an 11-year-old roof? Or will it age like a 5-year-old roof or a 20-year-old roof based on what else has happened and what the visual conditions are there.

So that's an example where we can use the aerial imagery, we can combine it and enhance it with other data sets to create a new analytic that has value from assessing for a carrier underwriting and assessing the risk that they are writing.

Get to study Verisk, you get to study American home roofing demand.

Exactly.

So maybe let's talk a bit about the excess and surplus data business that you guys are -- I would describe it as budding or you're building it out and barriers perked up because you recently mentioned that, that's now got about $18 billion of historical and current premium data, and that was up from $10 billion early in the year. So it's growing quite nicely as far as coverage goes. But can you walk us through some of the opportunity, what you're going to do with this expanding coverage and why this is something investors should care about?

Yes. So this is -- in our forms, rules and loss costs and in our underwriting businesses, the traditional perspective was this was really for the admitted lines of insurance. Admitted lines in the U.S. means essentially covered by regulators. So admitted in the regulated insurance market. And we assist carriers with that regulatory process. So that was kind of really our traditional sweet spot.

We came to find by accident, that's different from excess and surplus lines of business, which is lines that are either not regulated by the regulators or higher value and so exceeding the value of what the carrier will put in their book. Those were historically very idiosyncratic policies that were priced in a very one-off way but weren't "Verisk" like policies where having standardized view of data would be helpful.

Now in today's environment, more and more, in particular, property risk, in the U.S. is moving into that excess and surplus market as, for example, the $10 million mention on the coast of Florida, which is -- has potentially high weather risk, is being seen as too high a value or too high a risk to fit into the admitted markets. So those risks are looking more and more like risks that Verisk knows something about where an industry view of loss costs will be helpful for the market.

So it has gone from a little bit of an accidental customer set for us where we've had some carriers in that space. I should also add there's the market dynamic where admitted -- where regular carriers that write admitted business are also now expanding into excess and surplus lines of business because it is an area of growth for them. So our typical customer may now have a line or a book of business that is -- that they are familiar with the Verisk products and want to use them for that area. So we've been expanding into this market. We've added to our team to bring specific coverage to that market, and it's an opportunity for us to continue to support that growing part of the insurance industry.

Got it. So I think across these sort of hobby horses of ours, we've covered now that the investors should feel pretty good about the new pace of innovation, and we have not used the word AI yet in the 18 months we've been doing this. So maybe that's a record for this event this year.

But let's touch on AI. The number that I think resonated most with us coming out of the earnings call was that there are 7,000 licensees on your XactAI solution, which, sort of, is very much often contractor facing, not purely insurer carrier-facing, but it's the widely -- it's the AI version of your widely used Xactware claims estimation suite. Talk to us about what's resonating so well with XactAI in the marketplace. Is it is the strong data foundation workflow capabilities? Or is it just the user base is particularly prime there? Because 7,000 is a big number.

Yes. So it's a combination of a couple of different things. And one is, yes, the value of the product and the desire for more efficiency in that space. So the XactAI tool can bring Gen AI tools on top of -- we talked about the software and the underlying pricing detail that enables the carriers and the contractors to develop this pricing estimate.

Now you've got Gen AI tools built into it. So for example, one of the most popular features of this product is automated photo tagging. So you can take a photo of the damage that you're assessing. And then the AI will populate, okay, here's the estimate, here's the price list, and so here's what the estimate will cost.

Now that, of course, requires review from the contractor. It may hypothesize that it's a certain type of drywall, a certain dimension of it and actually, it needs to be modified. So there's carrier review. But that's one of the most popular features and it significantly improves the throughput of number of estimates that can be reviewed by an adjuster or by a contractor in a given day. So that's the popularity of it. That's one driver of the growth is the strength of the product.

The second though is actually gets that something fundamental, which is the rate of adoption of AI products in different sectors. And so the rapid growth that you're seeing on the number of licenses is primarily on the contractor side today because they look at the product, they see something with a real return and a benefit for them. And the key thing is they are sort of able to adopt and switch on relatively quickly.

In the carrier market, we also have users on that product. I think we said we have 1 of the top 10 using that. But what you see there is on the carrier side, it does take a bit more time for AI-enhanced products to go through a review process, to go through an AI governance board, to go through legal and contracting review for both sides to understand data use rights and what exactly is being shared and what content. So I think what we see there is the ability for adoption to be rapid when there is, number one, a value proposition and that whatever kind of governance and contracting hurdles can be worked through quickly.

We think it will also continue to deliver value over time on the carrier side, but that it is -- and there's quite a bit of interest. It is still going through, in many cases, the review process.

Yes. So we see that with a few info services firms that especially serve regulated use cases. The sales cycle with an AI-enabled product is, it's not short right now.

Yes.

But maybe to switch to, obviously, the other thing we're seeing a lot of in the information services space is the launch of MCP connectors. And Verisk has 2. One is your forms, rules, and loss cost data. And the other, again, is that Xactware business, if I have it right. Obviously, insurance adopts technology in a deliberate way. Is that what you're seeing play out with your MCP connectors as well? Or has that been a little faster, has it been any way different than what you've seen in the Xactware piece?

Yes. I think on the carrier side, yes, it is on the similar cycles of that. There is a lot of interest and some adoption on the MCP connectors. Right now, today, those are MCP connectors on Claude. It's not exclusive to Anthropic. So we can launch other connectors in the future with other large language model companies. But -- so that is -- a customer needs to be already a customer of Verisk as well as a customer of Anthropic in order to begin using the connectors.

Understood. And maybe just thinking through how you've distributed your data historically. Can you refresh us how to think about your historical distribution channels? And how does Verisk data distribution change in the age of AI?

Yes. I mean if you want to go back to historical distribution channels, the loss cost -- the forms, rules and loss costs used to be mailed to our customers in a stack of paper circulars. That was how we started. Obviously, that's -- more recently, it was downloadable PDFs. There was still a surprising amount of workflow that -- of manual workflow that went -- took place on our customers' side between downloading a PDF, looking at the loss table and then potentially manually keying that into their own internal systems or their policy administration systems.

Our goal is to distribute in however a customer wants to take it. And believe it or not, there are plenty of customers that still access our content by downloading PDFs. That will continue to change over time. For those who have the appetite for it, obviously, a better 2020s way is to provide the data through APIs. They could also get it through -- we have connectors built through most policy administration systems so that they can access it directly through a Guidewire or a Duck Creek or many of the other policy administration systems that they may have in place. There are many that build their own connections.

And then, of course, in today's world, connectors may be the latest way to access the data. Eventually, we are doing some trials where we are building agents based on our data, and that may be a way for our customers to interact with our content.

And I know that a core part of your Core Lines Reimagine program was making sure you are distributing the data as in the most modern way that your clients wanted so that they can get rid of any associated tech debt because the spending on ingesting your data has always sort of been more than the spending on your data itself. So as you've seen -- as you entered the age of AI, which has made sort of in some ways, reducing tech debt, a much easier task, have you had to go back to the drawing board and say, "Hey, look, this is our road map with Core Lines Reimagine," but actually now, we're doing this thing instead or we're doing that thing instead. Had you guys had pretty good visibility that this was the road of travel maybe towards the end.

Yes. I think we have pretty good visibility. I don't think it's instead of what we're doing with Core Lines Reimagine, I think it's in addition to and on top of. So maybe -- maybe if I can jump off from that. As you were talking about distribution of content, and we said downloading PDFs, part of Core Lines Reimagine and reinvesting in those that forms, rules and loss cost content has been about bringing the content together on a platform of core.verisk.com, where they can get all of it together and get associated insights and analytics around it. That all of our content will be available on core.verisk.com by the end of 2026, which is essentially that kind of essentially marks the completion of what was initially envisioned with Core Lines Reimagine.

I think on top of that is where we can begin to build other ways to access the data that they can use, whether it's API-led or whether it is AI-enabled. And maybe if I can also comment on this, our dialogue with our customers around the AI road map has been very active. They will have their own AI road maps, which is generally around workflow efficiency and how they manage their own workflow processes on the underwriting value chain, on the claims kind of process workflow.

Verisk has always been fairly workflow agnostic given that it's so different across all the carriers. And our value is that we bring our data and content to bear for the customer at their point of mission-critical questions. The mission-critical questions being, should I write this policy or not? What is the -- what are the risks associated with this policy? What is the actuarial expected loss cost of this policy? What am I taking on? How does this fit with the rest of my portfolio on the claims side? Is there likely to be fraud associated with this claim or not?

Those are each points and questions that they will come to us regardless of whether they have manual tasks that get them to that process or even in an agentic world, they will still need to answer those questions, and we largely believe to use our data and content to answer those questions. So that's why the AI dialogue with the customers is whether or not they are rebuilding their own workflow from an AI standpoint, the conversation they're having with us is how can that AI-based workflow interact with your content in an efficient way.

And we've heard a lot of talk lately about token costs, right? And we've heard examples of software businesses that had a start change in their economics as they ratcheted up the amount of AI that was available to their clients. In your instance, walk us through sort of how both those branded products like XactAI, but also the cloud-enabled products, what does the tokenomics of those products look like?

Yes. Tokenomics on the different products will vary according to the pricing model of those products, which is going to vary as to what fits the market best. For the connectors, we do not bear the token cost, the client does. I said the client had to have a Anthropic subscription as well as a Verisk subscription. So they handle that separately. That doesn't impact us or our cost base. On the XactAI side, yes, the license -- there's a license price for that product that, yes, should cover the token cost. And if that changes, then ultimately, the license costs might potentially have to change.

Got it. But I don't think we need to worry about the insurance industry, token maxing particularly.

Yes, that hasn't been their opportunity so far -- or their experience so far, I think nonetheless, whether they are at max or not, so to speak, and maxing, they are absolutely like every other industry looking to ensure that they have the best ROI for what they are spending on insurance, and we intend to be a partner in that discussion.

Understood. Let's maybe shift gears to capital allocation. Verisk has this nice model of pretty fairly consistent 6% to 8% with margin expansion on top of that, driving good double-digit EPS growth. But you recently introduced a target to return 75-plus percent of free cash flow to shareholders. I recognize there's some fluidity around these discussions, but you also recently had a large acquisition that -- or midsized acquisition, let's say, whose status has changed, it was on and now it was off and now it might be back on again. Just walk investors through maybe what they should know about that AccuLynx situation and what that would -- what impacts that would or wouldn't have on your capital return framework?

Yes. So on the AccuLynx acquisition specifically, it was an acquisition that was signed just over a year ago in late July. For a number of reasons, it was terminated at the end of 2025. And there is now active litigation around that termination. So I won't give a lot of comment on that other than to say it's under appeal at the moment. And it is being handled on an expedited basis as litigation goes. So the time line, we do expect within -- on the order of months to have some visibility into outcomes there.

As to our overall capital allocation, it continues to be -- first, beginning with the generation of our very strong free cash flow and then looking to invest in our business organically and with acquisitions, probably at the moment, focus more on tuck-in size acquisitions, and then returning capital to shareholders in the form of dividend and share repurchases.

Yes, with that commitment of over 75% of free cash flow on an ongoing basis, given the strength of our investment-grade balance sheet and our 2x to 3x debt-to-EBITDA range, which even today, we're at -- in the middle of that at around 2.5x debt-to-EBITDA. So we have significant balance sheet capacity to fund whatever tuck-in acquisitions we may be interested in.

Got it. But that would include -- if this were to go a certain way, that framework would not be materially disrupted by this acquisition.

So, yes. So if the situation were to be that we were going to end up proceeding with the AccuLynx acquisition, number one, we would have the capacity to do that on an all-cash basis. Probably in the immediate aftermath of that, that would reduce the 75% -- that would temporarily pause the 75% of free cash flow return to shareholders. But we would -- I think we would relatively quickly delever and be able to return to that position.

Got it. That's very helpful. One thing that's sort of, I would say, unique to Verisk or appreciated by the long-time owners of the company in public markets has been you and Lee, your CEO's focus on return on invested capital. We like to look at, sort of, how these are structured and designed and measured by your Board. And about a year or 2 years ago, they switched from measuring your performance on an incremental ROIC basis to an absolute ROIC basis. And I know it feels like it's in the weeds, but ROIC is very much in focus for you guys. So maybe you can touch a bit on that transition from that incremental measure to the absolute measure. The target for you guys has been impressive, 25%, I think is the target number in the proxy. So maybe you can just lay out for us what prompted that change and how you guys are thinking about ROIC at this juncture of the business?

Yes. ROIC is very important for us, holding ourselves accountable to what returns we're driving on capital is absolutely, we think, one of the things we should be held accountable to, whether it's organic investments or inorganic investments. And our Board has supported that focus. Investors have supported that focus. The change from incremental ROIC to just absolute ROIC was one that largely came actually in our discussions with shareholders. The feedback that we heard was we like the incremental ROIC concept, but it is difficult to measure. There's complexity to it, and it's hard to compare across peers as we looked at the peers and of course, with the compensation committee of our board and looking at metrics and stuff. There weren't many others out there that had an incremental ROIC target.

And so for simplicity as well as the fact that we were now kind of post the divestitures that we've talked about, the feedback was for simplicity to have the ROIC metric, which also is maybe more intuitive, both how you measure it and also kind of what those numbers mean, like what good looks like. And so that was the -- what it says about us is that we were just kind of open to that investor feedback in a more simple and a more simple metric to continue to drive accountability.

Got it. Got it. And obviously, the simplest way to hit that number is to grow organic revenues as fast as you can. The next way to hit that number is to continue your margin expansion, which obviously you did well on the last few years and have committed to sort of progressing forward on that. Then another piece of that would be, of course, are you deploying capital towards M&A effectively? Are you reducing the amount of invested capital through buybacks? But -- maybe on that M&A piece, again, talk about the inorganic opportunity in front of you. What do you look for in an acquisition? And in the past, you sort of said, "Hey, look, we feel like we're -- there's a lot of opportunities right now?" Are there a lot of opportunities right now?

Yes. So within acquisitions, we said we've kind of got -- our priorities are roughly three priorities. One is proprietary data sets and anything that would enhance our own proprietary data -- sorry 0 -- I should have given 0, which is the filter of is this relevant -- is this acquisition relevant to our insurance businesses or not? We are solely focused on the insurance industry. Within the insurance industry, priority one is proprietary data.

Priority two is expanding the total addressable market even within the insurance industry, whether that's geographic or maybe segments of the insurance industry that we hadn't addressed before or, I don't know, excess and surplus would be an example.

And then priority three is anything that can enhance the workflow or the efficiency or the use of our data for customers. So those are sort of the priorities within the insurance industry. We do see opportunity out there, not as much that's attractive from a scaled and transformative business, but we will always continue to look and stay active in the market. It helps us stay sharp as to what's out there and what we should be keeping in mind for our own businesses.

Yes. And a perception that I've always had, and correct me if you think I'm wrong here, is that because you have these 98%, 99% retention rates, you're in 100 of the top insurance providers, all hundreds of top insurance providers in the U.S. for P&C, is that you really have the platform to scale a solution that might be too early stage for another company to acquire? And so as long as it has product market fit and is good, the bones of the acquisition are good. You don't need it to be a material revenue generator, be later in its maturity curve. You're willing to buy earlier-stage companies. Is that a fair assessment? And is there any other thing we're missing in?

No, it absolutely is. And it is one of the -- it has been one of the drivers of success for us. We talk about, for example, the life insurance business that we acquired when we kind of entered into the life insurance space has been a software product that sells to life carriers. It was something in which we saw a great product and remain -- and continues to be a great product.

Their growth had been kind of mid-single digits when we acquired it, and it has delivered strong double-digit growth every year thereafter, in part because of the customer footprint we are able to bring to the table, even in the life insurance space where we hadn't historically had a presence, the Verisk name carries weight and as well as just the scale and investment-grade balance sheet of a strong partner for the insurance industry, for the Life Insurance carriers.

So yes, we drive growth on acquisitions that way. And I would add -- I think it is also an underrated strength in driving our strong returns on invested capital because even our organic investments -- if we get a product right, if we get an investment right, we can scale it very rapidly across our footprint. We don't -- I joke, we don't need to go take a lot of people out to lunch to get to know Verisk and know who we are. We can bring them innovations right off the bat, which has helped us scale our innovations.

That's really fantastic. We've got 30 seconds left. So maybe I'll end it with this question open ended. But Elizabeth, when we have you here in this room again next year, what is one thing investors are not asking you about now or aren't talking about with respect to Verisk now that will be highly relevant to this room next year?

Great question. I think you are asking the question now, but I think a year from now, I'm really excited about what traction and further updates we can give on some of our AI product developments and starting to see the adoption more broadly across the industry.

Great. Thank you so much for your time today.

Thanks a bunch. Great to see you. Thanks for the attention.

All right. Good morning, everybody. We'll keep this on time. Thank you for being here, Day 2 of our Global Financial Services Conference. For those of you who don't know me, my name is Manav Patnaik. I cover business and information services for Barclays. One of the companies under coverage is Verisk, and we're very pleased to have Elizabeth Mann, the CFO, back with us here again.

So thank you for being here, Elizabeth.

Thanks so much, Manav, for having us, and thank you all for coming.

So I thought the best way to start would be to just talk about current trends implied in your guide, the long-term guide. But maybe before that, let's just knock the question around the AccuLynx deal out of the way, just the kind of the latest update with the situation there.

Yes. So I think we've announced -- so the AccuLynx transaction, which had been under litigation, we have appealed the decision now. And so that is under appeal. The hearings would start in late October. So it is continuing to be handled on an expedited basis as the original trial was.

Got it. Okay. Fair enough. So maybe just getting back to this year's guide, maybe just remind us how the first half performance was and then kind of the implied second half guide in there.

Yes. Thanks a bunch. Yes. So our revenue for the year, the first half had been impacted by some near-term revenue headwinds that we've talked about. I'm sure we'll get into that. Short-term factors, the weather impact being the most significant and primarily on the transactional revenue growth side, which is only -- which is 17% of our revenues. Our subscription growth at 83% of our revenues continues to perform well.

We've also -- and then to your question on the second half, we've continued to say our expectation is that those short-term factors are we are -- working through them and working past the time that they would have an impact. So we expect to see continued accelerating growth into the second half of the year with an expectation that we deliver within our "long-term" or Investor Day guidance range of 6% to 8% organic constant currency growth. We expect to be in that range in the second half of the year. And we've also said we are confident to deliver another year in that range, meaning the full year '26 to be in that range.

Got it. Maybe just first follow-up on the subscription side of the business. I mean the first half of the year, the numbers actually got better despite some of what we thought were probably tough comps heading in. So what are some of the drivers of that slight acceleration in that subscription growth?

Yes. I think we continue to see good outcomes and good interest from our customers on the value that's being delivered across the platform. And it's not just one business or one upgrade. It is really across our largest businesses. Our forms, rules and loss cost business, which is our largest business, continues to see the benefit of Core Lines Reimagined and the significant technology investments that we've put into our core products, including AI-based innovations. So that continues to express itself in the subscription growth there. Our Catastrophe and Risk Solutions business just saw the launch of Verisk Synergy Studio, the new platform there, as well as the new model for hurricane, for U.S. hurricane risk. So that's seeing strong subscription growth as well.

Got it. And I guess on both those, I mean, it sounds like you have a new platform and then Core Lines Reimagined is also new capabilities. So is there scope for further acceleration driven by those 2 -- like I guess, how early in the innings are we on those 2 contributors?

Yes. I think we will continue to see the benefit of those play out over a long term, meaning a couple of years. Both of those businesses, as some of our largest businesses, have very long-term contracts with customers, meaning 3 years to 5 years for some of the largest customers. And so the benefits and enhancements that we've built in are being monetized in the subscription renewals. And so we do anticipate continued strength.

Okay. And so I guess -- but it's also fair to say that the current elevated or higher growth rate of subscription is sustainable. And then as the contracts come up for renewal, I suppose you can keep adding on more of the value in there. Is that fair?

That would absolutely be the intention. We don't give specific, specific guidance by subscription or transactional revenue. We're targeting the total. But yes, absolutely, we do continue to see positive engagement with our customers.

Got it. And then maybe just touching on Core Lines Reimagined, it was obviously a heavy lift for 4 to 5 years for you guys. I guess what is the -- I know it never ends, but what is the end outcome today where we stand? And like what's the runway of the potential for going through this effort?

Yes, absolutely. So we've -- Core Lines Reimagined was reimagining the benefit and really primarily the delivery mechanisms and the underlying infrastructure for our forms, rules and loss cost business, really reinvesting in a product that had been deeply embedded in the insurance industry, but maybe hadn't gotten an overhaul in quite some time. And so that was a 5-year scope. We started it in '21. By the end of this year, we will have delivered the full program that was envisioned then. And most of the new and newly rebuilt content is available on core.verisk.com. We continue to turn things on module by module and line of business by line of business.

By the end of '26, it will all be available on core.verisk.com, and you won't have a need to go back to the old ISOnet platform. There may be still some customers who prefer to use it that way, but we will be pushing hard to shift them over to core.verisk.com. So that will be kind of the -- we will draw a line under the completion of the original scope of Core Lines Reimagined. It has been such a benefit and such a success that when that was designed in '21, it was -- we were doing a lot of machine learning. We were doing a lot of AI. It wasn't -- but it wasn't an environment where everybody was talking about generative AI. We've brought some of those elements into our platform already. But I think where we stand now, we will continue to see benefit. We're not going to stop investing in the product, the investment scale may taper a bit, but we continue to see significant opportunity and significant client interest in what can be done off that core content that is so valuable to them.

Got it. And maybe just a few examples on that because part of -- I think what you described felt almost like a necessary modernization of the way you have the data, the delivery and the platform. So now that you have that, can you talk about whether that helps innovation, stuff companies -- can you just give some examples there?

Yes. Let me give some examples. So the way -- so the product there is the -- it is the loss cost, meaning the industry average-wide expected loss on a particular type of risk with deep granularity, not just by class of insurance, general liability, but by business type, say, commercial -- small commercial, by state and by type of risk. So it's not just commercial liability for a restaurant. It is separated out into 13 different grades of restaurants by state. So very granular views of risk based on the industry-wide average and industry-wide views of the risk and really no one carrier has enough penetration or sees enough data. That's the core value of the product.

The delivery method was where, as we talked about, it had maybe been underinvested.

And so if you go back before Core Lines Reimagined, those loss costs were primarily delivered by PDF in tables that customers would deliver -- would download and probably manually key in into their own internal systems or into their own workflow. That we knew was not how work should take place in the 2020s, even before anyone started talking about AI interaction with it. And so we've rebuilt the platform. We've rebuilt the underlying data. I should say this was all enabled because in the 2010s, we moved that core data set to the cloud and on modern database infrastructure. So that was almost step 0 of Core Lines Reimagined in the 2017 to 2021 era.

So we've got our database, our industry-wide data housed and manipulated in modern data methods. Of course, this was also an important prerequisite in being able to use and handle that data with AI and other modern methods. So delivery mechanism is more modern. Customers only download the PDF if that's still how they want to consume it. They can now access the data via API. They can access it through accelerators and integrators into their policy administration systems like a Guidewire or a Duck Creek. Today, they can -- if they choose to, they can interact with that data via an MCP using Claude. So those are some of the different delivery mechanisms.

The content -- the form content, the policy language that is so crucial for carriers. Insurance, each policy is a legally binding contract with language that really matters. It matters, first, because it has to be approved by the regulator on every line of business. In every state that you're doing business in annually, your policy form has to be approved by the regulator. Updates and changes to it also need to be approved. And then it matters also because that language is court tested. It sets policies. It assesses -- it governs the liability for what carriers are exposed to, on what risks. And so this is very legally sensitive language. It remains legally sensitive.

What hasn't changed on our rules business is the number of actuarial experts, legal experts, local legislative experts that we have that is giving input into that forms language, which is far more efficient for us to do once versus each carrier in the industry doing that analysis and hiring those people themselves. That hasn't changed. What has changed now is the ability to interact with the forms language in much more modern ways, not -- again, not just working with the PDF. We actually built a data structure underlying those forms and that policy language a couple of years ago before -- again, before ChatGPT and other things. So we have a modular data form underlying the forms and the policy language, which enables much easier and better interaction with that form.

And so you were asking for specific examples of how does this save time. It used to be, even 5 years ago, if an underwriter at a carrier was taking a look at this year's policy, they said, "Okay, I read there was a legislative change in Illinois." It's going to change my commercial property form language. They would download this year's form. They would have to search through and find the relevant paragraph and figure out how the language had changed. Now it is much more digitally interactable. You've got a map, you've got legislative monitoring. You can click on the state, what legislative changes were made, click through what policies have changed, click through actually have these policies changed in other states, and where has it changed my exposure.

So that's -- those are all the things that are enabled now in the forms business that have been enabled by Core Lines Reimagined, and you can easily imagine and extrapolate from that how carriers might use GenAI to interact with that to build their own modifications on top of our forms or to create their innovations on forms language. To be clear, any innovations that they make with those forms, number one, will need to be also filed and approved by the regulator. They can do it themselves from scratch, but that would mean taking legal liability on the full form. It would mean having that infrastructure to build the full form, and it would mean full regulatory review of that new policy.

Or they can start with the industry-wide gold standard starting point. They can download that. They can say, "I've tweaked it in these 3 places." Because of our infrastructure with Core Lines Reimagined, it's much easier to identify where those 3 places are that they may want to tweak, and they can file that for approval and get reviewed just on those 3 modifications as opposed to the full form from scratch.

Got it. Okay. Thank you for that.

Sorry for that. It was long answer, but I wanted to bring to light what is one of our -- really our core businesses and our core value proposition and what we continue to provide to the industry that is still valuable even in this world.

Got it. One of the other initiatives you mentioned briefly there was the kind of MCP delivery of data. So can you just help us appreciate like how much of the data that you guys have today is available through that and what the strategy with MCP is going to be going forward?

Yes. The MCP that we have today is for convenience on the part of our carriers. What they see is the loss cost, which is the table, the industry-wide average. It is what we would call -- that is what we would call the output. You could -- maybe you would call that an analytic that's based on the internal raw data that is contributed across the industry. So they can see. They can interact with that loss cost data. It's the same thing that they get access to in their core subscription, but now they can ask questions of it, "Why were loss costs trending down in Florida over the last couple of years?" It's because of regulatory reform. But -- so they can ask business-related questions, they can integrate it into some of their other things. But I think the key thing to know is that's the loss cost table that is our IP that is created and being monetized and accessed through the MCP connector, it is not the raw data that's contributed across the industry.

Got it. So when you say for convenience, I guess, it's just another delivery mechanism, but there's no uplift in pricing or some kind of a premium attributed to accessing that data?

At the moment, no. We are looking -- we are assessing the value that is created for the industry in accessing the data in that way and interacting with the data in that way. And if we believe there is value that's being created as they use it and interact with it, we will charge for it, and we will monetize that.

Okay. And then maybe a couple of other examples of AI. I think, on the call, you mentioned XactAI. So what is the uplift or what are the new features of that?

Yes. So the new features on XactAI is a number of AI tools that is added to the core software, XactAnalysis or Xactimate, that's the software in our Property and Restoration Solutions business. It's used by the carriers themselves and the contractors or third-party adjusters to develop an estimate and approve an estimate for property repair associated with an insurance claim. So a tree falls on a house, maybe in a hurricane, maybe not. The contractor goes on site, the insurance adjuster goes on site, and they build an estimate. They say, "Okay, here, let me assess the damage, let me take photographs of the damage, and then I build an estimate." And it's going to take -- it was 3 windows that were broken. "I need this much wood for the frames. I need this many panes of glass."

The labor, which is a very hard part to develop pricing on. It's going to take -- this is a job that's going to take 3 people, 6 hours of work each. "And here's the cost of that in this region at this moment in time." So it is both the software that develops that estimate. It is the pricing data, both materials and labor that populates that estimate. And so that's what happens. The contractor, the adjuster develop the estimate. It goes to the carrier. The carrier approves it. The carrier assesses, "Is it in line with my rules and policies and compliance? Is this an appropriate estimate in this region and for this type of work?" The AI features enable the process and the development and those processing of that estimate much more quickly.

So now if you take a photo, it can auto-populate, "Oh, I see it's this type of window. It was this type of glass," and it will suggest this is what you're going to need, and here's the price from the pricing estimate. Obviously, that gets reviewed and adjusted. But compare that to -- it saves a significant amount of time for the adjuster versus taking a picture, going back, having to look at a price list, having to look at trying to assess what each element in that photo is, maybe forgetting a couple of things and having to go back to it later.

Got it. Maybe just one moment to go back to the Cat Synergy Studio. I mean one of your main competitors has also introduced or has introduced their own platform. Is there a trend in the industry? Is it just AI capabilities allowing for this platform? And then also, just for you, how should we think about whether that starts creating uplift in that specific business?

Yes. So the platform -- our platform or our competitors' platform were not designed as AI-specific innovations, but they will have -- they already do and may have further AI enhancements or obviously, AI was used to develop the platform. I think it was more that they were built and created to have more modern and much more powerful infrastructure on which to run the catastrophe models. So it used to be the catastrophe models were run on-prem, accessed on a platform that was an on-prem build. Now it is truly SaaS and can use as much power or compute as you might want.

So I think industry standard used to be to run 10,000 paths on a Monte Carlo. But if you want it, if it's appropriate to have a more robust view, you can now run 100,000 views of risk. You can take and modify each of the parameters associated with the risk or with the portfolio that you have. So it's much more interactable and you can kind of take your own view on risk. And we can say, "Well, look, our expectation for the assumptions that you should use are this, but you may -- you can kind of take and modify those platforms."

Okay. And then the rollout of the studio, I know your competitors talked about it, it'll be a nice pricing uplift for many years. Is it the same for you guys?

Yes, yes.

Okay. And so maybe just putting all this innovation, I'm sure there's more, but together, it sounds like a lot of it is being monetized through kind of your pricing uplifts in your renewals as opposed to direct the incremental revenue. Is that fair? Or how would you kind of break that out?

The ones that we've talked about, so Core Lines Reimagined, Catastrophe and Risk Solutions, those are fairly mature products that are deeply embedded in the industry. And so there's an expectation of what the product is. And so yes, those innovations will be monetized through pricing on the core subscription. Something like an XactAI, which is more of an add-on, that is a separate SKU, a separate revenue line that a customer can opt into or opt out of and pay for accordingly. So that you'll start to see the monetization over time.

Okay. And then maybe somewhat tied to this, if you go back to the last Investor Day, you actually raised the component of your growth that was pricing by 50 basis points. So can you just talk about the reason behind that? Maybe it was anticipation of all this innovation? Just curious.

Exactly. It is both anticipation of the innovation as well as increased comfort that we have in being able to monetize that based on the demonstrated success of what we had done with primarily Core Lines Reimagined before that. And so if I rewind in 2023, we had said we expected pricing to be 3 to 4 percentage points of our 6% to 8% growth. We actually delivered right about 5%, and we -- that was both monetizing product innovation through pricing, yes. It was also, in fairness, had a contribution from the strong premium growth environment, which I'm sure we'll get to. So that helped the price increases there.

With that confidence of having significantly overdelivered on that range, we raised the range from 3.5 to 4.5. So if you like -- so 3.5 percentage points of annual growth, we would target to come from price. If you like, that gives room for a little bit less pricing benefit from the premium environment versus the 5% we had already delivered, while saying that we believe the pricing benefits that we get from product innovation, we expect to be sustainable and to continue.

Got it. That 5%, the 100 to 200 basis point outperformance versus your '23 guide, like can you attribute how much of that was premiums versus your own initiatives?

We haven't quantified it, and it's not -- it's actually not concrete or formulaic from a premium standpoint. So I couldn't tell you even if I wanted, but it was clearly both were in there, and that was our framework for.

Okay. And so maybe let's just touch on the premium topic and maybe rehash again as we do every year. What the relation to the net written premium number is versus your contracts and how you look through those?

Yes. So we set the stage when we became independent from the industry that we would grow as our customers grow. And so our contract renewals had an input into the renewal price increase that came from the customers' premium growth. I think that's a great revenue model. It ties our growth to an externally observable growing market, which is the insurance and the insurance premium market. And while any given year, it may vary a bit, we've had a couple of years of very strong premium growth. But on average, we've got an input into our pricing that is growing mid-low to mid-single digits. So that is a contributor to our pricing growth.

We also have the opportunity to take our own Verisk price increases in addition to the premium growth. So both of those things are inputs into the growth rate. We say it's about 20% to 25% of our revenues now that are on contracts that have some input from that premium growth component. It's not directly formulaic, but it is a supporter of that. So we probably grow faster in stronger premium environments and a bit more moderated in softer premium environments. There is -- I should -- the one other thing I should add is there's a 2-year lag on that premium growth dynamic.

Got it. And maybe if you could just remind us of the stat you've given before in terms of -- you said, in a softer market, which is what we're seeing now, you would expect a moderation of growth. How much does moderation imply?

Yes. So the historical view -- and each year is different, and there's always different dynamics. But when we went back since -- we said this at our Investor Day, when we went back since we went public in 2009, and we classified the years into soft market years or hard market years, the years that were soft market years, our average, and this is just organic constant currency growth in our insurance business throughout this time, it was 6.8% in the soft market years, it was 7.3% in the hard market years. So you can see in there, there's a bit of a headwind when the market is softer or a bit of an acceleration in a hard market. But at the end of the day, it's only moderate and both of those kind of average out to our 7% historical average growth rate.

Got it. And I don't remember the premium growth in that -- in those periods that you talked about. But like, for example, you said the last few years have been really good premiums, right, in the upper high single digits. And now you said we're kind of low to mid. I mean, I think the first half was like low single digits thus far. So is that delta also encapsulated within that?

That's about the range. I don't know the exact averages in those years, but the highest years were high single digits. We may have maybe 1 year tipped, barely touch double digits. That's kind of the high end of the range. The low end of the range, some years in that time period, you've actually seen premium growth being negative, and we've continued to grow even in those environments. But yes, more recently, kind of the last couple of years have been high single-digit premium growth, which is very high. And you've probably read and heard about this, if not experienced it yourself as an insurance consumer, this year, it is moderating. So yes, for the first half of '26, we're seeing low single-digit premium growth. It varies by line of business as well.

Got it. Maybe we'll switch quickly to the topic of weather. Just -- I think in the last update, you said weather was tracking below average or light versus what you had assumed, I suppose. So maybe just some more color, flesh out exactly what those assumptions are and what you're seeing today?

Yes. So our business -- our Property and Restoration Solutions business that I talked about before gets revenue by helping process claims associated with property repair. Last year was -- and so it can get benefits in very active weather years, which certainly was the case in '23 and '24. 2025, as it happened was a very light weather year. It was the first year in a decade that no named hurricanes hit landfall in the U.S. That is a good thing for homeowners and a good thing for policyholders and a good thing for insurance carriers. It was a headwind for revenue associated with claims. I want to be clear, our business is mostly subscription. And even in that business, we have been converting more and more customers to a subscription basis. So the transactional piece is kind of the incremental piece.

But because of the stability of our revenues, people have been watching that transactional revenue as it's maybe one of the swing factors. But with a business as stable as ours, 25 basis points or 50 basis points moves the needle. So we've been watching those weather activities. Because of the subscription nature of our business and because this is only incremental, we plan and forecast for "an average" year of weather, which is what we've done consistently throughout. In '23 and '24, we significantly outperformed that average year of weather. '25 was a much lighter weather year.

Going into '26, I would say we planned for an average year of weather. So far, it appears to be a bit on the lighter side. I don't think that doesn't -- that's not necessarily a headwind versus 2025. To be clear, we don't anticipate that it would -- it didn't change our guidance range. This is just modest variability within the range. I think the trends that we're seeing right now in mid-September is playing out as we roughly in line with where we -- what we saw and what we expected as of the end of July when we spoke at the end of our second quarter call. So relatively light, it's mid-September. There hasn't yet been a major hurricane in the U.S., which again is a good thing, and is kind of in line with how we talked about our guidance before.

Got it. Okay. Thank you for that. Maybe this is a good time just to help us appreciate what all is in the transaction business because I know subscription is a majority, but you get, I think, the majority of the attention on the transaction side. So what exactly -- like, what is the mix of the different items in that transaction business today?

Yes. And let me start with our goal is to maximize revenue across the portfolio and our goal for each of our products and businesses is for them to develop and establish the revenue model that works best for that business and its customers. And so each of our businesses tends to evolve to a mix of subscription and transaction. Across the portfolio, again, we're about 83% subscription, 17% transactional. So what's in that transactional revenue? There are some businesses where we have -- where it's really more of a usage-based or a volume-based business, and we have a traditional price volume. That can be -- some of our underwriting data products. So in the UDAS part of the pie can have products where it is a data pull that is typically correlated with an underwriter underwriting a piece of business.

On the claims side, we have some businesses that are, as I said, associated with volumes of -- typically number of claims. That is often a subscription with an overage tier that correlates with the number of claims. The other area that we have is services businesses. So where we have some software businesses on the life insurance side. On the specialty business side, we have a services component. These are not kind of heavy implementations. They're pretty quick, but we've found it enables our customers easier access and improves the sale of the license revenue to have some support in implementation. So we've got some services revenues in there. And then the final piece, which is volume -- kind of falls in that volume category, is the weather elements, claims associated with the weather. Those are the largest parts of our transactional revenue portfolio.

Okay. That's helpful. Maybe just on the broader topic of AI. I think at your Investor Day, you did a pretty good job in outlining how much of it is proprietary data, et cetera. Just a few lingering questions that we get. So the first one tied to you guys is more -- over the years, Verisk has talked about the softwarization of the business. And so the question is more, how much of that is just true software that could be vibe-coded away versus how much of that is integrated with your proprietary data?

Yes. I think we gave the pie chart at the Investor Day. A lot of our products are built on contributory data sets from across the industry, which we view as very differentiated. There's another significant part that is proprietary data where we're the only ones that -- where we create it and have it in-house. It's not easily vibe-coded away. There may be, in some cases, a couple of other providers of similar data, but we have strong performance and strong proprietary data there. We had another category that we call proprietary analytics and IP. And those are things that aren't exactly data businesses, but are built on very deep domain knowledge that it would be very difficult to replicate. The catastrophe models, for example, would be in that category. Or the -- we talked about the Xactware, the pricing and restoration -- Property and Restoration Solutions business.

Some of that business, yes, is software or it is delivered as software, but it is software that is built on top of and enables the access to the pricing database, which is proprietary and very difficult to replicate, certainly, for example, on the labor pricing side. So that would go in that bucket. That -- those categories together amount to 85% of our revenues. There's only 10% of our business that we would call true software and another maybe 5% that are services-related businesses in the casualty space or in the international space.

So those would be the ones -- and the software, in theory, you could say, "Oh, maybe that 10% could be vibe-coded away." We still think it is pretty -- it is either based on deep domain knowledge in very regulatorily sensitive spaces like life insurance, for example, or it is software that is protected by a network characteristic. For example, in our Specialty Business Solutions product where the software, again, is enabling something that is transactions between a broker and a carrier, and you have -- the software is where they come together to transact.

So we may have businesses that are software, but what's differentiated may not be the software itself. It's more the characteristics of the business where it's a network-type business, and it's where the industry comes to interact to exchange financial transactions.

Got it. The other one we get is, like at this conference, I think a lot of the large carriers are here, and I guess they tell investors, "Yes, we're going to use AI to do a lot more with our data and bring stuff in-house." In your discussions, is that -- does that impact your business? Does it create opportunities? Just how would you react to that?

Yes. We think it creates opportunities for us. There have been -- for many decades, Verisk has been a strong participant in the industry. We contribute a lot of data. We contribute a lot of insights and value to them. From a scale perspective, our revenues are 30 basis points of the total industry premium. So for every $100 a carrier gets in premium, they spend $0.30 on the Verisk data. That is -- we think that is good value to them to protect the insights and the views on selecting the right risk, from pricing it appropriately and then processing the claims accordingly. As you can see, there's many things outside of that $0.30 that they may do on their own, they may each take different approaches. The large carriers will have more bandwidth to invest, and we'll do some things with their own data.

The small and midsized carriers may be interested in doing some of the same things, but might be interested in productizing from different products from us to enable them to have the same reach and scale. I think another thing that may be underappreciated in this is our -- we are already speaking across the industry. We have that contributory data angle that gives us a perspective on the full industry that we can share back to them and create value even for those that are doing things in-house.

And when you think about the fragmentation of the industry, insurance is a very large market. The largest players in their largest lines may have 20% or max 30% of the market in a certain line. As I have been in rooms with customers that say, "That's great. I have 70% of the market that I don't see, and I need to know what's happening there to be able to price the best risk." So that is our kind of our fundamental value proposition that we think will be maintained as an element of even what the large carriers are doing.

Got it. Okay. In the 2 minutes we have left, maybe let's end with capital allocation. Since you backed out of the AccuLynx deal, you did a big bunch of buybacks. So maybe just remind us of current leverage levels and kind of the plans for buybacks and other capital allocation priorities.

Yes. So leverage at the end of the second quarter was 2.5x debt to EBITDA. That is in the -- at the midpoint essentially of our 2 to 3x debt-to-EBITDA range. So -- and we have significant and growing free cash flow. So we are fortunate to have significant capital allocation firepower capacity and bandwidth. We will -- we can -- we have the opportunity to continue buying back shares in the market. Yes, the AccuLynx appeal is pending, and we'll have to see how that comes out from a large allocation standpoint, but we're very comfortable with our leverage range. If -- and this is a big if, but if that transaction were to ultimately go on and be completed, we have the bandwidth to do so on an all-cash basis and get back to our 2 to 3x leverage range within a relatively short period of time.

Okay. All right. We'll end it right there. Thank you so much, Elizabeth. Appreciate the time. Thank you, everybody.

Thank you. Thanks very much for attending.

Good day, everyone, and welcome to the Verisk Second Quarter 2026 Earnings Results Conference Call. This call is being recorded. [Operator Instructions] We will have further instructions for you at that time. For opening remarks and introductions, I would like to turn the call over to Verisk's Senior Vice President of Finance and Investor Relations, Ms. Stacey Brodbar. Ms. Brodbar, please go ahead.

Thank you, operator, and good day, everyone. We appreciate you joining us today for a discussion of our second quarter 2026 financial results. On the call today are Lee Shavel, Verisk's President and Chief Executive Officer; and Elizabeth Mann, Chief Financial Officer. The earnings release referenced on this call as well as our traditional quarterly earnings presentation and the associated 10-Q can be found in the Investors Section of our website, verisk.com. The earnings release has also been attached to an 8-K that we have furnished to the SEC.

A replay of this call will be available for 30 days on our website and by dial-in. As set forth in more detail in today's earnings release, I will remind everyone that today's call may include forward-looking statements about Verisk's future performance, including those related to our financial guidance. Actual performance could differ materially from what is suggested by our comments today. Information about the factors that could affect future performance is contained in our recent SEC filings. A reconciliation of reported and historic non-GAAP financial measures discussed on this call is provided in our 8-K and today's earnings presentation posted on the Investors section of our website, verisk.com.

However, we are not able to provide a reconciliation of projected adjusted EBITDA, adjusted EBITDA margin and adjusted EPS to the most directly comparable expected GAAP results because of the unreasonable effort and high unpredictability of estimating certain items that are excluded from projected non-GAAP adjusted EBITDA, adjusted EBITDA margin and adjusted EPS, including, for example, tax consequences, acquisition-related costs, gains and loss from dispositions and other nonrecurring expenses, the effect of which may be significant. And now I'd like to turn the call over to Lee Shavel.

Thanks, Stacey. Good morning, everyone, and thank you for joining us. Today, I will provide a broad overview of our second quarter financial results. We will also offer a perspective on our industry engagement including client discussions focused on the use of advanced technologies, including the evolution of AI and the current operating environment. Finally, I will wrap up with some updates on recent groundbreaking innovations we have introduced into the market, including the release of Verisk Synergy Studio for the catastrophe risk market.

I will then hand the call over to Elizabeth for more detail in her financial review. Turning to our second quarter results. Verisk delivered organic constant currency revenue growth of 5.8% with balanced growth across underwriting and claims and demonstrating the sequential acceleration that we previously anticipated. Revenue growth was underpinned by an 8% increase in subscription revenues, demonstrating the stability and value of the solutions we provide to the insurance industry, helping them make better decisions. These are supported by our broad connectivity and deep client relationships we have within the industry.

Our focus on efficiency and cost discipline drove organic constant currency adjusted EBITDA growth of 7.4%, delivering another quarter of very healthy margins. Growth was modestly ahead of our expectations and reflected the short-term factors we previously described, namely the carryover impact of the very low weather activity, tough compares from strong renewals last year and a work stoppage in a federal government contract. We continue to have confidence that the resolution of these short-term factors and core growth momentum will result in continued sequential improvement in revenue growth as we move through the second half of the year.

Moreover, we expect 2026 to be another year of performance in line with our Investor Day targets and reaffirm our 2026 financial guidance. Throughout the quarter, our client engagement was very active. We held several executive sessions across underwriting with top national and regional carriers discussing how we can support clients in the current operating environment, as well as our broader strategic plans, including our AI strategy. Additionally, we hosted client-specific emerging issues workshops within underwriting focusing on topics including data centers, AI risks and regulations and quantum computing, where we discuss company-specific exposures.

For one top 20 carrier, we hosted 3 different sessions on artificial intelligence that were attended by almost 400 underwriting professionals across their enterprise. These engagements are a further demonstration of the critical role we play in the industry through our deep industry expertise, data analytics and thought leadership. That same combination is why we continue to win new data contributions. So far this year, we have onboarded 8 new core lines contributors and 10 contributors to our new excess and surplus data set. And with those excess and surplus contributors now online, our data set covers over $18 billion in historical and current premium. Specific to the operating environment, the first half of 2026 has continued on the trends experienced in 2025, namely improved combined ratios and robust industry profitability, helped by unusually low catastrophe losses.

In fact, 2026 is currently tracking from global catastrophe losses to be below the $100 billion mark for the first time since 2020. With profitability improvements and rate adequacy satisfied across many lines, carriers have turned their attention to driving growth, resulting in price competition and softening markets. As we mentioned last quarter, this dynamic is most pronounced in property and commercial property in particular, where pricing is soft and volumes are lighter. We continue to watch how these dynamics shape client activity particularly as it relates to transactional usage. It is in these types of markets that carriers are increasingly focused on underwriting discipline and risk selection rather than relying on broad-based rate increases.

Our comprehensive data sets and analytic insights underpinned by our continued investments in data currency and data coverage can best help segment and understand risk, helping our clients navigate through these dynamic times. In our conversations with clients, AI remains one of the most important topics, and Verisk has partnered with the industry to help them move from experimentation into production deployments and ultimately to scaled adoption when the industry is ready. As carriers expand their use of AI, they continue to turn to Verisk as the trusted source of data in the industry. Currently, those conversations are increasingly centered on accuracy, efficiency and repeatability as well as driving return on investment from their investments.

To meet these needs, we are investing in techniques such as retrieval augmented generation or RAG and broader context engineering capabilities that help improve the quality of AI-driven outputs by better managing how large language models, access, interpret and apply information. This is all further enhanced by our highly cleansed and structured data sets and deep industry expertise, which is leveraged through the semantic layer of AI processes where we provide data structure, context and rules that make large language models work more effectively to deliver consistent and predictable outcomes.

More importantly, our goal is not simply to adopt the latest AI tools, but to apply them in ways that deliver measurable return on investment and value for clients by combining advanced AI capabilities with Verisk's high-quality and proprietary data assets, deep industry expertise and established industry standard workflows while also creating connections across the broader ecosystem. We believe this positions us well to help clients navigate the next phase of AI adoption while strengthening Verisk's role as a trusted strategic partner across the insurance ecosystem.

As a specific example, in May, we announced our first collaboration with Anthropic, launching 2 Verisk MCP connectors for Claude, which bring our trusted regulatory grade data and analytics directly into conversational AI workflows in an underwriting and claims use case. These connectors enable clients to interact with Verisk's proprietary underwriting intelligence and clean solutions using natural language, helping them access insights when, where and how they need them. These connectors were developed in partnership with Anthropic on an expedited time line from initial discussion to production and public launch and we are the first insurance data provider with MCPs available with Claude.

This was made possible by the earlier foundational investments we made in data organization and infrastructure making our data entirely AI-ready as well as experimentation and development of independent large language model applications. Importantly, the architecture is designed to maintain the governance, security and trust our clients expect, with data retrieved only within the client's Claude session and not used for model training. Interest levels across our client engagement are building along with usage with a top 10 carrier already using the MCP. We're excited by the early client feedback we have received, and we are actively developing additional connectors both with Anthropic and with other frontier model companies that can deliver value to our clients.

Additionally, we are excited by the opportunities to develop agentic capabilities in coordination with and on behalf of our clients. Last quarter, we disclosed one of those initiatives to develop a next-generation digitally native agentic underwriting platform with a global insurance firm and we are excited with the progress that we are making. We are also in the development stage of agentic capabilities in our life solutions that will build on our conversational Ask Max feature to embed autonomous capabilities within the platform. We're also encouraged by the early traction we're seeing with our generative AI solutions that have had scaled engagement and premium audit AI is a good example.

Premium audit AI brings natural language access to our premium audit rules and classification content directly into our clients' underwriting and audit workflows. It's still early as we are now in the first renewal cycle post the launch, but we're beginning to see it show up commercially. The incremental value we have added is supporting stronger renewal growth. It's a proof point for how we're embedding AI into our proprietary content to make our offerings more valuable to clients. In our claims business, we continue to see strong momentum in Exact AI which we launched in the fourth quarter of 2025 and have continued to enhance with new capabilities.

Exact AI embeds AI directly into the workflows of insurers, adjusters and restoration professionals, helping clients automate time-consuming tasks such as summarizing claim information, labeling photos, extracting key data from documents and generating estimating recommendations. The result is faster claims handling, improved productivity and more consistent outcomes for policyholders. Adoption has accelerated significantly since March, the number of Exact AI users has increased nearly 10x, and we now have almost 7,000 licensees on the platform. The feedback from clients has been overwhelmingly positive with strong demand for additional functionality.

As a result, we are continuing to invest in our innovation road map and expand Exact AI capabilities across the broader Exact wear suite helping clients realize even greater efficiency and value from their claims operations. The rapid adoption we are seeing reinforces our conviction that AI will become an increasingly important driver of efficiency, consistency and better outcomes across the property claims life cycle. During the quarter, we also reached an important milestone in our catastrophe and risk solutions business. with the on-time and on-budget launch of our reengineered U.S. tropical cyclone model and Verisk Synergy Studio, our new cloud-native platform for integrated catastrophe modeling and risk analytics.

Our updated U.S. tropical cyclone model redefines the U.S. hurricane risk modeling by integrating significant advances in climate science, hazard modeling and vulnerability analytics to provide a more accurate, transparent and realistic view of individual risk and portfolio exposure across insurance, reinsurance and capital markets. Specifically, the model includes key scientific advancements, which provide a more physically realistic view of how tropical cyclones evolve, including the impacts of wind, storm surge and inland flooding. Additionally, as catastrophe models are used to increasingly inform decisions in industries outside of insurance, including housing, infrastructure, capital markets and climate risk disclosure, this new updated model is designed to support risk evaluations with results that can be used across all segments.

Verisk Synergy Studio, our cloud-native platform is designed to help clients make better decisions in an increasingly complex risk environment. The platform brings together advanced analytics, high-performance computing and modern workflows in a single environment, allowing clients to analyze larger and more complex portfolios generate insights faster and better understand the drivers of risk and loss across their exposures. The first release of Verisk Energy Studio includes our complete global model suite in our latest next-generation modeling framework giving our clients immediate access to our latest views of catastrophe risk for every model around the world. This allows clients to run more sophisticated analyses, evaluate risk more efficiently and make more informed underwriting and capital allocation decisions without having to navigate a patchwork of model vintages.

By combining leading science with modern technology, we are helping clients gain deeper insights into risk while improving the speed, scale and transparency of their workflows. We have already onboarded our first clients onto the system and the initial feedback on performance, scalability and keeping our commitment to deliver on the schedule we promised has been incredibly positive. We have a robust pipeline of additional clients scheduled to migrate to the platform, through the remainder of the year.

As a further enhancement to our catastrophe risk solutions business, we closed this week on the strategic tuck-in acquisition of McKenzie Intelligence Services, a geospatial intelligence and event response company, specializing in global real-time catastrophe and conflict event analysis. MIS will become part of Verisk catastrophe and risk solutions. We believe that the strategic combination of MIS' real-time geospatial intelligence together with Verisk catastrophe models, risk analytics, weather analytics and claims solutions will give clients a more complete view of unfolding events so they can assess impacts, prioritize response and support stakeholders more effectively.

Before I close, I want to announce that Nick Dean, our Chief Information Officer, is leaving Verisk after 2 decades. I want to thank Nick for his partnership and key contributions to Verisk, which include leading the modernization of our computing platform successfully migrating from the mainframe to the cloud, strengthening the infrastructure supporting reliable delivery of client solutions and helping position the company well for this next phase of AI innovation. With Nick's departure, Jeff Migrett, our CTO, will step into the role of interim Chief Information Officer. We are confident in the bench strength we have in place within our corporate IS&T organization and will commence a search for a permanent replacement. I'll now turn the call over to Elizabeth.

Thanks, Lee, and good day to everyone on the call. On a consolidated and GAAP basis, second quarter revenue was $806 million, up 4% versus the prior year, reflecting contribution from both underwriting and claims. Net income was $229 million, a 10% decrease versus the prior year, while diluted GAAP earnings per share were $1.75, down 3% versus the prior year. The decrease in net income and diluted GAAP EPS was driven by a divestiture at the end of 2025 as well as the higher year-over-year tax rate, increased interest expense and higher legal fees incurred in connection with ongoing litigation. This was offset in part by higher operating results and a lower average share count. .

Moving to our organic constant currency results adjusted for nonoperating items, as defined in the non-GAAP financial measures section of our press release, our operating results demonstrate continued solid growth across both underwriting and claims. In the second quarter, OCC revenues grew 5.8% compounding on the 7.9% OCC revenue growth in the prior year period. This was a sequential improvement from the first quarter in both underwriting and claims with reported OCC growth of 5.6% in underwriting and 6.1% in claims. The quarter's performance was modestly better than our expectations primarily due to stronger-than-expected insurance-linked securitization activity. The reported results continue to be impacted by the continued carryover effect of a lower level of weather-related events last year as well as the work stoppage in a federal government contract.

Subscription revenues, which comprised 83% of total revenue in the quarter, grew 8% on an OCC basis compounding the 9.3% growth in the prior year period. The growth in subscription revenue was driven by strength across our largest subscription-based businesses, including forms, rules and loss costs, catastrophe and risk solutions and antifraud analytics and reflects strong price realization in renewals, expanded relationships with existing clients and the addition of new logos. The resilience of our subscription revenue underscores the strength of our business model and the critical value our solutions deliver to clients. In formed rules and loss costs, our investment in Core Lines reimagine continues to drive strong price realization through subscription renewals as clients experience the additional value we can provide through the transformation of the platform.

During the quarter, we released another 7 new client-facing modules and remain on track for 25 releases in 2026, delivering even further platform functionality and value to our clients. Within catastrophe and risk solutions, we delivered another quarter of strong growth, driven by the addition of new clients and some notable renewals that provide upside to multiyear growth. As Lee mentioned, we are excited to announce the launch of Verisk Synergy Studio in June with our first clients already onboarded and a pipeline for additional clients to migrate on to the platform. Additionally, we released our reengineered U.S. tropical cyclone model, which delivers comprehensive advances in how hurricane risk is quantified and applied and is exclusively available through Verisk Synergy Studio.

In anti-fraud, we delivered another quarter of strong growth, driven by good price realization, early renewals, adoption of newer innovations, including digital media forensics, and healthy growth in adjacent markets. Our transactional revenues, which comprised 17% of our total revenues declined 4.2% on an OCC basis, a sequential improvement from the first quarter. The declines were primarily driven by 3 factors: one, tougher comparisons from overages in the prior year as well as lower volumes in our commercial property business that could persist in the second half of the year; two, the carryover impact from lower weather events in our property restoration solutions; and three, lower volumes in our international travel business, primarily related to Middle Eastern travel disruption.

This was offset by strong ILS issuance within our catastrophe and Risk Solutions business, which we do not expect to benefit the third quarter. Moving to our adjusted EBITDA results. OCC adjusted EBITDA growth was 7.4% in the quarter, compounding on 9.7% growth in the prior year period. Total adjusted EBITDA margin, which includes both organic and inorganic results were 57.5% down 10 basis points from the prior year. As a reminder, the prior year quarter's reported margins benefited from a foreign currency translation impact, which contributed 120 basis points to margin net. Excluding this nonrecurring benefit, we delivered solid margin expansion driven by revenue growth, disciplined expense management and ongoing global talent optimization initiatives.

Moving down the income statement. Net interest expense was $53 million in the quarter compared to $36 million in the prior year period due to an increased debt balance as well as higher interest rates. Our current leverage level is in the middle of our targeted range of 2 to 3x adjusted EBITDA. Our reported effective tax rate was 24.6% compared to 22.7% in the prior year quarter. The year-over-year increase was driven by lower tax benefits from a lower level of employee stock option exercise activity. Adjusted net income decreased 1.9% to $259 million. The year-over-year decline in adjusted net income was the result of a divestiture and higher below-the-line items, including higher interest expense and a higher tax rate.

Yet we still grew diluted adjusted EPS by 5.3% to $1.98 per share, reflecting our capital return activity, which reduced our weighted average share count by 6.8%. On a reported basis, net cash from operating activities increased 50% to $366 million, while free cash flow rose 58% to $298 million. The increase was driven primarily by growth in operating profit as well as the timing of certain cash payments. We remain committed to returning capital to shareholders and during the second quarter, we paid a cash dividend of $0.50 per share, an 11% increase from the prior year. Additionally, we initiated a $200 million accelerated share repurchase program which was in addition to the $1.5 billion program we entered into during the first quarter.

In total, we retired 8.5 million shares during the first half of 2026. Both programs concluded earlier this week, and we currently have approximately $800 million remaining under our share repurchase authorization. We are pleased to deliver continued momentum in the second quarter and are reaffirming our outlook for 2026. A complete list of all guidance measures can be found in the earnings slide deck, which has been posted to the Investors section of our website, verisk.com. We continue to expect consolidated revenue in the range of $3.19 billion to $3.24 billion. Adjusted EBITDA is expected to be between $1.79 billion and $1.83 billion with adjusted EBITDA margins of 56% to 56.5%.

We continue to expect net interest expense of $190 million to $200 million and our effective tax rate to be in the range of 23% to 26%. This results in adjusted earnings per share for the year in the range of $7.45 to $7.75. A few things to note as you update your models and think about pacing for the final 2 quarters of the year. First, we continue to expect a gradual recovery in OCC growth rate for the remaining 2 quarters of 2026. Second, the transactional revenues in the second quarter benefited from strong ILS activity that will not repeat in the third quarter as this is a seasonal market. Third, while it is still early, the hurricane season is off to a slower start as June and July have had limited storm activity.

These factors could continue to exert pressure on transactional revenues in the second half of the year. Still taking everything together, we remain confident in our ability to deliver results in line with our financial guidance for 2026 and in line going forward with our Investor Day targets. And now let me turn the call back over to Lee for some closing remarks.

Thanks, Elizabeth. In summary, we are experiencing the growth rebound that we anticipated in our financial results. Additionally, the increased value in our products from AI functionality is improving price realization and the increased engagement from our clients and partners as they recognize the value of our data and expertise in generating real returns on their AI investments. This has further enhanced our confidence in the operating momentum we are building in the business. We continue to appreciate all the support and interest in Verisk. Given the large number of analysts we have covering us, we ask that you limit yourself to 1 question. With that, I'll ask the operator to open the line for questions. .

[Operator Instructions] Your first question comes from the line of Toni Kaplan with Morgan Stanley.

Lee, you talked about industry profitability continuing to be strong, and that could lead to maybe a continuation of the soft market. But on the other hand, you're helping insurers with profitability tools. And so I was hoping you could talk a little bit about historical periods where you've been in this part of the cycle and how growth typically plays out just given perhaps decelerating pricing dynamics, but maybe more cross-sell. And so just trying to get at should we be prepared for a few years of growth towards the lower end of your growth algorithm? Or can you like more than offset that through like some of the new product launches and upselling and things like that?

Yes. Thanks, Toni. So I think you touched on a couple of the elements that we've talked about previously, and I want to reaffirm, first for some historical context, our experience has been in soft markets that we've generally grown at approximately 6.8% organic constant currency growth rate. And again, hard markets 7.3%. So both of those are well within the range that we are -- that we talk about -- that we talked about at Investor Day. And I think you also correctly identified that in these periods, the value of our data sets in assessing risk and supporting good pricing decisions become more important. And I think that's something that we have certainly heard in our client engagement as we've been talking about where we can be most helpful. As you heard, in our comments on the call, the level of engagement of clients wanting to have discussions around AI impact on pricing, pricing on other kind of market dynamics is evidence of that. .

But I think the most important point that I would center on is the fact that our growth is driven much more by the value that we are able to deliver to our clients and our ability to participate in that. And I think over the past 6 months and certainly the past 12 months, the ability for us to utilize our data and our expertise to support our clients value journey in using AI has been very clearly demonstrated across our businesses. And so despite the softening market, while that will have an effect, I think we're more bullish on our ability to create value for our clients and for the industry by supporting their adoption of AI in workflows and processes in connecting the industry and we're beginning to see that in the pricing dynamic that we described for the premium audit AI and exact AI. So I think that is certainly a difference that we've had relative to prior periods. So hopefully, that gives you good context around the growth -- our growth perspective in the softer market.

Your next question comes from the line of Andrew Steinerman with JPMorgan.

I definitely call out what you just said about June and July hurricane activity. I'll also kind of mention that summertime is not typically hurricane season. But yes, you're right, you have to kind of look with what we have now. So with that, have you assumed a low level or a typical level of hurricane activity when you consider the full 2026 revenue guide. I have one more point to this. And have you considered the return to an El Nino, and I've also read about a Super El Nino being a near-term possible revenue driver for Verisk climate and catastrophe risk analytics and our insurance clients asking Verisk about El Nino preparedness at this time. .

Thanks for the question, Andrew. Yes, our guidance, as we typically do, the range still considers in the base case and average year of weather activity and of hurricane activity. So what we're highlighting is if that plays out to be lighter as again, and there's different views from the experts as to how it may play out this year. But playing out lighter would be a bit of a risk on the transactional side. Again, these differentials are all in the overall context of our business and even within the guidance range that we're talking about.

As to the discussions on El Nino and the risk to insurers. It's something that our catastrophe and risk modeling team is engaging with clients on. They're discussing the latest weather impacts. And I'll highlight the acquisition, the small acquisition that we just announced today of McKenzie Intelligence Services as a geospatial intelligence platform and event risk management is one that can, over time, help to give kind of real-time insights to events as they unfold.

Your next question comes from the line of Kelsey Zhu with Autonomous.

Lee, how are you thinking about your channel partner strategy today? I think we've talked about previously how Claude and OpenAI could be helpful as distribution channels. But are you also looking at partnering with some of these AI companies for model co-development? And if so, are there specific areas or processes that you're interested in joining forces with them to add that intelligence layer .

Thank you, Kelsey. Certainly, we are engaged in discussions with all of the significant frontier model companies. Tangibly, you saw our announcement of the cloud connectors and MCP solution that had 2 applications, one to underwriting and one to claims that were starting points in demonstrating what our data sets could do by pairing them with natural language capabilities of the model. And the feedback from our clients have been strong. In many ways, those were test cases or proof points that we could roll out very quickly. One thing that we've heard from clients is they want us to focus on what can we deliver now that has an impact and not conceptual on what's in development, but what they can use now and that was a demonstration of it. .

And coming out of that was a clear appetite for us to go deeper and broader in those types of connectors, which will require some further development in a number of our product areas. So specific to your question, we believe that, that type of engagement and work with the model companies is going to be beneficial for our clients. It will, I think, take time for clients to test the products, understand how they apply and develop it, but there clearly is enthusiasm and engagement. We are doing this across the board with the model companies. One thing to your question on distribution, I think we would observe that our ability to provide distribution to the insurance industry as the last mile, particularly to workflows is a very important part of dimension. Our connectivity to claims professionals, underwriting professionals, risk professionals, it gives us an ability to identify where those models can be best applied, most effectively applied in order to generate real returns to our clients.

And that's clearly something that's been recognized by the model companies that we've been in discussions with and I think that strengthens our position in helping them and helping our clients bring that model capability together with the data sets.

Your next question comes from the line of Scott Wurtzel with Wolfe Research.

Just wondering if you can talk a little bit more about the lower volumes on the commercial property side and why you would expect those lower volumes to persist in the second half of the year.

Thanks, Scott. I'm going to turn this over to Saurabh Khemka, who runs our underwriting businesses to give you a perspective on the commercial property, what we're experiencing, what we're hearing from clients. .

Absolutely. So overall, in the commercial property line and the insurance industry, what we're seeing is soft pricing, and it's a cyclical thing that happens. And what the behavior that it's driving is that our clients are looking at their business, they're looking at maybe not quoting as many of the opportunities that are out there. And then when they do make the quotes, they're also looking at how much they're spending on underwriting data and analytics to analyze that business. So those impacts are being felt in our transactional part of our business. I do want to say the underlying business remains very strong. So the subscription side of our business is good and continues to be healthy.

Your next question comes from the line of Gregory Peters with Raymond James.

One. So for my question, I know most if not all of the large property casualty companies have walled off LLM general access to the data and pricing infrastructure so kind of a 2-part question. Are you seeing any shift among your customers and attitudes towards LLM access? And then can you just step back and remind us how you're preserving your unique data assets amid the growing proliferation of AI? .

Great. Thanks for the question. So we will certainly -- data security has been a critical question and issue that we have managed very carefully over decades with our clients. So it is kind of central to our DNA to make certain that we are protecting our clients' data and any application or new technology that we're developing is done with careful consideration and discussion with them about the rights to utilize that data and that technology. And so that has informed our governance approach to the use of data. We have had a data policy and an AI policy for many years, and that serves as a great guide for us to make certain that we are protecting that data.

Now 2 additional points. One is that in our work with the Frontier model companies, it was absolutely critical that the use of the data was controlled in the client's Claude instance and could not be used to train models. That's a protection that we think is important for our clients, certainly important in protecting our overall data access. So that is a demonstration of our care in managing access to those data sets and protecting them. It is front of mind in making sure on an ongoing basis that our clients' proprietary information is protected. And while we are finding ways to effectively utilize that data for what we feel are valuable applications that our clients are looking for inquiring that data.

And so given, for instance, the success that we've had with premium audit and client uptake in the use of that AI product as well as an exact AI, just 2 examples across the businesses. I think the one thing that I would have a different point of view is if our clients are definitely interested in applying AI to the data sets to support their underwriting or claims functionality. But we're doing that in a very safe and carefully thought-out process.

Your next question comes from the line of Manav Patnaik with Barclays.

Lee, I just wanted to touch on the AI monetization today. And you kind of alluded to 2 examples, which I was hoping you to elaborate on. So the MCP Connector, I think you mentioned that one of the top 10 carriers is already using it. So I was just wondering what are the pluses and minuses between, is it all now? Or are they using this instead of something legacy. And then kind of the second part was, I think you talked about Exact AI, growing 10x. I think you said with 70 licensees like so how is that contributing to growth and how we should think of that over time?

Thanks, Manav. And clearly, as a topic that we're focused on and we're approaching this with the recognition that this is still evolving. We're applying new technologies. We are at the core, assessing how this technology is creating incremental value for our clients? How can we -- how are we helping them create a real return on their investment in AI. So if we can demonstrate, and I think we believe that our clients clearly see value would be gone beyond the step of just testing it but a demonstration that it improves efficiency, productivity, accuracy. And I think there will be several channels in which we are currently monetizing and expect to continue to monetize that incremental value, one most immediately. And while this at a scale level is not significant for us yet, but I think has -- clearly has the potential to support ongoing growth is simply improving the value of our pricing renewals upon subscription. .

We've talked a little bit about the -- our ability to do that in our underwriting data on renewals specifically to the premium audit product. Similarly, in our Exact AI licenses, we are expecting to be able to capture the incremental value that we're delivering there through these additional products on that front. And I think that ideally is kind of the broad-based ability for us to realize value as we have in the past, as we have what the core lines reimagine where more current data sets, expanded data sets we're able to capture that value in increasing subscriptions over time. Additional channels may include as we see appetite and early adoption of AI functionality, potentially some transactional pricing on an initial basis for clients to test and experiment with new AI applications.

So I think there are aspects where we could see pursuing an additional transactional model, but we would want -- we would probably want to see that migrate into a more stable and growing subscription business over time. And then thirdly, we have a number of projects that we've talked about in the past where the ability to deliver an agentic AI platform or another AI solution may enable us to generate license fees for that software for that platform that our clients will view as an appropriate way for us to monetize the investment that we've made in delivering that solution.

So I think all 3 of those will be pads I think we are realizing that already on the pricing front. I think as we move from piloting to greater client usage, we could see the transactional element and we are clearly exploring on the licensing component on a number of the platforms that we're pursuing. Overall, I mean, I think that we come out of the last 6 months in our experience with Anthropic and other frontier AI model companies with increased confidence that the value of our data, the value of our ability to support our clients AI journey and investment returns on that technology to be a clear upside for us over the next several years.

Your next question comes from the line of Faiza Alwy with Deutsche Bank.

I was hoping for an update on the auto business because I know you had talked about some new data sets and new solutions that were supposed to come to market at some point this year. So I just wanted to get a sense of where you are and how you're thinking about that business going forward.

I'm going to turn that question over to Saurabh as well.

Yes. Thank you, Faiza. I think on the auto side, we continue to make progress there. The competitive environment remains robust. But our focus on differentiated platforms like Lightspeed and new analytic objects that we're bringing out in our coverage or business is delivering good results for us in terms of Lightspeed being adopted by more customers and good engagement on these differentiated analytics with other customers. So we continue to focus on that strategy as we go forward.

Your next question comes from the line of Henry Hayden with Rothschild & Co.

I had a follow-up on MCP monetization. So is this kind of volumetric -- is there a volumetric component to how you're charging for this? Or is it all covered on a subscription basis? And depending on that, how should we think about incremental margins versus variable usage cost and higher storage costs to vectorized data sets. Just to help contextualize that, how should we think about the kind of pace of adoption? You mentioned you have 1 carrier on this now, but as you roll through the rest of the client base. .

Yes. Thanks for the question, Henry. On the -- specifically on the MCP connections, it is included in the client base subscription. Their Claude costs or token costs are covered by them separately. So that is not an expense to us directly. More generally, I think we have strong governance on AI spending across our enterprise. And as for the pace of adoption and the rate of diffusion across the insurance industry, I think you've heard Lee talk about that, clients are adopting. We are ready to move with them as they move into more systematic deployment. But I think given some of the discussion, you've heard some of the insurance focus on governance, on data security, protection and other things. So as the industry works through and moves through that, you will see our monetization opportunities increase gradually over time, but it will probably be a slow and steady build.

Your next question comes from the line of Andrew Nicholas with William Blair.

This is Tom Roesch on for Andrew Nicholas. I was just wondering if you could provide some color on what kind of supports your confidence in the acceleration in second half organic growth rates. It sounds like transactional, at least from the storm activity is softer through the first 2 months, but also do recognize that, I think last quarter, it was like a historic -- last third quarter was at historical low and storm activities so I was just curious, like what is the business you think or giving you the most confidence on the acceleration in growth in the back half of the year?

Tom. A couple of things. Two things that give us confidence in the build. One is the subscription growth rate, again, that's 83% of our business is where we have some visibility into that. I would add that supported. We had highlighted the federal government contract and a work stoppage there. That work stoppage now has been lifted as of the beginning of the third quarter for a 1-year term. So that work has resumed. That was -- I will add that was always the assumption that we had going forward. So this is now the removal of that risk. So those are some of the elements of the steady acceleration. That said, I do want to highlight it may be more of a sort of steady step-up in that year-over-year organic constant currency growth rate.

We highlighted some of the headwinds on the transactional side. That strong ILS contribution that we had in the second quarter is not likely to repeat. And so I think you've heard from us, we do have a slightly more cautious view on the transactional revenues, especially in the third quarter with the property market and of course, the weather as a TBD so taking all that together, we may see less of the upside in the third quarter and more of an acceleration into the fourth quarter as the year plays out, again, with full confidence in the full year range supported by those subscription revenues.

Your next question comes from the line of Jeff Meuler with Baird.

Just thinking through the financial impact and timing from the synergy Studio release, is there like a platform upgrade fee that you monetize? Or is this all about upselling and cross-selling additional and more advanced models. And if you could just help me nor out for a second, you have a competitor that talks about their high def models being a real differentiator. You're calling out this like next-gen modeling framework that comes with synergy Studios. So just help me understand from a model capabilities perspective, like what's different to next-gen models? And how you feel that changes the competitive dynamics, recognizing many clients overlap and buy models for both? .

I'm going to start off and then I'm going to -- on the differentiation, and then I'll turn it over to Elizabeth to kind of talk through the kind of the pricing revenue elements to it. First, I think what's important is that, first, the models are kind of the starting point. And there, what we are releasing or what we feel are the most sophisticated scientific meeting catastrophe models with a much more physics reality oriented solution for our clients. And so with the U.S. tropical cyclone model, we think that, that is cutting a science and a leading model. Synergy Studio as a platform enables our ability on to increase the capacity of our clients to run larger simulations over longer periods which adds value to them and do that more quickly. So the capability of that platform is a significant enhancement.

And secondly, our ability to update those models is much easier for our clients than a traditional on-premises solution. Finally, I think a key competitive differentiation is a consistent economic framework so that all of our models are -- can be utilized to assess risks on a consistent basis across that entire portfolio. And I think that is a distinctive differentiation for our clients that want to understand risk on a global and a portfolio basis. So those are the elements that I think go to your question from a competitive standpoint in terms of why we think these are great products and why Synergy Studio as a new product, we'll be delivering more value to our clients. .

Yes. And I'll add in on the pricing. So first, I'll comment, all of our models are on that next-generation financial framework, and we talked about it a while ago on earnings when we kind of launched that and put all of our models on that next-generation financial framework. So that will be available on that Synergy Studio. There is not as to the pricing, there is not a specific platform upgrade fee that we're monetizing with that. We do think the overall platform itself derives greater value. And the other piece I will add to it is that some customers may choose to have that operated on a hosting basis. And so some of our customers have migrated to a hosted model and some even before even on their Touchstone platform have added a hosting component, which has added to our revenue. .

So taken all together, that is all contemplated in the Investor Day guidance for that catastrophe and risk business at 8.5% to 9% on a long-term basis.

Your next question comes from the line of Curtis Nagle with Bank of America.

Just maybe could you comment on growth in catastrophe and risk in the quarter. I think it was up double digit in 1Q. What does it look like in the second quarter? And just how to think about general expectations in the back half of the year, particularly with the -- you talked about the launch of the Synergy Studio.

Yes. Thanks, Kurt. We don't give specific disclosure on that business on an ongoing basis. It has been a strong contributor and of course, the second quarter gets -- has the securitization market as a benefit on the transactional side. But they're seeing steady uptick and performance that is in line with their long-term guidance.

Your next question comes from the line of Jason Haas with Wells Fargo.

I want to ask maybe a high-level strategic one. It sounded like from the prepared remarks you mentioned like an agentic underwriting platform that you're working on. And some of the comments around Exact AI just sounded a bit more like, I guess, like a workflow tool. So I'm curious if there's an opportunity here to use AI to maybe push a little bit more into workflows software. I know historically, you've really been more of a data come you have obviously some software solutions. But curious how you're thinking about that from a high-level perspective in terms of where you want to take the business?

Thanks, Jason. So there clearly are elements for us to integrate our data and our insights into workflows. I think the predominant path will be in integrating those data sets into our clients, either AI solutions or their existing workflows but we have had, as you've noted, clients who have asked us to work on developing a platform, which may be -- which would be a software platform or an AI platform that integrates their workflows more effectively. And we're excited about that because we clearly have the expertise, the data sets are familiar with the workflow in order for us to be able to do that. And as you also referenced, Exact AI is something that is built into our Xactware platform that services the needs of a wide range of claims companies and professionals. So yes, there is a software opportunity for us to deliver on our clients' needs for data integration, automation and modernization of their processes also connecting participants within those workflows outside of the individual client basis. .

So that level of connectivity and integration of data, we can deliver in a variety of ways in partnership with our clients' preferred platforms, particularly among our larger clients, in partnership with AI solutions that may be developed by the frontier model companies as we've done with the Anthropic MCPs or in specialized platforms that we have developed for clients that want us to deliver that capability. At the end of the day, what we're focused on is leveraging our data sets and our expertise to create more value for the clients, and we have a variety of means to do that.

Your next question comes from the line of Ashish Sabadra with RBC Capital Markets.

I had a question on AI as well. So thanks for sharing the client engagement and the monetization for AI. Previously, it was noted that sales cycles had elongated due to AI. I was wondering if you have seen any shift in that trend recently? And then another question on the same topic would be a question that we get is as insurance companies are launching industry-specific LLM, is there a risk that they could move some of these processes in-house. So as we think about the puts and takes, how do we think about AI as being a net positive? Or is there some headwinds from moving some of the processes in-house.

Yes. Thanks, Ashish. I'm going to take the second part of the question first. And yes, we do have -- there are clients that are developing their own LLMs. And I think the opportunity with them for us remains as strong, if not stronger, because the utilization of the unique data sets that we have, the standardized and cleansed data are just as relevant to them in this context as it would be for a frontier model company. And those have been discussions that we think are -- that we have had and have supported our clients with. I would also use that as an opportunity to say, the context or the semantic layer of what we have delivered and our retrieval augmentation generation technology is important.

Our ability to access all of that data and deliver what's really relevant to them is just as important in that context. So I think we -- to us, that's a very positive development. our general experience is the more sophisticated our clients are from a technology and data standpoint, the more data that they consume, the broader relationship that we have. And on your first question, I may not have heard it, but I think Elizabeth did.

Moving to the sales cycles and the elongation that we referred to in the first quarter. I think that pattern in that environment does remain consistent. As you heard us discuss earlier on the call, there is a tremendous amount of client focus on questions of data, data usage rights, data protection. There's also our own focus on ensuring that our IP and our valuable data is well protected. So those discussions -- both sides are working through the legal terms, ensuring that confidence. In the long run, we view that as a competitive differentiator for us because we have a long history of trust with the insurance industry and the robust governance processes and robust legal team to ensure and give confidence to the clients in the protections that we have there.

Your next question comes from the line of Jeff Silber with BMO.

This is Ryan on for Jeff. I was just hoping you could help us on the EBITDA margins for the quarter. I know there was a tough comp with the FX for the year-over-year, but I was wondering if you could walk through any other drivers that drove the margins? And then just looking forward, are you still anticipating that expenses ramp for the second half of the year?

Thanks, Ryan. Thanks so much for the question. Yes, it was a strong margin quarter for us as we highlighted that year-over-year comp the Q2 of '25 included a 120 basis point impact of FX that impact is small to minimal in this current quarter. So that margin expansion is real, so to speak. On a trailing 12-month basis, we're at 56.3%, which is in the midpoint of the guidance. Factors for the strong margins this quarter are a couple. Number one, the you've seen historically, there is seasonality in our margins with Q2 often being the strongest quarter because -- in part because that ILS transactional revenue comes in at a high incremental margin and our expenses tend to build steadily over the course of the year. I think I would also just -- I want to highlight, we did -- beyond that, we have had strong expense discipline over the course of the year. And I want to highlight that we delivered margin expansion in every single 1 of the past quarters, even despite the more modest transactional revenue impact.

So I think we've had consistently strong expense discipline over that time. As we build into the balance of the year though, both the seasonality on the second half margins will have an impact, and then we will have both general timing of expenses as well as perhaps an opportunity to invest further behind these innovative products as our revenue growth continues to aerate from here.

Your final question comes from the line of George Tong with Goldman Sachs.

You highlighted AI as a driver of stronger renewals and improved price realization. Can you help quantify the contribution that AI is making to organic growth today? Is the benefit measured in 10s of basis points? Or has it already become large enough to contribute more meaningfully to organic growth?

Thanks, George. Look, it's hard -- we're still at an early stage. So I don't think that we are able to quantify, certainly its current impact. I do think that based upon what we see, we clearly think it could -- it should lift our organic growth rate to some degree. It's difficult to parse out across overall renewal and value that we're providing in other areas. But I certainly feel more confident that this is additive to our overall growth rate certainly on a gross basis and on a net basis, we see just increasing in client engagement and a recognition of the tangible value that they're getting by integrating our data sets with AI models.

This concludes today's call. Thank you for attending. You may now disconnect.

All right. Thank you, everyone, for joining. I'm Andrew Nicholas. I'm the business services analyst here at William Blair. Before getting started, I am required to inform you that for a complete list of research disclosures or potential conflicts of interest, please visit our website at williamblair.com.

With that out of the way, I'm very pleased to welcome Verisk's CEO, Lee Shavel, to the 46th Annual William Blair Growth Stock Conference. Thanks, Lee, for being here. I'm going to hand it over to Lee to give you an overview of the business.

Good morning, everyone. Thanks for taking the time. I'm sorry, I'm getting adjusted to the microphone here. But thanks for taking the time to meet with us today. I'm going to make sure the slides are working here. As an overview for Verisk, I want to try to accomplish 3 things today. The first is to give you a clear sense of the underlying core durable franchise that Verisk represents. Two, to help you understand the growth opportunity that we have to pursue to sustain the growth that we've been able to deliver with some very distinct competitive advantages and then tying that to what we think is a very strongly differentiated financial model, which has consistently delivered value for our clients over time.

And for the -- our audio specialties, is this mic up front on. I want to make sure it's not interacting with -- Okay. Excellent. Thank you. So first, for those of you that are not familiar with the Verisk model, we have started as a utility to the U.S. property and casualty insurance industry over 30 years ago.

We are entirely focused on insurance. We have about $3 billion in revenue and the distinguishing characteristics of this is a highly recurring revenue model that is largely subscription-based. And that forms a very solid foundation for -- and the economic model of what we -- of how we provide value to the industry. And what underlies the strength of that business model is the fact that Verisk sits at the center of the global insurance industry. We serve all dimensions of both risks, as you can see on the top side, from a property, auto and both from a functional underwriting, claims and even in related insurance areas such as property repair estimating and fraud detection.

And so these are all functions across the industry that we serve. And beneath all of these functions is really the core asset of Verisk, which is the connective data that Verisk gathers, normalizes and integrates into the dozens of products and functions that we use to support the overall insurance industry.

And kind of building on that prior slide, you can see the individual products that support each of these distinct areas that we are able -- where we are able to support a major global, national, regional, local market insurance provider across a variety of their products and functions.

And I think what is most important and certainly the question that we're asked most frequently is what is the durability and sustainability of those data sets. And as we discussed at our Investor Day, over 90% of Verisk's revenue is underpinned by a unique data advantage where, for instance, 40% of our revenues are tied to data that is directly contributed to us by our clients.

Now this data isn't usable as they give it to us. It requires a substantial amount of actuarial normalization because each carrier underwrites to different products to different standards with different amendments, different aspects of their policies that we need to normalize, and this isn't a theoretical exercise.

It also is one that has to meet regulatory standards because the data sets that we are providing to rate policies are used as the primary basis for rate approvals by regulators. And so it has to be actuarially sound. It has to be scientifically rigorous. And this data that we're collecting can't be acquired anywhere else. It's not publicly available. It's highly sensitive data that the carriers trust us with, and it requires a massive amount of work to normalize this data for use in these functions.

Now in addition, we also gather our own data sets. So for instance, in this building and pretty much any other building that you can see from the hotel here, Verisk has a field team that gathers detailed engineering data, fire suppression data, ground floor use and function data for this building that is very relevant to insurers that are insuring either the building or businesses within the building.

But not only that data that we gather on a proprietary basis, we also rate every fire department within the U.S. So the Chicago Fire Department receives a rating from Verisk on the basis of the quality of their equipment, the quality of their training, their speed of response.

Not only do we provide that, we provide a building code effectiveness score. So in every municipality, it's not enough to understand what is the building code, but is it actually being enforced and is it effective, critical to understanding particularly how catastrophes can potentially generate risk. So these are -- this is an example of proprietary data that we collect with expertise specific to the insurance industry. And importantly, a competitive advantage is that we have an ability to gather this data at a much lower cost than the industry would incur if they were gathering this individually. So there's a natural economic efficiency that exists.

And then the third primary component is our proprietary intellectual property and analytics. An example of this is the scientific intellectual property that we generate in modeling tropical cyclones or hurricanes, severe convective storms, wildfires, floods. And catastrophe modeling is not weather forecasting.

Weather forecasting is a component, but it's understanding how weather and insured assets interact. And there's a high degree of structural knowledge, materials, labor costs, exposures, risk mitigation that goes into that. And our models serve as a standard for reinsurers and carriers and brokers to facilitate the transfer of risk within those markets.

And that expertise is not easily obtained or integrated or certainly to set a standard that the market relies upon on a daily basis. So I spent a little bit more time on these data components because they're really important in this market environment where there's a lot of anxiety about AI disruption, and we certainly recognize that risk.

But these are not public data sets. They're utilized for both regulatory and industry standard support and are very difficult to disrupt. Now that leads us to a high degree of resilience and predictability, as you can see on this review of our revenue growth.

And you can see across this period of 15 years that we have seen a steady growth in our cumulative annual growth rate. And it's a function of both the increasing adoption of the use of data and analytics to automate and improve the efficiency of the insurance industry. So if you think about the percentage of the use of data relative to traditional human means of evaluating risk, data, technology and analytics has become more important.

It also has reflected the adoption of new technologies that facilitate a variety of industry functions such as claims, anti-fraud capabilities or the integration and facilitation of specialty risk transfer in the Lloyd's market, where we've developed software platforms and ecosystems to facilitate that.

So we continue to see the industry adopting more technology, and we're in a unique position with our centrality and our scale to deliver on that. All of that growth, if we look at it on a purely organic basis, has generated a very consistent 6% to 8% organic growth rate where we have been in that range and only been below it in 2 instances in 2009 in the midst of the global financial crisis, where we still generated a 5% organic growth rate.

And in the initial year of the disruption of the pandemic, where, again, we were still generating a 5% organic growth rate. And certainly, when you look at these numbers, you can't avoid thinking about the compounding power of delivering that consistent growth over time and particularly enhanced with the operating leverage that we'll talk about when we get to the financial model.

So with that foundation core, let's turn to the growth opportunity that we have ahead of us. Now a foundation, but by no means a governor for our growth opportunity is the overall growth in the property and casualty insurance industry. And you can see here that over the past 15 years or so, the industry's gross U.S. net written premium has been growing at about a 4% compound annual growth rate.

And has -- is projected on the basis of projections by the NAIC, the National Association of Insurance Commissioners as well as Swiss Re is expected to increase to approximately a 5% growth rate over the next 5 years. Now there are a couple of factors that are driving that growth. One is just more greater -- more risks or more assets that need to be covered and naturally inflationary factors that drove that.

But within that growth, we benefit from specific market forces that are driving more demand for data. One, as I mentioned before, carriers are looking to automate more and more workflows through automation with data sets. And AI specifically is driving the demand for greater data. AI without high-quality data sets cannot be nearly as effective. And while the focus has been in selling broad enterprise licenses for large language models, what's critical is tying that to existing workflows and data sets.

This is not only our opinion, but it's the opinion of both our clients as well as the frontier model companies that have expressed a desire to work with us much more actively, realizing that the returns from improving the efficiency of an underwriter or a claim is going to be critical to demonstrating a real return on the AI investment and certainly was a foundation for our opportunity to develop 2 connectors with Anthropic for their Claude model to just 2 of our data sets.

So the carriers are certainly driving more utilization of data. We also see in the market that the use of data for intermediaries like brokers or MGAs or even regulators is important. We're also seeing expansion in markets such as the excess and surplus market, which is an adjacent form of insurance that supplements the regulated or admitted markets where clients are giving us new data sets. And then finally, more macro trends such as affordability and climate issues and how they affect insurance markets are creating demand for new data sets.

Now with both the growth in the underlying market and these trends, Verisk brings several significant advantages in our ability to capitalize on each of these. And I'll talk about each of these in turn. The first is that -- we are a mission-critical and a trusted partner for the global insurance industry.

Our data is the backbone of the underwriting function, particularly related to regulatory rate filings. Our data is used as an actuarially reliable source of their basis for rate increases and rate adjustments. We have broader data sets than any other company normalized for their specific purposes, and we've been playing that role for decades.

And I can't understate the importance of the trust in protecting the data and utilizing the data for the industry's benefit that is a substantial advantage and a natural starting point for us as a partner. And that differentiation, I think, is emphasized on this slide.

It's a busy slide. But what I'd like to emphasize is at the center Verisk provides as an innovation hub, the scale, the quality and the breadth of data and our ability to experiment with new technologies in a way that the industry can utilize to get comfortable and to generate higher returns on their investment in technology because we have these broad data sets that we source from across the insurance ecosystem, and we're able to translate them into very tangible benefits in underwriting, claims, catastrophe modeling, compliance, as you can see, improving 80% faster growth, 3% to 4% pricing uplift, more accurate estimates, faster settlement, all of which translate into value for the industry.

And our opportunity is to make that investment, test it, prove it and deliver it to the industry. And that's certainly the game plan that we have been pursuing with AI across several fronts as we'll talk about in more detail. Our strategy has been one to engage in AI so that we can learn from deploying it internally against our data sets to enhance our own analytics and generating and enhancing our insights of what we see across the industry.

We have integrated into over 60 of our products that have allowed us to test that with clients. You can see examples that we've talked about. Each of these you can review on our website. And most recently, it's enabled us to put together in a very short order, a partnership with Anthropic, where we have been able to connect their cloud model to interrogate our analytics and facilitate an insurance underwriting professional's questioning of what's happening from a regulatory and from a loss cost standpoint as well as to evaluate and determine what the potential restoration costs are on a remodel or a repair of an existing business.

Now that certainly was an exciting step for us and one that has generated a lot of activity and interest from our clients, but we're not restricted to Anthropic. We have had conversations with other frontier model companies. Some of our clients are using other models, and we believe that our data sets will be relevant to the models.

What's differentiating is the quality and the breadth of the data. And we certainly think that models will be differentiated, but all of them are going to require the data we provide. It's not just Generative AI. We also have had a client, a very respected global insurance company that has asked us to build with their partnership an agentic AI underwriting platform.

So this goes beyond Generative AI to building agents that replicate the function in gathering data, assessing data and rating policies on a purely agentic basis. and we're excited to develop the intellectual capital and the intellectual property associated with that.

But we've also talked about a client that has decided to pursue Neurosymbolic AI. Now this is an important dimension of AI. It's actually existed for a while. The key differentiation here is that Neurosymbolic, unlike Generative AI, which is predicting the next token in response to a query and so it was a predictive path, but in many ways, a random walk just as a stock price -- in a stock price random walk context, it's -- Generative AI is not replicable and it's not auditable.

Neurosymbolic was developed to apply neural network and machine learning approaches constrained by domain knowledge so that you could have a clearly determinative reasoned outcome that was auditable and repeatable. And so we are working with the client to integrate our data sets with a Neurosymbolic model that we believe could certainly represent a very relevant AI technology for the industry and one which interestingly, insurance regulators have already begun thinking through.

And so finally, beyond that engagement, the other factor is the economic factor. We represent slightly over 30 basis points of industry U.S. net written premium and about 37 basis points of industry expenditures. Now the good news is that while it's small, it also has been growing, reflecting that increasing adoption of data and technology by the industry, but there clearly is substantial room to grow, and it speaks to the fact that for a relatively small component of their combined ratio or net written premium, we can deliver a lot of value if we can -- we continue to bring that to bear, as we have in the past on the functional efficiency with which they are handling underwriting, risk management and claims functions.

So we feel we go into this with very distinct advantages, a historical level of trust and established centrality and very high-quality data sets. And all of that translates into a financial model that has some very compelling elements. As we've talked about, it has very consistent and strong mid- to high single-digit organic constant currency revenue growth.

We have strong operating leverage that drives improved EBITDA growth off of that 6% to 8% revenue growth. And from that, the ability through capital management to drive even higher EPS growth. We have a very strong balance sheet, and we have a very well-established disciplined capital returns methodology. The growth algorithm, as we described at our Investor Day that we anticipate over the next 3 years to continue to deliver 6% to 8% organic growth of which pricing where we capture the value, both the value that we're delivering to the industry as well as underlying industry growth will deliver, we expect 350 to 450 basis points.

That will be complemented by additional up-sell and cross-sell where we have demonstrated an ability to deliver increased product sales to our growing clients, 100 to 150 basis points of new initiatives where we have new emerging technologies that we have an opportunity to penetrate the industry effectively, growth in new clients in adjacent areas such as intermediaries and on the regulatory front and then offset by a historical level of attrition that comes from consolidation within the industry.

So you can see that our growth model is one that's founded on value creation centered in pricing and expansion through both up-sell and cross-sell of new initiatives and new clients. And then from a margin perspective standpoint, naturally within the system, our ability to make that investment at a relatively low OpEx and CapEx costs delivers strong operating leverage.

We've enhanced that through efficiency gains by applying new technology like cloud computing as well as AI that we believe will improve our efficiency in data ingestion and analysis and then offset to some extent by portfolio impacts from some of our faster-growing businesses that are operating at lower margins, but we believe that, that's a good trade-off as those margins are actually improving as they scale as well.

And we expect from that to continue to deliver between 25 to 75 basis points of margin expansion annually. And all of this is guided by very clear and consistent capital allocation priorities. Our priority is organic investment, particularly in this environment where we have demonstrated an ability to invest in our data sets, both their quality, the currency, the expansion of those data sets that our clients have been willing to pay us for because they see increased value in their utilization and the broadening of the applicability of those data sets.

We look to invest in M&A where we see an established product that we can ramp much more effectively with our centrality and our scale and our position in the business. And where we don't see adequate returns from an M&A standpoint, capital is returned to our shareholders and will utilize to maintain our strong financial position from a leverage standpoint.

We generate a lot of strong core free cash flow, and we're working to improve that through working capital efficiency. We have an investment-grade rating, and we have easily maintained a 2 to 3x debt-to-EBITDA target.

So we're working from a very strong financial perspective, and all of that supports our long-term financial targets of organic constant currency revenue growth of the 6% to 8%, magnified through operating leverage and margin improvement for strong EBITDA and EPS growth and an attractive capital return with over 75% of free cash flow returned to shareholders.

So hopefully, that gives you a sense of the very strong durable base that we have, the ongoing growth opportunity to deliver on the mission that we've had for decades, which is being a true utility to the global insurance industry where we can leverage those data sets and our scale to deliver strong incremental value to the industry and all of that reflected in a financial model that is very durable, sustainable margins, strong organic growth and tremendous opportunities ahead of us. So I think that pretty much covers everything that I have, Andrew.

Great. Lee, if you don't mind, maybe we have a few more minutes. Just one kind of high-level question on the state of the industry as a whole. Can you talk about where kind of net industry premium growth looks, loss ratios and maybe more holistically, your clients' willingness to spend on data and kind of the secular trend there?

Sure. Thanks, Andrew. So as I talked about earlier, the net written premium as a whole, obviously, a diverse set of risks. Across those businesses, we have hard markets, we have soft markets.

And consequently, it tends to vary from year-to-year. We've done an analysis that we've shared previously that when we look at our organic growth in hard markets versus soft markets, our soft market performance, the growth rate has generally been 6.8% and in hard markets, it's been 7.3%.

So it's about 0.5 percentage point of difference, both of them round to 7%. So it's an influence, but it is not the primary driver of growth. It's the value creation that I've spoken about where we can apply a technology to our data sets and deliver value for the industry and participate in that.

Now as we are in certain soft markets, in hard markets, when everything is going well, there's a natural expansive element, which is great to have. But in soft markets where pricing risk becomes more importantly, our view is -- our experience has been that the data sets become more valuable and our clients tend to lean into that dynamic.

And I think the second part of the question is how are our clients communicating to us about how they are thinking about utilizing our data. And I'll start with, I think, the strongest experience that we've had, which is we continue with our largest, our most sophisticated clients, the ones with the largest scale businesses to see a consistent renewal trend of renewal of our multiyear agreements at or longer than the last renewal.

This has been true for the last 12 months on all of our major renewals and with price increases that reflect the increased value that our clients are experiencing from our most recent investments in our core lines reimagine effort.

But we also have other data sets that we've been expanding that are new sources of growth. It isn't just the pricing element, but uptake on our excess and surplus capabilities, uptake on our catastrophic risk modeling new platform, Synergy Studio, is something that our clients see incremental value in managing their risks more actively.

And then finally, I think the thing that's been most promising so far this year, Andrew, is after a period of experimentation with AI, the recognition from our clients that finding ways to tie this to our data sets and to their existing workflows is critical to them generating a return on investment.

Now there are efficiencies that can be accomplished, but the ability to enhance that with broader operational and industry loss data, our experience at a micro level for those that have been experimenting with it are substantial. And I think that, that is going to propagate across the industry as we find ways to embed or as some of the frontier model companies as this technology diffuses into the insurance industry.

And I think that will be a slow adoption process. The industry for both regulatory reasons and natural conservatism tends to be very cautious in how they adopt technology. But one thing I can guarantee, our data will continue to be valuable in that process, and we will continue to be a natural partner to the industry.

Great. Thank you very much, Lee, and thanks, everyone, for joining. We are moving to Adler for the breakout here in a few minutes. Thanks for joining us.

Good afternoon, everyone. Thanks so much for joining us today. My name is Kelsey Zhu. I'm the information services analyst at Autonomous. With me on stage today, I'm very pleased to welcome Lee Shavel, the CEO of Verisk. Thanks so much for joining us today. Lee. Really appreciate it.

Thanks for having us, Kelsey. It's great to be here.

So AI has probably been the hottest topic within the information services sector this year, and I think that's a good place to start. And I know Lee, you recently launched your MCP server. So maybe talk us through a little bit more about the rationale behind that launch. What data is included in the MCP server? How do you protect your data? How do you protect your customers' data and the pricing and the target audience for this MCP?

So we're just going to dive right in. So let me start, and I will get to that. Kelsey has shared that we may have some generalists in the room. And so I just want to provide a very brief overview. Verisk started out as a utility to the U.S. property and casualty insurance industry. And we were there to serve a role in collecting data, collecting regulatory filings, managing those on the part of the industry. And it gave us access to an extraordinary wealth of data, particularly loss costs and the ability to standardize forms that enabled us to help the industry understand loss experience across individual product lines and also to develop an intermediary relationship with regulators.

And that as we began to apply more data science and analytics approaches to the business, we were able to build on that and acquire and develop other businesses such as our catastrophic risk modeling business that models hurricanes, severe convective storms, wildfires, floods, we also built claims oriented businesses that capture potential fraud risk in claims and allows carriers to estimate losses from claims that are filed with them, all of which serve the industry and importantly, in a classic utility fashion, we have the ability to invest in a data set, invest in an analytic or a technology that we can rapidly scale across the industry. And the industry benefits from that because they get the value without all individually thousands of insurance -- individual insurance companies without having to make that investment. And so that dynamic is still kind of critical to what we do and recognized by our carrier clients for the value that we can bring to the industry.

And so with that, we have been working with AI in classic forms for at least a decade. We've developed procedures and policies to make certain that we are deploying AI with responsibility, with protections for the data, for protections for privacy and generative AI has come along in the last few years, and certainly captured the kind of collective imagination. And we have been working to deploy generative AI and large language models into our data sets. So this is not something that is new to us. We have developed products that support our clients but we've recognized that with the frontier AI model companies that there is a moment where many of our clients are interested in utilizing those models in their work.

And so we were connected to anthropic as they were developing their insurance strategy, and they recognize that we were a unique and valuable player in the insurance markets, and they said we would really love to develop 2 use cases or connectors to your business. And we went through in the course of about 4 weeks, over a dozen potential applications, some of which may follow these initial 2, but we came up with 2 connectors that connected the cloud models to an underwriting data set for our forms, rules and loss costs that allows the model to interrogate the data, and it's important to understand that this doesn't give access to the underlying data, but it allows the model to query that data in the same way that a subscriber, one of our client subscribers might gather data on loss costs by -- on a state-by-state basis or a business line by business line basis and accelerate their ability to pull that data, understand the analysis to inform their underwriting decisions.

In addition, we have also developed a connector use case that connects the cloud model to our restoration analytic, which allows a restoration professional to interrogate our materials and our labor costs to evaluate if I need to do a restoration on a kitchen or on a garage, what might be involved, what level of quality am I looking for so that it can come up with an estimate for that renovation or that repair very quickly. So these are natural language interfaces that much more efficiently gather and connect that data set. That we have seen in both cases, demonstrated at a micro level, the ability to get that information faster to get to a more connected analytics associated with it, and we believe will create value to the industry as a whole.

Now importantly, there's nothing exclusive about this. We have clients, some of which have cloud licenses, some of which have chat GPT licenses, co-pilot licenses. And so we do think this is a broad opportunity for us to show how our data sets enable and deliver much more tangible value than simply buying a generalized cloud license. And a lot of our clients have had the mandate to do that, and they have told us, look, we -- this is interesting, but we really need to demonstrate where there is economic value, and that means tying it and interacting with the data sets and with the workflows that are out there. So we're excited about what we accomplished in a short period of time. It builds upon the knowledge that we've developed in AI, and we believe it's just the start for, I think, what we can do for the industry and our classic utility role.

Got it. That's a super helpful summary. I guess one of the main investor debates is really in the future, what kind of role do you think large language models would play in the insurance industry? Are you thinking of them, the cloud, open AI of the world? Are you thinking of them as your incremental distribution channel? Are you thinking of them as potential competitors or maybe partners for co-developing some of the models and analytic solution that you will introduce in the future?

Yes. Kelsey, I think those are 3 -- we think about those 3 alternatives. I think our view is that this is clearly a distribution channel for us and the data sets. And it is -- I think that view is bolstered by the fact that we have this happen repeatedly where there is a new technology, for instance, cloud data storage or SaaS computing applications where our data has been critical from an industry perspective and integrating it into those solutions. So as they were adopting cloud storage, the ability for them -- for our clients to deliver data through that technology and access it became a critical function.

With many SaaS solutions, particularly policy administration systems, many of them rely on our underlying ratings data, and so that became an ability for us to support the value that they were creating with those technologies and to find new means for us to monetize the value of the industry as a whole. And so when we think about the value opportunity for us, I think we feel, based upon the micro experience that we've had and extrapolating to a macro view, if AI can improve underwriting efficiency and accuracy by 5% to 10% and claims efficiency and effectiveness by 5% to 10%. Across an industry with a massive expense base dedicated to those functions, that's a substantial amount of value. And our ability to participate and help facilitate that value is the opportunity that we'll pursue.

So I think, first and foremost, a distribution channel. We've also seen that as our most sophisticated clients increase AI utilization, they want to use more of our data sets. So the number of products that we're able to sell as we've talked about at Investor Day, which has shown a steady progression and a correlation to the size and scale of our clients will benefit. But the third point is they, I think, will also be effective partners where we're able to bring together the AI element with the data element and the process element to create a true intelligence layer that facilitates overall industry functionality.

And so I think those are the 2 primary channels. We don't view this as competitive to what we do. The work that we do to gather data sets, to normalize them from an actuarial standpoint, to cleanse them to integrate them with other data sets is a very unique proposition. We have contributory data sets that can't be accessed publicly that our clients are very sensitive to the use of that data. And so in many ways, we're as much a custodian as we are an user of those data sets on behalf of the industry and good AI requires high-quality data sets, and we're happy to continue to play that role.

Yes. Well said. I guess one of the main points you mentioned is AI implementation at client side does lead to increased data consumption for Verisk. My other question on this is just in general, when you look at insurance carriers, what kind of AI investment strategy do they have? Like are they mostly focused on top line opportunities, cost-saving opportunities? Or what are you seeing across the board?

From our experience, they are overwhelmingly focused on efficiency and cost savings opportunities. I think that's the first priority. I think the second priority is portfolio optimization and risk selection applications, although I think that is a step behind or a next cycle element. And the third is customer interaction. And how do they -- certainly, the use of AI to facilitate more efficient customer interactions. But when you look at the use cases, that our clients are most interested in. It's how do I improve the speed and the productivity of our underwriting teams or our claims teams, first and foremost, and then kind of more interest in how do we use this technology to evaluate our overall risk portfolio preferences and management.

Got it. And when you think through that 5% to 10% productivity uplift whether in claims or underwriting, I guess, my thinking on this is like what are the regulators saying about the usage of AI in underwriting or claims processing, and how do you see the regulatory landscape will change in the next 5 years?

Yes. You're absolutely right. And I think it's important to say at the outset on the -- on any of the use of AI, the insurance industry is highly regulated. It's regulated in a very fragmented fashion on a state-by-state basis. So it's going to be complex. It's going to evolve. I can tell you from first-hand experience and talking to a number of state insurance commissioners who are our clients and that we work with and engagement that we've had with the NAIC. They're very much aware of concerned about AI. And I think while there is an orientation to find ways for the technology to provide value, they are certainly going to be focused primarily on protecting the consumer.

And I think in some ways, the technology may be helpful in that regard in standardizing treatment from both an underwriting and from a claims standpoint. One challenge that the regulators have or are focused on is the fact that generative AI, by its nature, as kind of a predictive tool that is trained -- a model is trained to predict the next token in a response to a query is not -- it's not predictable, it's not auditable, you don't know what goes into that. And so in that context, I think the regulators are always going to be opposed to taking the human out of the loop because you don't know -- you're not going to have consistency and you're not going to know how that decision was based, and it's a fundamental regulatory principle, there has to be a justification for pricing or how a claim is handled.

I won't go into great detail, but it's been interesting to us that the regulators have been focused on a form of AI known as neurosymbolic, which is a more determinative AI application that limits or puts a constraint based upon domain knowledge to make certain that it is a more -- it's a more transparent and predictable and consistent outcome. We're actually working with a client who is deploying neurosymbolic AI, and utilizing our data sets to pursue that. And it's something that we are having conversations with regulators to pursue. So that's the -- I think what we're experiencing from a regulatory environment. They realize that it will be an element, but they're going to want to make certain that it's predictable and transparent.

Got it. And just to clarify, is AI allowed to be used as part of underwriting decisions today? Or is It not?

Well, it is allowed to be utilized to support decisions, but ultimately, the individual or the company is going to be responsible for whatever is submitted from a regulatory standpoint.

Got it. Very helpful. The other question I want to get your thoughts on is really this build versus buy question that I think all the carriers are trying to think through. So maybe there's a difference in terms of larger and more sophisticated customers who have more resources, how they're thinking about building new AI solution versus small to medium-sized carriers. Now I was wondering from your dialogues with clients. Are they mostly looking at internally developed solutions? Are they looking to partner with Verisk? Are they looking at AI start-ups? Or do they even have any appetite to work with start-ups? Or what are you seeing in terms of the build versus buy?

So it really varies dramatically. We have the benefit of being able to see across a wide range of scale of players, some of the largest insurance companies, those whose brands are well known to smaller regional players. At the high end, I think there is a sense of responsibility to have ownership of the technology to explore it and determine how they can apply it with their data sets, but in almost all of those cases, the clients in that category have wanted a specific dialogue and conversation with us to talk about how we can integrate our data sets into their strategy. What are we doing that they might learn from or leverage. And there are, in many cases, where elements of -- how we're applying AI that they feel they can leverage that, for instance, taking our ratings and building an agent that rates a policy for them to evaluate rather than them investing in an independent ratings element or a ratings agent associated with that. But they clearly want to drive that deployment of technology and evaluating it.

We also have some clients that have asked us to work with them in developing a technology platform. We spoke on our call about a very well-recognized and respected insurance company that has asked us to build an agentic underwriting platform based upon our knowledge of the data sets, the regulatory needs and the technological dimension. So we're excited about that dimension. I mentioned the neurosymbolic client that we're partnering with. But I think there is also a wide range of clients that realize that they may not have the resources or the expertise to develop their own customized installation. And in that case, some of the products that we've developed like our underwriting assistant or in some of our claims areas, our AI solutions for exact where that enable or apply an AI technology may be more than sufficient to meet their needs.

So I think we're trying to meet our clients where they are at all levels of sophistication, and we have the flexibility to be able to do it. We also -- I think it's probably not recognized, we have an intense level of engagement with our clients at the functional level. And so we are truly a partner in understanding what they want to accomplish with their data strategy and their technology strategy, and it's a very regular part of our dialogue to understand what they're doing and what they're considering.

You also asked Kelsey about their inclination to work with AI start-up. And I -- our experience has been -- they're often interested in what may be accomplished at some of those levels, but there is a general reluctance to scale off of a small emerging company because of the uncertainty around where that company is going to end up or what they're going to do. And I think that's been a challenge for a lot of the startups. We have found in instances where if there's a good technology that's been proven, we often have the ability to monetize that if it's an acquisition to accelerate that and to build on our strengths. But in a lot of cases, it's very difficult for them to achieve the scale necessary to convince a large insurance company to adopt them.

Makes sense. And where are all of these AI start-ups concentrated? Are they mostly focused on collecting incremental data points? Or are they focused on model development? Or how are you thinking about the landscape?

Yes. So what we have seen, we've seen a real concentration in workflow functionality, which is interesting because those applications still require a lot of data. And so they're going to often draw data sets that our clients have or that we can provide to automate a component of the functionality in an underwriting process. It may be data ingestion, but I think in many cases, it's an integration of data and a reasoning function that produces an outcome that then would be reviewed by a human underwriter or a human claims professional to evaluate. So I think a lot of micro functions that might be built into as components of an overall agentic strategy. That's been the primary focus that we have seen.

Got it. So it's more like the layered analytics layer above Verisk data for insurance carriers data?

Yes. Absolutely. I'm focusing on claims functions, underwriting functions, risk assessment functions.

Got it. And how about you Lee, how are you thinking about the build versus buy conversation for Verisk?

So when we look at the components, certainly, we've made the decision we're not going to build a large language model. An we don't think that it's necessary for us to provide that. There are plenty of good models. In fact, we have worked with almost all of the models, in some cases, using a combination of them in some of our applications. I think what we are dedicating time to is working with individual clients that have a clear use case that they want to pursue, where they feel we can support or develop that for them. And then if we prove the functionality of that, then it gives us the ability to roll that out to the industry as a whole. So I would probably describe it as our focus is around applied technology as opposed to technology and integrating our data sets with that applied technology approach to meet our clients and then work to scale that across the industry.

Got it. Very clear. So something I've been thinking about is Verisk has actually started talking about deploying AI in different models and analytics from 10 years ago. So over the last 10 years, I guess, what are some of the key initiatives that you are most excited about, looking for in the future? What kind of AI investment strategy would you describe that Verisk has, and how should we think about the top line and margin opportunities from AI?

Yes. So I think there are a couple of levels to where I get excited about the opportunity. The first is that basic level that I think as clients are using more AI, the demand for data will increase, I think the value of the data improves. And so I think it is the distribution model where we benefit from that. The second element is kind of more specific to the industry is how do we improve the overall productivity in the underwriting function or the claims function. And this is where concept that Anthropic has talked about, which is the diffusion of the technology into the enterprise is a limiting factor, the rate of which is a limiting factor.

And I think we'll see a slow absorption of the technology that will produce improving productivity over time, but which will have a significant benefit to the industry in terms of that efficiency of the underwriting, the accuracy of the underwriting, the ability to assess risks more effectively and to manage claims. And that from a scale level, while I think an intermediate-term opportunity, I think, is the largest -- the largest foreseeable commercial opportunity for us to pursue. We've shown in a variety of instances where we can help deliver value to the industry, we have an opportunity to participate in that value. And because of our scale and utility model, our ability to make that investment and then deliver to the industry tends to enable us to produce very high value to cost equations, which encourages it.

So that's level 2 that longer-term -- the intermediate-term opportunity to improve process. And I think the third intermediate longer-term opportunity is the ability for AI to integrate data sets across disciplines and find connections or new products that are going to be additive to what we do already. So this isn't just improving an existing underwriting process or a claims process. But improving the overall -- the overall economic enterprise of insurance.

And one use case that I would point to is the ability to connect the life insurance life cycle and manage risk more actively. Certainly, insurance is a marketplace for risk and pricing risk. We have seen led by the reinsurers a more active engagement in managing that risk actively either in selling reinsurance contracts or laying it off in the insurance-linked marketplace. And we think that as the ability to manage real-time exposure data, underwriting information and claims information, we're going to have the ability to help the carriers really benefit that Chief Risk Officer or Chief Portfolio Manager within an insurance context to manage that risk more actively. In many ways, we're setting up synergy studio to be that platform to serve that chief risk officer or risk portfolio officer. And that's kind of an incremental opportunity that we think the industry will benefit from.

We'll come back to Synergy Studio in a second. But 2 quick follow-up questions to that. First one being, have you thought about sizing the incremental revenue or margin opportunity in the medium term? And secondly, you mentioned this distribution of AI technology within each vertical. Could you just elaborate a little bit more about that? Is that just like getting all of your employees familiar with using AI? Or what has got?

Yes. So it is actually, again, 2 that. I think the question that you're asking is, when I refer to the diffusion of the technology, it means the adoption and the integration of that AI technology across the enterprise in terms of the number of employees that are utilizing it. And I think we're at a very early stage in a very limited stage simply having a cloud license, you can certainly experiment with the model. But until you tie it to a function and a workflow in the data set, the value creation is probably more limited, but that demonstrates it. And I think different industries will have different diffusion rates into that. I think insurance will probably take a little bit longer because of the regulatory process because I think natural caution around new technologies.

But that diffusion rate, I think, is going to make this a longer adoption rate to scale of the technology within the industry. We saw it in cloud computing. Initially, insurers were very cautious about the movement of their data from mainframes into the cloud. But once some pioneers had demonstrated, we were one of the first to move a lot of -- all of our data sets into the cloud. And when the efficiencies and the benefits of associating that data became clear, I think the industry followed us and really realize the benefits of it. I think we'll see something similar in AI.

Got it. So Lee, when you look at Verisk portfolio across different segments and with AI, there will be new competitors or new solutions in the marketplace. Which product category do you feel that Verisk has the most -- the best defensible competitive mode over the long term versus having more room for improvements?

Sure. So we understand that's a question that's on investors' minds for a lot of companies. I think from our perspective, as we talked about at Investor Day, we believe that 90% of our revenues are tied to proprietary data sets, contributory data sets, proprietary intellectual property such as our catastrophe models. And we feel very comfortable that those data sets not only are defensible, but they're critical in the realization of value from the application of AI technology, which requires good data sets specific to an industry functionality to do that. We are mindful that there's a lot of concern about the exposure of some software businesses, particularly horizontal software businesses to the ability to code more quickly or to develop internal applications.

We do have some independent software businesses, but we believe they're very vertically anchored. They're tied to proprietary data sets in many instances. And so we think are defensible on that basis. We've also deployed lighter architecture to them. We're using low code, no code, which is more conducive to flexible data applications. So we're watching our exposure within those businesses. But to date, we haven't experience any loss of clients in any of our software businesses and we believe that, that's -- we're still in a competitive position, but that's one area that we watch.

Got it. I guess in my discussion with investors, for loss costs, anti-fraud, property estimating solutions and catastrophe risk models are probably the most defensible segments of Verisk, but there is one segment that I do want to dig a little bit deeper into, which is underwriting data analytics. Maybe just talk us through and remind us why Verisk competitive moat is really strong in that segment.

Yes. So in our underwriting data and analytics solutions business, we have a business called ProMetrix, which collects commercial building. So in this building, this hotel, we have a very insurance-driven data set that focuses on the engineering, fire suppression systems, the ground floor use of the business, the general application of the business, everything that a carrier is going to want to know about ensuring this property or general liability associated with businesses in this business.

Now that data set is gathered through a field force of individuals that survey the property, gather know what information to gather, and we have expanded the data sets that are relevant and included in that database. This information isn't publicly available. It's acquired by insurers. We're again acting on behalf of insurers. So we have the efficiency to gather this data once on this building. And that way, any insurer that wants to have access to it can do it more efficiently than sending their own team to do diligence the building. So we believe that that's unique proprietary data that we're able to build.

We also have in underwriting data and analytics solutions our 360Value, which is a replacement cost analysis. So for an underwriting function, what would it cost to rebuild this building. That is built upon proprietary information and intellectual property on materials costs, labor costs and what's required to rebuild that business. And it's used as an industry standard for underwriting purposes within the industry. And then we also have contributory data on a auto-related information driver history, policy information. That's a business where we have faced competition as we've spoken to in our calls from another player in the industry. it's one of the businesses where we don't have as strong a competitive advantage, but we provide an alternative to the industry as a whole.

So I think in the first 2, we believe we still have a very strong proprietary dimension of the data set. And then the third one, we are -- we have been working to build competitive advantage part of what we are doing is trying to leverage some of the data sets that we have in other personal lines businesses to provide more insight around the underwriting -- the auto underwriting function.

Got it. That's super helpful. I guess the other question on investors' mind is really just ferrous pricing power in the medium term as carriers kind of rethink about their allocation for data and analytics budget. A percentage of that probably goes to newer AI-powered solutions. So just help us think through various pricing power over the next few years?

Yes. So we tend to think about our pricing as being value driven. And so we want to make certain that given our relationship with the industry, that we are delivering incremental value to our clients relative to what their pricing increases are. And I think it's great evidence of that, we have, as we talked about in our first quarter call, the fact that we have seen a very consistent trend of renewal of our multiyear contracts at the same or longer terms, than had existed before as well as with attractive pricing improvements that recognize the value we've created from investments that we've made in access and usability of the data sets, the frequency of our updates, which our clients have asked for as well as increased insights that we're able to provide our clients on a product line and a state-by-state basis.

So that's our starting point from a value perspective. The second point I'd make is that, we don't think that AI and data are mutually exclusive expenses. And in fact, in order to generate value out of we believe that our data sets are going to be required to make the AI investment effective. And so I think rather than one displacing, I am very much of the view that AI is actually going to expand the value that our data can provide and expand the utilization of those data sets, both from a quantity of data as well as a leader that we are providing. So I think that's where we see the opportunity.

And then finally, it's that quantum of what do we think can be achievable when you combine AI with high-quality data and integration into workflows. And that's where I think when we look at the breadth of what we've experienced on a micro level, on a function-by-function basis with the anthropic application, we believe that our opportunity is to deliver that value to the industry, and to participate in sharing in a portion of that value that we're creating. And we think that could be a meaningful new growth opportunity for us.

Got it. The other hot topic in the insurance industry is really the transitioning from hard to soft markets. From -- I guess, from your seat, are you seeing anything that's fundamentally different about this cycle versus historical cycles? And how is that impacting Verisk?

Yes. I don't think that we're seeing anything. It's -- I think we're still early in this cycle, but I don't think that we're seeing anything in terms of severity or breadth. This is, I think, a natural cycle where we had a strong hard market that was fueled in some part by inflationary dimensions, some catastrophic losses. We've had a very mild weather impact, no hurricane that made landfall last year. And so that tends to have a softening effect on the overall market. But all of this is very consistent with what we have seen in the past.

We've talked about historically that when we've looked at the variation between hard markets and soft markets, we've seen our organic revenue growth vary between 7.2% in hard markets -- or 7.3% in hard markets, 6.8% in soft markets, it still rounds to 7%, and we think it doesn't capture the fact that what drives our growth is the increasing adoption of our data and technology in the insurance space.

Got it. So coming back to Verisk Synergy Studio. I think you're launching this new product next month. Maybe just talk us through the pricing strategy, target audience, how is this new product different from legacy models and things like that.

Yes. So the intention with Synergy Studio is to move what had formerly been a client hosted or a Verisk hosted modeling environment into a cloud-based SaaS solution that enabled us to deliver our models much more quickly and update them. So again, we're addressing the currency of the tools that we're providing to the insurance industry to apply all of our cat models to a consistent economic model.

And this is where I want to explain, catastrophe modeling is not weather prediction. It is taking a view of weather variability and applying them to physical structures and insured assets and estimating what the potential loss is going to be. And so our ability now on a SaaS-based platform to integrate or to tie together a massive amount of exposure accumulation and subject them to a wide range of natural catastrophe risks so that our carriers can have a more accurate outcome, a faster outcome, the ability to apply more robust stress testing against that and get more current and updated models is the value proposition.

We've also opened up our model -- our ecosystem to invite other models to participate so that our carriers can utilize a range of models in areas where we may not be offering a model. So it is, I think, a more technologically robust product set. It expands the functionality of what we are doing, and it opens up that ecosystem, we believe delivering more substantial value.

And I guess the other exciting transformation initiative at Verisk is really the Core Lines Reimagine program. So maybe tell us more about where we are in the Core Lines Reimagine program? And are you seeing this program that's actually delivering tangible benefit in terms of pricing or customer retention and so on and so forth.

Sure. So I think we are -- we have accomplished everything that we set out to. I certainly think there will be an ongoing effort to take client input and integrate that into what we're offering and to enhance that. But in terms of digitizing much of the data that we provide, the ability to interact with our forms, gather data through APIs, that infrastructure has been established. We'll look to continue to enhance and refine that. But the feedback from clients is even stronger than we'd hoped for. That's translated into consistently stronger renewal experiences and more engagement from our clients and our ability to help them utilize and get more value out of the data.

And I would say what I'm excited about is that now having that infrastructure a lot of which is API-driven, its readiness for AI and the ability to apply generative AI large language models to those data sets through MCPs for which the 2 initial anthropic connectors are just to start in terms of what we can do. And we are just pricing that on a free for a trial basis. But I think our view is that there's going to be real value that we'll be able to price to over time. Now that has created a great foundation for us then to demonstrate value from AI investments with our client -- with our client base.

Got it. I guess, switching gears a little bit. Verisk is obviously a very important data and analytics provider in the P&C insurance industry. But are you looking outside of P&C insurance industry for some of the future growth initiatives that you're thinking about, whether this is international markets, the life insurance vertical or anything else that you're excited about?

Yes. So I'd say all of the above, Kelsey. Certainly, there's a lot to do in P&C. And I'll give as one example, which we've been thrilled at the results from is a lot of our loss cost data came from what's known as the admitted market, which is the regulated market where you have to go to state regulators. But there is -- it's also known as the excess and surplus market. And we've had clients come and say we'd like to have more data sets from you, and we're -- we would like to contribute data sets so that we can evaluate our excess and surplus writing, which has been growing at a faster rate than the admitted market.

And so we've been thrilled to be able to get more data contribution on that front. So that's an example of just within the P&C marketplace where we're doing more. We also have been doing a lot in the specialty insurance market, the Lloyd's market in London, and have developed a transactional platform called white space that has received high adoption for facilitating greater efficiency of broker submissions and underwriting by underwriters within the London market. That's an example of both P&C expansion, but also in international market development.

And as we talked about at Investor Day, we have demand to roll that out in the Middle East and in Asia, and specifically the Singapore market, which we think will be a natural expansion. And we also see the opportunity to bring a lot of the technology that we've deployed within the U.S. and find solutions within Europe with an European content. And then finally, we've had great success in the life business with our fast element. We've added a regulatory component to that with the acquisition of SuranceBay. And we've also had clients interested in how we might deploy AI against the data sets that we're collecting in the life side as well. So I think we feel very comfortable with multiple vectors from off of our very strong base in U.S. P&C.

Speaking of the SuranceBay acquisition and the FAST acquisition, maybe talk us through a little bit more about what your product road map may look like in the life insurance vertical in the next 5 to 10 years?

Sure. So starting with FAST. FAST is a policy administration platform that has replaced a lot of legacy systems and has enabled our clients to dramatically accelerate their product development functionality both traditional players and life and annuity -- a private equity life and annuity acquirers that want to have a system that is more responsive, much less expensive to maintain. So that's the starting point. And then from that platform, SuranceBay is a natural regulatory function to make certain that, that brokers are meeting regulatory requirements and how they are describing the policies and the language and getting through all the necessary disclosures.

And what we have heard from our clients that have been really happy with that -- those implementations is how do we integrate more life cycle analytics to help them evaluate the maintenance and the renewal cycles for their life products. So I think the life insurance industry has been more actively engaged in thinking about data and analytics whereas before, they were probably more focused on basic mortality tables and kind of annuity calculations, and we're seeing a much more sophisticated demand for data and analytics to help them better manage those long-term relationships that they have.

Got it. Kind of switching gears to a more near-term question. So for FY '26, obviously, in the half of the year, you've had a number of short-term or near-term headwinds. You're guiding for a second half re-acceleration of growth. Maybe talk us through what are some of the key drivers of that second half acceleration? And how are you thinking about the full year guidance of 7% type organic revenue growth and the puts and takes to that guidance?

Yes. So I think it's important to understand that the -- while we talk about a -- you describe it as a re-acceleration. Our underlying business as evidenced by kind of the strong subscription growth has maintained a very steady and strong growth rate. We had the impact of some weaker weather -- low weather activity, we had a government contract, which was impacted by some policy changes within the organization. And we had some other headwinds that in the second half of 2025, we had to work through. As we've described, those are migrating out of the system. We believe we had the trough in the first quarter. We're expecting continued momentum into the second quarter. And then the third and the fourth quarter, based upon the guidance that we have described, should show a recovery to our 2026 overall growth rate.

But to us, it's less re-acceleration. Well, that's what's happening on a net basis to me, it's more of a natural revelation of the underlying growth the business as a whole as a couple of those exogenous pressures that we had in 2025 work their way through.

Got it. We have 2 minutes left. Maybe 1 last question from me today. How are you thinking about your capital allocation priorities, especially in the current environment where your own AI initiatives probably brings so many new investment opportunities and you're probably thinking through organic investment, inorganic investment. So how do you think about prioritizing your strategic M&As, your buybacks, your debt prepayments, your dividends and so on and so forth. And specifically for strategic M&As, what kind of new data assets or models or analytics solutions are you looking to acquire?

Sure. So our first priority by far is where we can invest organically in integrating AI for our customers into our data sets, creating value in that broad underwriting or claims function. And I think we're anticipating more intensive investment given the rate of change. You've seen our level of engagement, as I've described, both with anthropic, our dialogue with other frontier model companies, our exploration of the opportunities in neurosymbolic, project on the agentic AI element. So all of those are top priorities to determine where our greatest monetization opportunity is for AI in association with our data.

I think secondly, continued investment in maintaining the strength of our data sets. So investing in data, improving its currency, its relevance, quality, expanding new data sets like our excess and surplus data elements would be a second internal priority. A third priority is how do we strengthen the ecosystem and the network dimension of what we are doing to create more efficiency and data sharing across claims ecosystems, fraud ecosystems, underwriting and catastrophe and risk modeling. So there's a lot to do within each of those areas to strengthen our existing business and develop new growth opportunities in AI.

Fortunately, we generate a lot of capital. And so we have plenty to fund that, but I think we might see a marginal shift in that internal investment consistent with our overall guidance. So nothing that changes on that front, but I think we want to take advantage of this opportunity that we've seen. And then secondly, we will look for value-creating opportunities where we believe that there's a business that is delivering value for the industry, but we can rapidly scale it or enhance its effectiveness with our data set. That will be a second priority if the return characteristics are attractive to us.

And then finally, naturally, given the pressure that the overall sector has experienced, we have been more aggressive as investors have seen in terms of taking advantage of that from a share repurchase standpoint. And where we don't see opportunities to invest in good returns, we have a natural inclination to return that through both increasing the dividend and repurchasing shares.

Got it. This is all super insightful and helpful. Thank you so much for sharing with us today. Really appreciate this, Lee.

Thank you, Kelsey. It's great to be here. Thanks for the great questions.

Thanks, everyone, for joining us.

Good day, everyone, and welcome to Verisk's First Quarter 2026 Earnings Results Conference Call. This call is being recorded. [Operator Instructions]

For opening remarks and introductions, I would like to turn the call over to Verisk's Senior Vice President of Finance and Investor Relations, Ms. Stacey Brodbar. Ms. Brodbar, please go ahead.

Thank you, operator, and good day, everyone. We appreciate you joining us today for a discussion of our first quarter 2026 financial results. On the call today are Lee Shavel, Verisk's President and Chief Executive Officer; and Elizabeth Mann, Chief Financial Officer. The earnings release referenced on this call as well, as our traditional quarterly earnings presentation and the associated 10-Q can be found in the Investors section of our website, verisk.com. The earnings release has also been attached to an 8-K that we have furnished to the SEC. A replay of this call will be available for 30 days on our website and by dial-in.

As set forth in more detail in today's earnings release, I will remind everyone that today's call may include forward-looking statements about Verisk's future performance, including those related to our financial guidance. Actual performance could differ materially from what is suggested by our comments today. Information about the factors that could affect future performance is contained in our recent SEC filings. A reconciliation of reported and historic non-GAAP financial measures discussed on the call is provided in our 8-K and today's earnings presentation posted on the Investors section of our website, verisk.com.

However, we are not able to provide a reconciliation of projected adjusted EBITDA, adjusted EBITDA margin and adjusted EPS to the most directly comparable expected GAAP results because of the unreasonable effort and high unpredictability of estimating certain items that are excluded from projected non-GAAP adjusted EBITDA, adjusted EBITDA margin and adjusted EPS, including, for example, tax consequences, acquisition-related costs, gains and losses from dispositions and other nonrecurring expenses, the effect of which may be significant.

And now I'd like to turn the call over to Lee Shavel.

Thanks, Stacey. Good morning, everyone, and thank you for joining us. Today, I will provide a broad overview of our first quarter financial results, and then Elizabeth will go into more detail in her financial review. I will give some details on our innovation activity, including some recent AI developments. And finally, I will wrap up with highlights from our client engagement during the quarter.

Turning to the results. Verisk delivered organic constant currency revenue growth of 4.7% with growth across both underwriting and claims and sustained strong growth of 7% in subscription revenues. Our focus on efficiency and cost discipline drove organic constant currency adjusted EBITDA growth of 5.9%, delivering 60 basis points of margin expansion. This growth was modestly ahead of our expectations and included the impact of the factors we previously communicated, namely the carryover impact of the very low weather activity, tougher compares from strong renewals last year and a work stoppage in a federal government contract.

So while this quarter's performance is modestly below our typical growth levels, we have confidence that the resolution of these short-term factors and continued core growth momentum will result in a gradual improvement in revenue growth as we move through the year. Moreover, we expect 2026 to be another year of performance in line with our long-term growth targets.

Last month, we hosted an Investor Day where we outlined our strategy to drive compounding growth by focusing on 4 key initiatives, specifically, strengthening strategic client relationships, expanding our proprietary and contributory data advantage, delivering a steady stream of innovations to the market, and expanding networks across our businesses. We also reiterated our growth targets for the next 3 years and provided detailed overviews for each of our key divisions. We truly appreciate that so many of you attended in person, or watched the live webcast, and would encourage others to look at the materials, which are available on the Investors section of our website.

One hallmark of Verisk's business model is that we have delivered consistent growth across varying macroeconomic, geopolitical and insurance-specific operating environments. This is due to the mission-critical nature of our solutions, our scale-driven economic advantage and our diversified set of offerings across underwriting and claims and personal and commercial lines. Today, the insurance industry backdrop in which we are operating is healthy, yet evolving.

2025 marked one of the strongest underwriting results in years with robust industry profitability and near record low combined ratios, helped by unusually low catastrophe losses. With ample capital, carriers are shifting their focus from profitability to growth, resulting in more competition and softening pricing. This dynamic is most pronounced across the property lines, specifically commercial property. On one hand, this drives carriers to be more focused on cost efficiency. However, it is precisely in these types of markets that underwriting discipline and enhanced risk selection is a key focus for our clients, contributing to the need to be informed by the most complete and comprehensive data and analytics available. To that end, our level of engagement remains high, as our clients are turning to Verisk as a trusted partner in that pursuit.

At Verisk, we are focused on supporting our clients with the most advanced data analytics and insights, and investing at scale in new technologies to help them better understand risk and navigate through these dynamic times. We are not only introducing new innovations to the market at a faster rate. But these solutions are more impactful as they address some of the industry's most pressing challenges with more timely and more frequent insights, and more efficiency and automation.

As an example, within our underwriting data and analytics solutions business, we continue to enhance and strengthen our leading property solutions through our innovations using aerial imagery. By integrating this advanced technology we have innovated with more accurate property level insights at scale, namely our roof age and aerial imagery analytics solutions that address long-standing challenges for the industry. We have invested behind continuous data refreshment and have expanded our analytical capabilities, resulting in a product that offers better risk selection and faster underwriting.

Client adoption has been strong with our enhanced aerial imagery offerings, growing revenue more than 30% over the last 2 years. We have additional innovations, which are slated for introduction this year, including wind and hail peril scores and remaining [indiscernible]. And within our anti-fraud business, our digital media forensics is an AI-powered solution that automates anomaly detection in photos and documents, a growing source of fraud risk for the industry. This innovation reinforces our position as a key partner in fraud analytics, and highlights our scale and ability to organically build new contributory data sets, to help the industry address a growing challenge.

Through innovation, we are driving growth in a heavily penetrated business. And in fact, just this quarter, we on-boarded the sixth top 10 carrier to the digital media forensics platform. The changes to our go-to-market strategy, first implemented in 2024 and continued throughout 2025, and have enabled us to get ever closer to our clients, understanding their specific needs and delivering better service with high levels of client satisfaction. We are continuing to improve our client engagement with the addition of new sales leadership in our Claims business, added sales resources across the business and the expansion of our client strategy group, which focuses on our largest clients.

We recently hosted two key client events, the Insurance Fraud Management Conference, or IFM, our signature anti-fraud event and the Verisk Insurance Conference, or VIC, as it is known throughout the industry. VIC is our flagship event, where we strategically engage various market participants to learn, network and explore the latest industry trends, innovations and Verisk solutions, that address the most top-of-mind industry dynamics. In fact, this year, 75% of respondents viewed VIC as a must-attend industry event. Both events attracted a record number of attendees from across the global insurance ecosystem, including presentative from the carriers, brokers, reinsurers, regulators and our channel partners.

AI featured prominently across the education program with 23 sessions covering AI-driven product innovation and the role of AI across underwriting, catastrophe modeling life and annuities, specialty lines and core platforms. These sessions were the most attended, including hundreds of clients representing a wide range of scale from large global multiline carriers to regional and small carriers. In the [ solutions gallery ], the AI showcase focused on 5 workflow-based AI demos, reflecting how we're scaling practical AI in our underwriting, catastrophe and risk and specialty business areas. Demonstrations focused on showcasing solutions that embed AI directly into workflows, augment human decision-making, improve the usability complex data and reinforce Verisk's commitment to responsible regulator ready AI.

I'd note in an [ A.M. Best ] report on AI and insurance released this week surveyed insurers identified data readiness as the top impediment to AI implementation even ahead of security and privacy. Companies are keenly focused on how they can partner with Verisk and capitalize on our robust and proprietary data sets through this significant technology transformation. I was particularly impressed with the engagement with our largest clients as they develop their AI strategies. In several instances, clients have included us in their own internal discussions to explore how we can integrate our data and capabilities into their AI strategies as a co-development partner. There has been a recurring theme that while AI can be powerful, it requires both deep industry knowledge and relevant data sets to be most effectively applied.

Coming out of both events client interest and sales pipelines are robust and competitive win rates have been very strong. Additionally, we are experiencing a faster pace of trial and growing number of proof of concepts for our AI solutions. In fact, we already have over 20 follow-up meetings set up related to augmented underwriting. That said, in certain cases, we are seeing an extended sales cycle related to the more complex contracting to incorporate AI governance and compliance. We are also engaging with many of our large clients regulators and the frontier model companies on partnership opportunities to leverage our data and insights.

A key focus for all parties is accountability, transparency, governance and protection of intellectual property. Based on our interactions with several frontier model companies, it is clear that they recognize the importance of leveraging not just proprietary data sets, but also deep industry-specific knowledge and established workflows, all of which [indiscernible] Verisk. For these reasons, as well as our focus on accountability, compliance and governance, Verisk was the winner of a competitive RFP process to be the strategic partner of a global insurance firm to support the creation of a next-generation digitally native underwriting entity.

Verisk will contribute its established data, actuarial and analytics capabilities alongside a growing suite of AI-driven platforms and marketplace solutions to codevelop the operating model. This opportunity reflects continued momentum in commercializing Verisk's multiyear investments in agentic technologies, and expanded role in enabling innovation across the insurance value chain.

And with that, let me turn the call over to Elizabeth for the detailed financial review.

Thanks, Lee, and good day to everyone on the call. On a consolidated and GAAP basis, first quarter revenue was [ $783 million ], up 4% versus the prior year. Net income was $234 million, a 1% increase versus the prior year, while diluted GAAP earnings per share were $1.73, up 5% versus the prior year. The increase in net income and diluted GAAP EPS reflects solid operational performance and a lower average share count, offset in part by higher interest expense and a higher effective tax rate.

Moving to our organic constant currency results adjusted for nonoperating items, as defined in the non-GAAP financial measures section of our press release, our operating results demonstrate continued growth across both underwriting and claims. In the first quarter, OCC revenues grew 4.7%, with growth of 5.3% in underwriting and 3.4% in claims. This quarter's performance, while below our typical level, was ahead of our expectations as we continue to drive growth despite the shorter-term headwinds that we have previously communicated, namely the carryover effect of a lower level of weather-related events, tough comparisons from strong renewals last year and the work stoppage in a federal government contract. The durability of our subscription revenues is the best demonstration of the ongoing health of our business and the mission-critical nature of our solutions.

In the first quarter 2026, subscription revenues, which comprised 84% of our total revenues in the quarter, grew 7% on an OCC basis, compounding on top of a 10.6% organic constant currency increase from the first quarter of the prior year. These growth levels reflect the lower weather events as well as the negative impact of the work stoppage in the government contract. But otherwise, this quarter's subscription growth was broad-based, with out-performance from our largest subscription-based solutions.

In [indiscernible] loss costs, we are driving strong price realization in renewals, as we continue to demonstrate to our clients the enhanced value created through our reimagined initiative. In the first quarter, we released 7 new client-facing modules and we anticipate a total of 25 releases for 2026, as we continue to innovate and enhance our core offering. We are also continuing to onboard new data contributors, both in core lines where we added 4 new carriers, as well as in our new excess and surplus lines contributory data program, where we now have contributions representing more than $15 billion in premium.

Within catastrophe and risk solutions, we delivered another quarter of double-digit growth driven by the expansion of contracts with existing clients, competitive wins and the addition of new logos, including many clients that are new to catastrophe modeling. Specifically, we had key multiyear contract expansions in the quarter with 2 top carriers, as well as new wins in the casualty modeling space, where we are the provider of the industry's first probabilistic casualty catastrophe model.

Client interest in Verisk Synergy Studio, our next-generation catastrophe risk platform is high as live previews have been well received. The release of our updated U.S. tropical cyclone model and the production release of Verisk Energy Studio remain on track, and clients are expanding their hosting relationships with Verisk in preparation for the launch of the platform.

In anti-fraud, we are driving strong value realization in renewals as a result of our enhanced data insights and expanded ecosystem strategy. Additionally, new inventions, including claims coverage identifier and digital media forensics, which Lee mentioned earlier, are seeing strong client adoption, and we have a deep pipeline of opportunities.

Within our [ Life ] business, we continue to deliver double-digit organic revenue growth driven by new client wins, as well as the expansion of relationships with existing clients. Recently, we closed our first combined Fast Insurance [ Bay ] deal with a major life and annuity carrier, demonstrating the synergistic value creation we can drive by combining these businesses. Our transactional revenues, which comprised 16% of total revenues in the quarter, declined 6.1% on an OEC basis. The primary driver of this decline continues to be lower volumes in property and restoration solutions due to low levels of weather activity. As a reminder, the first quarter of 2025 included a benefit from claims associated with Hurricane Helene and Milton. Additionally, softness in the personal lines auto business as well as a lower level of overage revenues in the property business also negatively impacted growth.

Moving to our adjusted EBITDA results. OCC adjusted EBITDA growth was 5.9% in the quarter, while total adjusted EBITDA margin, which includes both organic and inorganic results, were 55.9%, up 60 basis points from the prior year. This level of margin expansion reflects the operational leverage of our business model, and our ongoing commitment to cost discipline, including global talent optimization, offset in part by increased investment in AI and technology. As is typical, we expect our expenses to ramp as we move throughout the year.

Continuing down the income statement, net interest expense was $43 million, compared to $36 million in the prior year period, due to higher debt balances and higher interest rates. During the first quarter, we issued $1 billion of senior notes and entered into a $500 million term loan. We used these proceeds to fund the previously announced $1.5 billion accelerated share repurchase program. Of note, at the close of the quarter, we have $250 million outstanding on the term loan. Our current leverage stands at 2.4x debt to adjusted EBITDA, which is well within our targeted range of 2 to 3x.

As we look ahead, we anticipate the run rate of quarterly interest expense to be higher than the first quarter 2026, reflecting a full period impact of the new [ debt issue ]. Our reported effective tax rate was 24.1%, compared to 21.6% in the prior year quarter. The year-over-year increase was driven by lower tax benefits from a lower level of employee stock option exercise activity. We continue to expect our tax rate to be in the 23% to 26% range for the full year.

Adjusted net income increased 0.6% to $246 million, and diluted adjusted EPS increased 5.2% to $1.82 per share for the quarter. The increase was driven by solid revenue growth, strong margin expansion and a lower average share count. This was partially offset by higher interest expense and a higher tax rate. From a cash flow perspective, on a reported basis, net cash from operating activities decreased 12% to $390 million, while free cash flow decreased 17% to $326 million. The decrease in both cash flow measures was primarily driven by a tax refund collected in the prior year period that did not recur this year, as well as higher interest payments. If adjusted for last year's tax refund, both cash flow measures would have seen growth in the quarter.

We remain committed to returning capital to shareholders. During the first quarter, we paid a cash dividend of $0.50 per share, an 11% increase from the prior year, totaling $66 million. Additionally, we initiated a $1.5 billion accelerated share repurchase program, which is expected to run at least through the second quarter. We also repurchased $126 million of stock through an open market repurchase program. In total, we retired 7.6 million shares in the first quarter of '26. We currently have approximately $1 billion remaining under our share repurchase authorization.

Turning to guidance. We are reaffirming our outlook for 2026. More specifically, we continue to expect consolidated revenue in the range of $3.19 billion to $3.24 billion. Adjusted EBITDA is expected to be between $1.79 billion and $1.83 billion, with adjusted EBITDA margin of 56% to 56.5%. We continue to expect net interest expense of $190 million to $200 million, and our effective tax rate to be in the range of 23% to 26%. Taken together, this results in adjusted earnings per share for the year in the range of $7.45 to $7.75.

A few things to note as you update your models. First, as we said last quarter, we expect the first quarter of 2026 to be a trough, both in terms of organic constant currency revenue growth rate as absolute dollars, and forecast a gradual improvement as we move through the year. Second, we continue to face tougher comparisons in the first half of this year as last year benefited from a strong subscription renewal cycle across our largest underwriting businesses. Third, all guidance figures reflect the impact of the divestiture of Verisk Marketing Solutions, which contributed $68 million in revenue in 2025 with little seasonality, and represents an $0.11 headwind to earnings per share. Finally, Specific to the second quarter, we remind you that the prior year quarter's reported margins benefited from a foreign currency translation impact, which contributed 120 basis points to margin, and which we do not expect to recur. A complete listing of all guidance measures can be found in the earnings slide deck, which has been posted to the Investors section of our website, verisk.com.

And now let me turn the call back over to Lee for some closing remarks.

Thanks, Elizabeth. In summary, we delivered a solid start to 2026 with organic revenue growth, expanding margins and strong cash generation, despite several temporary headwinds. The resilience of our subscription-based model, combined with disciplined execution and continued investment in high-return initiatives positions us well for the remainder of the year. We are excited about the growth opportunities ahead and have confidence in delivering a year of growth in 2026 that is in line with our long-term growth targets and compounds the solid year in 2025. We continue to appreciate all the support and interest in Verisk. Given the large number of analysts we have covering us, we ask that you limit yourself to 1 question.

With that, I'll ask the operator to open the line for questions.

[Operator Instructions] Your first question comes from the line of Ashish Sabadra with RBC Capital Markets.

In the prepared remarks, there was a comment on strong pricing realization on renewals. I was wondering if you could unpack that further. Can you talk about how the [ AWPs ] are impacting pricing, but also how you're getting pricing on the non [indiscernible] contracts?

Sure, Ashish. So the way I would summarize that is both at our large client multiyear renewals, we have seen a consistent trend of our ability to achieve stronger price increases on an annualized basis for those multiyear contracts, as well as either similar terms or longer terms, reflecting the criticality of the data, the importance, particularly in this AI environment. And they have been averaging approximately between 4 and 5 years, which we think is a very strong indication of our role as a fundamental partner to what they're doing.

So the comment reflects that, as well as our ability on the annual increases to secure [indiscernible] increases reflective of the greater value that we're providing through our Core Lines Reimagine initiative. And that's generally been in true across both of those levels. So hopefully, that unpacks a little bit the strength that we're referring to in those comments.

Your next question comes from the line of Toni Kaplan with Morgan Stanley.

Lee, you talked in the prepared remarks about clients wanting to use your data and capabilities in their internal AI strategies, which makes a lot of sense given your proprietary data. I was hoping you could talk about how you see the monetization model for that type of situation. Could you be net neutral in selling your data versus selling a whole software solution?

And I guess, does selling just the data limit your ability to cross-sell if they're not using your interface? Or no because you'll still have salespeople trying to upsell those clients anyway, and so you're just as well off? I know you want to partner with these clients to try to maximize the value. So just wanted to understand the puts and takes of monetization of the different models and situations.

Toni, I think the monetization opportunity for us is going to be rooted in the fact that the application of AI [indiscernible] come from client developed solutions, frontier model companies, our integration of generative AI, or agentic AI, all driven off of that -- off of the data sets that we are providing on a structured, clean industry-wide basis.

I was very reassured to see in the [ A.M. Best ] report that I referred to that there was a consistent observation that data readiness [ and ] its ability to integrate with AI is one of the biggest challenges that the industry faces. And individual clients facing legacy system issues and utilizing that data, even within their own data, creates that natural partnership opportunity for us to deliver that data and connect it to this technology in a way that allows them to achieve more value because the data is more [indiscernible]. It's broader, it's an industry data that will enable us to give them more value for the data that we provide.

So I start with that foundation. We think that it will also encourage more use of our data within specific data sets but also across our related areas in underwriting claims in cat modeling and the models. So I think that will encourage more use. And then our monetization strategy, I think, will consist of both realizing more value through our pricing arrangements, as well as at the outset opening up new specific data utilization for AI applications that are specific purposes that we are adapting our data to that are driving value realization from our clients.

So I think in the near term, what we are seeing is our clients have moved on an experimentation in an exploration phase in 2025 to realizing that integrating these data sets into what they're doing and their functions is going to create value, but they need that greater data [indiscernible], better data quality and partnership between us their objectives and technology providers, both on the Frontier AI model companies, as well as in some cases, the infrastructure or policy administration system partners. And we are working with each of those entities. And I think that will create both near-term opportunities as we begin to implement that as well as longer-term opportunities from a pricing standpoint for the data. And I -- this is certainly going to evolve over time as the industry experiments and experiences what's possible here.

Your next question comes from the line of Jeff Mueler with Baird.

There was a comment, Lee from you in the prepared remarks about extended sales cycles for some AI solutions. I just want to make sure I'm understanding what you're trying to convey there correctly.

Are you trying to insert any incremental caution relative to your prior commentary on how revenue should develop for you over the balance of the year? Or is this just all about governance and compliance of AI solutions, in a -- of a disruptive tech and a risk-focused industry, or anything on if the competitive set is broader after you go after those opportunities or anything like that?

Yes. Jeff, what that reflects is, as we are pursuing these specific AI opportunities. And even the -- our existing contracts, AI is an element where both our clients and we need to be thoughtful about intellectual property, the issues related to that privacy issues associated with that. And so it has added an additional complexity in negotiating and adapting our contracts to those specific purposes. And so I think we have seen in these larger contract renewals, we're having to spend some more time working our way through these issues. I think that, that will improve over time for us as industry standards on dealing with these issues improve.

And I think that the other advantage that we have in that regard is that we are very used to dealing with issues on data governance, security, privacy issues, given the trusted role that we have with our clients' data. And I think we will be in a better position to resolve those issues because, in many ways, there are extensions of the trust [indiscernible] -- the data governance components that we have around it.

So what I am -- what we are signaling is this is an element that is taking a little longer to work through. It goes hand-in-hand with the new opportunity and with what we are seeing is a growing pipeline of opportunities, which is the case, it may take a little longer for us to work those through from a contractual standpoint as we feel this out. So yes, there is a little bit of caution, but it relates to, I think, this growing opportunity and what it represents for us longer term.

Your next question comes from the line of George Tong with Goldman Sachs.

You mentioned expectations of gradual improvement in organic revenue growth moving through the year. Can you provide some color on the cadence of improvement taking into account factors like weather, property underwriting overages and subscription renewal timing?

Yes, happy to. Look, we indicated that we expected 1Q to be the trough, and we continue to expect that with improvement from here. On a reported revenue standpoint, I think we can expect a steady build to the full year amount that we gave in our guidance range as the year progresses. Some of the headwinds that we talked about from a year-over-year perspective will persist into that second quarter. So you could still see from an OCC perspective, the second quarter falling below our long-term guidance range. That's just a function of the year-over-year impact still of the headwinds we talked about in the second half of 2035. The core of our business remains strong. And so as we move past that year-over-year impact, we expect the underlying strength and health of the business with the strength of our subscription revenues to [ reemerge ].

Your next call comes from David Motemaden with Evercore.

Elizabeth, I believe you had mentioned that you added 4 new carriers to the core lines contributory data set. I'm wondering, to the extent you can share were any of those among your top 10, or top 25 carrier relationships? And more broadly, as carriers deploy some of their own [ AI underwriting ] assistance [ in ] AI tools. Have conversations changed around the value of continuing to contribute to Verisk's -- contributory data ecosystem?

We continue to see strength on the engagement of the contribution from carriers, both large, small. But I'm going to ask my colleague, Saurabh Khemka to add color into that.

Yes, absolutely. As Elizabeth mentioned, we continue to see strong engagement with carriers both large and small on the value of contributing data to our industry data set. And -- we mentioned the [ E&S ] data is a great example where we have new contributions both from large and small carriers around a new data set because we were able to provide some benchmarks that they didn't have previously. So we continue to see that engagement the 4 carriers that we mentioned are part of that overall 100 new contributors that we mentioned as we launched Reimagine, and they're just kind of flowing through our systems now.

Your next question comes from the line of Andrew Nicholas with William Blair.

I wanted to go back to, kind of like, the channel conversation on the AI product front. It sounds like a lot of options here. You have, kind of, AI native products that you're building yourself. Maybe some co-development work and potential partnerships with the frontier model providers. I'm just curious, as you think about all those different paths, what is the -- is there a difference in monetization potential between them?

Is there any preference in terms of channel taking into account scalability, or pace of adoption, or how much investment is required to get that off the ground? Just trying to figure out, to the extent that one of those paths becomes a more common consumption of your assets, if that has any impact on the fundamentals?

Andrew, the -- I think the most important aspect from our perspective is making certain that we are responding to what our clients' preferences are and needs. And each client is going to be different. There are some of our clients that are actively engaged with some of the frontier models. There are others that have been exploring those partnerships and have come to us in that one instance that we referred, and selected us to be their partner in developing their underwriting agentic solution. There are clients at a very high scale level that are developing their own AI applications and working with us to integrate our data into it. We have smaller companies that have been very engaged in utilizing the AI solutions that we've implemented into our products.

So I think our primary focus is in making certain that we can be as responsive as possible to the variety of approaches and needs that our clients are taking. I think from a scalability standpoint, I think each -- we've been pleased so far that we've been able to adapt our data sets relatively easily into these AI applications. And one reason for that is that a lot of this investment has been made first in the natural standardization and of the migration of our data sets into the cloud, which has facilitated that access. We already provide standardization as a function of what we do. But [ thirdly ], our ability to adapt prior to this to more API-driven access to our data sets has facilitated our ability to tie that to MCP, or model context protocol applications, that have been the primary channel for agent applications and even [ more ] language models.

So we -- I would not say at this stage, that we see differentiation in the scalability of that opportunity. We do see a variety of applications that our clients, or channels that they're pursuing. And our data fortunately has the flexibility to be easily adapted and applied to a wide range. And I wouldn't say that we see a preference at this stage.

Your next question comes from the line of Manav Patnaik with Barclays.

Lee, you talked about, I think, what was noticeable to me [indiscernible] more impactful innovation at a faster rate. And I'm just curious like how much of that gets absorbed as part of your value pricing strategy that you have, as opposed to driving new incremental revenue could, I guess, at Investor Day, you reiterated your long term from the way you were describing this, it sounded like it could be incremental? So I'm just trying to parse that out, if that makes sense.

Yes. Manav, I would say that the balance -- the greater balance of that is applied to developing new revenue opportunities for us because those innovations are creating a distinctively incremental level of value that may not have occurred before. And when we were talking about, for instance, aerial imagery, those are new analytics that provide [indiscernible] or improved outcomes to our clients that they otherwise wouldn't have access to before. So if we think of it as something that is separate and additional to the loss cost data, or the [ prometrics ] data, or the 360 value data on restoration costs. These are new applications that provide incremental value.

Similarly, the digital media forensics is -- while providing an anti full solution, this is something that is being applied to those digital images. So it's a similar model, but it is something that is incremental to the overall purpose. So I would say the significant majority of that focus is in developing new sources of revenue rather than just enhancing the existing value of what we already have.

Your next question comes from the line of Jeff Silber with BMO Capital Markets.

You talked a bit earlier regarding a contract renewal and embedding the different aspects of AI into the negotiations. I'm just curious, I know from a market perspective, we've seen, I guess, what you called the past normalization of net written premium growth. But your clients are still under a lot of pressure focusing on profitability.

Are you seeing any changes either put back on price increases or lengthening of sales cycles because of that specific item? And how are you addressing that?

Jeff, I'd have to say we aren't seeing that. And that's not the primary driver. And in fact, notwithstanding the -- some of the net written premium softness, I do think that the profitability that we've seen in terms of significantly improved combined ratios for the industry is creating a level of profitability that, on the one hand, is -- creates, I think, an opportunity for them to invest a little bit more heavily in technology, coming at a time where there is more demand for data and analytics and AI to be applied to it. And I think generally, the market has been -- or our client set, the industry has been leaning into technology, naturally AI and with the recognition that clean, structured accessible data sets are going to be important to that.

I think that has been a dimension that has supported our contract negotiations and renewals with them. And the fact that we have our largest clients in a variety of recent renewals over the past -- over the past 12 months who have recommitted to long multiyear contracts, I think, is a demonstration of the importance of that data and its value even in this industry of technological change, and adaptation, as well as a softening premium market. These dynamics [indiscernible] adoption and the utilization of technology in many ways, supersede of the year-to-year fluctuations in the overall market.

Your next question comes from the line of Henry Hayden with Rothschild & Co Redburn.

We were hoping for an update on the cross-sell environment that you're seeing, specifically as it relates to how adoption of digital modules from existing solution upgrades is trending? Are you seeing an acceleration uptake as you sort of work through the client base? And what's the current state of penetration of that?

Yes. Thanks for the question, Henry. We are seeing a strong environment with a lot of interest and engagement in our new products. But we talked about the engagement that we saw from clients at VIC and the pretty active pipeline of trials, POCs, engagement and new subscriptions on the new products. So we continue to be happy about the cross-sell opportunity and [indiscernible] to provide that value to the clients.

And Henry, if I could add a dimension to that. I think there were two levels that this is operating for us. One is because of a better strategic dialogue that we've had with our clients that has improved, we have seen improved in individual product cross-sells as we're better able to speak to the strategic value, or the return on investment of our products at that strategic level. But the second dimension is that our clients have been more engaged in working with us to understand how we can integrate data sets and product functionality across that. And so building and working towards more enterprise-oriented solutions that tie our products together to meet some of their specific goals. I think we're excited about the opportunities of doing more of that across the industry.

Your next question comes from the line of Curtis Nagle with Bank of America.

Great. Just, maybe [indiscernible] one for me. Just in terms of the shape of the year-end growth. What is the expected contribution from the new [indiscernible] modules that you're continuing to feather in, versus, say, just the impact of some of the easier comps in the second half of the year?

Thanks. Yes, I think it depends on how you look at it. So from a year-over-year comparison, that will be driven -- the improvement over the balance of the year will be driven by the easier year-over-year comps. But as we said, we expect [indiscernible] in reported revenue. The forms rules [indiscernible] business as our largest business will be contributing to that. I think we mentioned it as a driver of subscription growth in this first quarter. So that will persist. But all of our businesses are showing a pretty strong subscription outcome. So that will build over the course of the year.

Your next question comes from the line of Kelsey Zhu with Autonomous.

So going back to AI. Where do you see [indiscernible] margin or top line opportunity brought by your own AI investment? And any thoughts around sizing that top line margin outside from AI would be really hopeful. I know you've talked about aerial imagery, digital forensics. Any other incremental revenue or cost opportunities you want to highlight here that weren't previously available in the pre-AI world?

Yes. Thanks, Kelsey. We've been talking about the AI opportunity on our new products, and we see that continuing to build. From a material impact standpoint, we haven't sized it on the top line. We still continue to think of it as a long-term opportunity.

On the margin, we do see -- we are seeing the benefit of efficiency and productivity on our software and development teams, on our data ingestion and others. We're also, at the same time, investing in the new technology and in our data to build the AI ready and the MCP solutions that we're excited about. So I would say for the time being, we see it as a push on the margin and is embedded in our guide of gradual margin expansion for the year.

And I guess, perhaps to add another dimension to this [ and just ] answering it broadly because there are a lot of applications. But I think if we think about where it can be most impactful. And we look at what the industry is trying to achieve, one of their top objectives is increasing productivity. Whether it's for an underwriter, or an agent, or a claims professional. And that's where I think we can accelerate and support that productivity objective.

It's an area where in other parts of our business when we have been able to demonstrate productivity improvement, for instance, with a claims adjuster, or a claims estimator that demonstrates real value for them because they can accomplish more faster, that becomes a clear path to value realization and our ability to participate in that value realization. So I think, if we think about that broader opportunity, if we can support that activity, applying our data to it, integrating those data sets, and we're improving that productivity for that -- for that client, then I think that supports value realization in terms of the longer-term contracts that we enter into and demonstrating value in a similar fashion to what we've also been able to realize demonstrated by the stronger subscription growth that we've been able to achieve because of our Core Lines Reimagined initiative. That was digitizing a lot of the data, improving their access. We've heard it directly and indirectly that that's improved productivity. And I think AI will be an extension, potentially an acceleration of that opportunity, which then supports our ability to capture value through that message. So that's a very broad answer, but I think that captures what we see as the primary opportunity for monetization on our front.

Your next question comes from the line of Alex Kramm with UBS.

Lee, you mentioned this, I think, underwriting platform that you're developing with 1 client, not sure to what degree that was disclosed already. But can you maybe flesh out what exactly you're doing there? And obviously, like the revenue model there. Is this just a one-off with one client [indiscernible] this becoming more of an industry utility over time? And are there opportunities to do something similar with other [indiscernible], obviously?

Yes, Alex. So this is a -- it is a one-off specific to this customer. But I think it's indicative of our clients' broad objectives to think about how they can restructure their processes and integrate different data sets. And so specifically, as we discussed in the call, the project is to work with them on restructuring, reimagining their underwriting process. Integrating a range of our data sets as well as agentic technologies that we are providing on the underwriting side to be able to improve the efficiency and the effectiveness of that underwriting process. And that came after an RFP of a large number of potential clients some from the technology side, some from the software side, some from the AI side. But it was our familiarity with the process our data governance elements, and they're comfort with our knowledge and expertise on it that drove it.

So it is specific to the needs of that client and what their objectives are. And that's, I think, a reflection of the stronger strategic dialogue that we've had with a variety of our clients, as well as our expertise. But I would also [indiscernible] as something that we're hearing from a range of our clients and something that I could see us doing with a much larger number of our clients.

Your next question comes from the line of Jason Haas with Wells Fargo.

Can you talk about the moat around your underwriting data analytics solutions business? And what prevents your competitors or largest customers from using AI to recreate this data? And I know there's a lot that goes into it, but could you could talk about some of the major data that's in there, and [indiscernible]?

Yes. Jason, I'm going to hand this over to my colleague, Saurabh Khemka, who runs all of our underwriting businesses to address that.

Yes, Jason. So let me talk about a few things. First, a lot of our data sets are proprietary to us, whether it's contributory or self source. So that is an element of moat.

The second, what we do with the data is analytics that our normalization, or looking at data across our platforms, which is, again, something that is unique to us. The third thing I'll say is our experience and our focus on risk segmentation. So taking that data and creating analytics that life -- [indiscernible] segmentation for our clients is a differentiator for us. I mean, we've talked about aerial imagery today, we went from roof age to roof condition to specific wind, and [ hail perils ], and now looking at remaining life for. These are all new segmentation.

And then finally, we are the trusted providers. So when we think about how we standardize and the scale at which we standardize when we go to regulators, we're able to offer our turnkey solution to our customers, which is a filed analytics that they can use very easily. So that describes a broader way is kind of the moat that we have.

Your next question comes from Scott Wurtzel with Wolfe Research.

Apologies if I missed this earlier, but just wondering if you can talk about the sustainability of the subscription OCC revenue growth. [indiscernible] still a little bit to 7%, but just wondering if you can talk about, if we can see a sustainable growth in that high single-digit range?

Yes. Thanks for the question, Scott. We do continue to see sustainability of that subscription growth rate. We talked about the fact that we had double digits in the year ago cycle, and that level may not itself be sustainable, but where we are is amply continuing and continues to be strong.

As we talked about some of the subscription outcomes we saw in the first quarter not just in one business, not only in our [ forms rules and loss cost ] business, which continues to see the benefit and strong retention and even extending terms and improved pricing based on Core Lines Reimagine, but also strong subscription growth across our portfolio in the Catastrophe and Risk Solutions business, in the Property and Restoration solutions business as carriers continue to see the value and the AI enhancements driven on the solutions.

So we really see strong engagement across our portfolio and the investments that we're doing on those products, driving good outcomes and good conversations with the clients.

This concludes today's call. Thank you for attending. You may now disconnect.

Good afternoon, everyone. I'm Curt Nagle, the Senior Business and Information Services Analyst here at BofA. This session is Verisk. Very pleased to have CFO, Elizabeth Mann with us. This is going to be structured as a fireside. Time permitting, we can field any questions from the audience. But with that, welcome, Elizabeth. Thank you for joining us and looking forward to the conversation.

Thanks so much. Thanks for having me here, and thanks, everyone, for joining.

Great. So coming off your Investor Day last week, lots of new findings. But at least for me, I think one of the most important -- one of the biggest themes was the idea of expanding Verisk's open architecture, connecting the broader ecosystem. So if you look at the growth opportunities, let's say, over the next 3 years or so, in terms of the adjacencies or new product lines where you think you can see the most immediate opportunity or upside for Verisk? How would you describe that?

Yes. Yes. Thanks, Curt. We're particularly excited about our open ecosystem and the ecosystem opportunities that we have in a number of our products. And philosophically, this comes from the opportunity we have. We are so connected to the insurance industry, and they already rely on us for many solutions. This gives an opportunity that's really win-win for us to find and identify new value-added solutions.

Obviously, we do some of this organically. But when we see great products out there that we think have a an opportunity to really bring value to the industry. We can integrate them into some of our existing solutions and participate usually by a revenue share. And this helps bring new opportunities to our customer set, which they have told us they very much rely on.

And so we gave a number of examples of this at our Investor Day, but we can talk more about how we've been doing this in our property estimating solutions business. We're doing this increasingly in our anti-fraud space and elsewhere across the business.

Yes. Maybe it would be worth diving to some of these verticals with the property estimation. You walked away from potential acquisition, just given, let's call it, government friction. But maybe the playbook there and then, yes, fraud, which was a big topic at the Investor Day and lots of new interesting assets there. And yes, maybe dig into that a little bit more.

Yes. Yes, let me start with our property estimating solutions business, which as you said, we're really excited about the organic opportunity for that business, both in the products that we're creating and also in the ecosystem that we're bringing available to our customers. And our customers, the customer set for that business, it's important to remember that our property estimating solutions business is a business that has -- it serves both the insurance carriers, it also serves the contractors that are doing the work for property repair that's covered by an insurance name. And it also covers the third-party adjusters who help facilitate that workflow.

We have different solutions for those different groups. It is a workflow that connects that industry and is built upon a proprietary data set, which is the pricing for -- to agree on sort of the estimate for property repair work. And so the pricing -- so if you think about how this is used, if a tree falls on your house, you call your carrier to submit a claim. There's an adjuster that reviews that and eventually kind of -- they may well go on site.

They will -- they can use our software and tools to assess the damage, figure out what is the estimate that should be written and what is the cost for each of those line items. The line items can be building materials, like how many roof tiles or how many sheets of drywall. It can be the contents of the house if that was damaged. So was there a laptop? Was there a furniture that was damaged? And it's the labor involved as well.

And of those -- of that pricing data set, some of it may be more transparent in the markets than others, but the -- it's the labor cost that we track in great detail across 460 jurisdictions that is not at all transparent in the market and difficult to replicate. So it's the core and the quality of the pricing data set that's at the heart of the value proposition that's agreed upon between the carriers and the contractors.

So there -- it's a 2-sided market. They obviously have different -- they each want the prices to go in the opposite direction. It's kept honest by that continued agreement. And so this is fundamentally a network business. To that, we talked -- actually, we talked on our fourth quarter earnings call about the AI-driven enhancements to that process and the products there moving from Xact expert, which relied on rules-based and machine learning tools to help carriers ensure that the estimates that they're receiving are and approving are in line with their own internal guidelines in line with regulatory requirements in line with building codes. We can then move -- and we can build on GenAI for automatic photo tagging as we have done in XactAI. And eventually, we've got Xact Gen now that has generative based ability to create an estimate and then be reviewed by that.

And were traceable and -- yes.

Yes, yes. And it's traceable and auditable is important. It's also important to remember, this pricing data -- and these outcomes of claims are -- there is frequent litigation around claims outcomes. And so the reliability and defensibility of those pricing estimates is of high importance to the carrier community.

Yes. Sure. Labor point is really interesting, too. I haven't thought about that. But I mean, very opaque, I would imagine so.

Yes.

I would imagine there's a lot of value we can drive in that. Maybe the detriment of some of the services, but maybe a more honest assessment.

Yes. And just last month, I was at our elevation.

That's not a fair way to put it. More accurate, I want to say. You know what I mean. Yes.

Just last month, I was at our Elevate Conference in Utah, which brings together the different groups in this community with Verisk Conference as a central point. And they talk consistently about the value of that ecosystem and then the value of the third-party solutions that are adding value to the platform from them.

Maybe talk about fraud a little bit more. I thought some of the points you made on, I guess, I'll call it the photo repository, right, and how it's contributory and very much a not great effect. But yes, maybe track a little bit more on fraud.

Yes. So our anti-fraud business is on our claims side is a great business. We help carriers identify or flag which of their claims should be further reviewed for potential fraud. We are going to put out a study recently that -- or soon that took a look at the prevalence of fraud in the insurance industry with AI-based tools. Unfortunately, it is increasing the ease with which fraudsters can submit or can falsify claims that they are submitting in fraud. And what's -- one of the things that's shocking in some of our research in the studies is about 1 in 3 consumers view it as okay or not a problem, to alter a photo they are submitting to their insurance company to support a claim, which then can very easily lead into fraud.

Our antifraud database, which has historically has always been the leading place for insurers to review fraud claims and be able to identify -- the single biggest predictor of fraud is quite simply what is the prior claims history of that climate, whether it's an individual or small business, and so we help the contributory database helps them identify that.

And now -- so that was our historical strength. We are moving into the future with new technologies and AI to be able to identify the more modern fraudsters. So we have built what's called digital media forensics, which now helps them identify if there is a photo submitted with a claim. Has it been digitally manipulated or does it appear 3 years ago in a different claim and somebody is duplicating the photo.

We have built up in this a data set of over 600 million images that are contributing -- contributed by the carriers. It has contributions from at least 5 of the top 10 carriers and growing by the day. And this, we think, is just a perfect encapsulation of the fact that as technology develops, carriers are seeing more value in the contributed -- in what they can get from the contributed data sets that Verisk can bring to the table. We are creating more data sets, not less and bringing more value to the industry, in this case, in identification of potential fraud.

Okay. What keeps the other 5 from not joining? It seems again, the contributory network effects. Why not be part of the ...

We're working on it.

Okay. Fair enough. So another focus for the Analyst Day was using enabled automation to lower your internal cost structure. As you're deploying whether it's agentic or generative AI, how do you been sure those efficiency gains flow through the bottom line aside from maybe being competed away? I mean, you already have very high margins. So yes.

Yes. Yes. In terms of making sure that we have efficiency gains and not competing away, fundamentally, that gets that protecting the value of the top line. We've never priced our products to cost. We've never said, well, it cost us this much and so you get a 15% markup or whatever it is. So we are focusing the pricing on what is the value delivered to customers and what is the -- what are the alternative ways at getting at the same solutions.

If you think about it from an insurance carrier standpoint, for every dollar they take in, in premium, they spend on average $0.70 paid out in claims. They spend on average $0.25 of OpEx in running their underwriting and their claims departments and the -- and leaving about $0.05 of profit. And this is for the sort of operational insurance side of the house, set aside the investment side of the house for a minute.

But -- so if you think about that and then Verisk's revenues, we said were, on average, 30 basis points of the industry premium. So of that dollar they're spending $0.03 on Verisk Solutions system-wide. That $0.03 is protecting the $0.70 of claims and ensuring that they price each new policy, right, that they act correctly on each claims outcome. If you think about pricing and new policy, you come in with a price that's too high and someone else is going to take the business from you, you'll get competed away. You price that policy too low and you're going to be underwater on that bucket of claims. So it's maintaining the value of that $0.03 is what's fundamental to protecting our pricing or top line and therefore, our margins.

Right. And hopefully, enhancing the profitability of your customers in ...

Yes, exactly.

Give it like a fair value.

We think there is significant opportunity for that.

Switching gears a little bit. So you're enhancing your client risk tools and analytics. Your [indiscernible] models, climate volatility is becoming a big issue, a board issue, right, for a lot of companies. In terms of a growth opportunity for Verisk, I guess how would you size this? And how does that perhaps expand beyond sort of the traditional property and casualty business?

Yes. We think there is potential opportunity there. Our catastrophe and risk models are used -- we think they are the leading models to benchmark catastrophe risk. We do have a -- the traditional usage is for insurance and reinsurance for insurers to decide how much of the risk to seed to reinsurers for both parties to agree on the pricing. It's ultimately the benchmark on which they trade.

It is a sticky business in the sense that those decisions, those risk decisions have implications they drive through to the capital that's held against those risks. It has both regulatory implications for both insurers and reinsurers as well as ratings implications, which is very important to them. So those -- that's the traditional value proposition of our catastrophe risks. But you're right, as increasing climate focus becomes, as you say, a topic in the boardroom, a topic for financial institutions that have exposure to property and catastrophe risk, yes, we do see opportunity there.

Okay. Very good. So I think across the information services space, arguably one of the most -- maybe the most defensible set of data assets, right? It's a very large proportion is purely contributory, and there's obviously a lot more built around that, that's walled off and protected. As we're -- as you're pushing into, again, newer verticals or adjacent verticals, how do you incentivize, I guess, early adoption for your customers? Historically, I think it's kind of a slow-moving industry, but how should we think about them just getting the flywheel spinning quicker, I suppose?

Yes. It's a great question. I mean in terms of incentivizing new data sets, we gave -- we showed some of the stats at our Investor Day of a number of data sets contributed increasing over the last year or 2 by nearly $100 million. So when it is adjacent to our core products, I think that as we demonstrate some of the stats and some of the outcomes to our customers, for example in our core lines business, we've created more and more benchmarking reports, which can allow a carrier to compare their own outcomes or performance to industry benchmarks.

As we see this as we have more senior level strategic engagement, they can get very interested in this and say, oh, that's interesting. You can benchmark for me one line of business in one line of sight in one state. We've had some of them then say to us, "Oh, can you do this for me in this other line of business." And we say, "Well, actually, you haven't historically contributed that type of data to us." And so that can incentivize the contribution.

The digital media forensics is another one where we've been able to prove out the value proposition very quickly because we're already connected to the industry, we can create proof of concepts or we can prove out very quickly without them spinning up a whole new contract NDA data contribution. We can take the data that we already have in-house from them, and we can say, look, with this tool, you could identify $10 million worth of fraud in the past in your past year. Is that of interest to you? And so we can move quickly with that.

And then that gets flywheels ...

Yes, that gets flywheels spinning.

Go on from there. Yes. Okay. That makes sense. International markets and historically a smaller piece of business for you versus domestic. I guess, how critical are non-U.S. markets in terms of achieving your long-term growth targets organically?

Yes, we're --

Or through inorganic growth.

Yes. We're comfortable with the portfolio we have. We're very comfortable with our current long-term growth targets of 6% to 8%. We do have some businesses -- I mean today, international revenue is about 17% of our total quite a bit of that comes in our catastrophe and risk modeling business, which is obviously a global view of risk and has global customers. More generally, I think we've had -- we have a strong presence now in the U.K. between our Lloyd's market business and then some general insurance and claims businesses. So I think we've -- as we achieve critical mass in those markets, we continue to see opportunity to sort of densify. But this is not an environment where we need to go out and plant a flag in different countries around the world.

In Europe, is that much of an opportunity?

It is a bit of an opportunity, yes. And in the past 3-year cycle, we've acquired a couple of businesses in Germany focused on the claims side and building us to a position where we are sort of the only independent claims technology business in Europe in a market that's fairly concentrated with some high position carriers.

And I guess how do the data repositors, the data sets that the contribution models differ from the United States? Is there any -- is there a correlator there, too? Or ...

Yes. We would love to have contributory data businesses all over the world. It's a great business model. For structural reasons, it's ...

The founding of your company.

Yes. And obviously, it goes back to the foundation of our company in the U.S. in many other international markets, either there may be a nonprofit player already or look, the need for the contributory data set in the U.S. came about because of the fragmentation of state-by-state regulation, which doesn't really exist in other domestic markets and the lack of concentration in the overall insurance industry. Many of the markets in Europe have -- they don't have that state-by-state regulation phenomenon and they have more concentrated players. So what we're doing in Germany is a little bit of an alternative view to that.

Okay. So structurally different, right?

Yes.

EU doesn't mean the U.S. and okay, just -- yes.

Yes.

Okay. Understood. That makes sense. So product velocity, innovation, another, I think, pretty, pretty important focus.

Yes.

Structural changes you made internally right, to ensure your new analytical tools, I guess, come to market quicker and ultimately are adopted by our your customers?

Yes. I mean I'll start with the simple structural tool, which is that we had a bunch of businesses in other verticals, and we divested those. So the structural simplicity of being an insurance-only focused business and insurance only focused leadership team meant that all of our capital was either invested in the insurance business or return to shareholders. And so that, I think, accelerated the focus on what we could do and accelerated the resources that we were deploying on it. That's point one.

And then point two, we recognize this has been gradual, but in '22, we definitely doubled down on the moment in time that we were at of the insurance industry really needing more modern digital tools which Verisk was in a unique position to provide because at the end of the day, that's why we were created to help them bring better data and analytics to the table to better select the right risk, price the right risk and combat fraud. That's why we were created in the 70s.

But in the 2020s, there has been a unique opportunity to do that. That was abundantly clear throughout, but particularly even in 2022, before ChatGPT launched and every conversation started being about AI, we were already on this path of investing in the digitization and better data and analytics and tools for our customers. So I think that -- that focus is what drove the product acceleration over the last 3 years and which we think can continue.

And you see it manifested in our financials and in our results, whether it's the acceleration of our subscription revenue growth to be north of 8% in the last 3 years or whether it's in that product inflection, we measure the number of products per customer as did -- depending on the size of the customer as a way of assessing our land and expand is what some people call it, that has definitively inflected upwards over the last 3 years.

So maybe looking at it from the -- and I'll use a comparison looking at from the customer side and thinking about kind of rate of change and adoption of more sophisticated technological tools. A couple of sessions ago, Steve Hasker was talking about how they've dramatically increased the number of centric tools, but they're kind of ahead of the curve in terms of rate of adoption by the customers.

Maybe a corollary to the insurance agency. So -- in terms of willingness need or just kind of rate of adoption for your core P&C clients, where does that sit right now? Is there still a good amount of friction because of there's slow to change industries, I suppose. So yes, where does that stand?

Yes. I think it is a journey. And you're right, the industry is takes a cautious look. You have to keep in mind, it is a regulator very --

Highly regulated.

Highly regulated, focused on risk and required to bring auditability defensibility. Remember, insurance claims are some of the most litigated contracts in the world. So if they say your premium is x or your claim was y, and they need to be able to back that up in any potential lawsuit. So that's one element of it.

I think you're seeing -- but clearly, there is an appetite for modernization and appetite for more efficient work. I think there was an adjustment period where many of them -- we led on sort of the AI governance side of things. We put out an ethical AI policy, very early on our website. We have established an AI Governance Board very early on to review for each model, for each product that we build, what are the potential risks? How is our IP being protected in this? And are there any potential data risks or protection?

So we -- so we review that very carefully because we view it as doing it on behalf of the industry with that trust on a solid foundation. I think our customers are interested in taking on products. They themselves then had to establish their AI governance boards and they may have their review processes. In some cases, it may mean slightly longer sales cycle as they review things. We were never -- we always have dealt with kind of long sales cycle. So it's something new for us.

And I would imagine that's a moat as well.

Yes. Okay. Yes. So that's been good. And then look, large company insurance -- the insurance industry is doing quite a bit with AI on their own. That doesn't replace what they are doing with us. If you go back to that economic model I described of the dollar they get on premium, $0.70 on claims, the $0.25 that they spend on OpEx, that's their target. The things that they do internally and operationally, the $0.03 that they spend with us for better data and analytics is not going to be their first target to replace? Or if they try to rebuild that it would cost quite a bit more than the $0.03, not just want to transition, but on a permanent and ongoing basis.

And that was sort of the next natural question. Are you seeing some of your larger clients trying to do this?

Trying to do what? Trying to use AI? Absolutely.

To internalize demand? Yes.

To replace what we are doing for them? We are not seeing that.

Okay. I guess one of the more common questions I get. Just thinking about sort of the growth arc aside from just general pricing and new product adoption is a sensitivity to either net written premiums or just overall industry profitability, which can be volatile. So I guess in terms of just answering -- I don't know if it's insulation but maybe sensitivity to those things and ultimately, pricing power. How would you answer that, I guess, that question? Yes.

Yes. So we have historically grown faster than the insurance industry, net written premium growth, but much more stable through the cycle. So if you look since 2009 because that's when we went public, so that's when we have public financials. Insurance industry net written premium growth on average was about 5% during that cycle. Our insurance business, organic constant currency revenue growth was about 7% on average.

If you -- but the variability of the insurance industry ranges from negative growth in some years to tipping double digits most recently. So wider dispersion in Verisk's growth has been 6% to 8%, basically in that -- between 6% and 8%. So a much tighter band around that 7% outcome. And actually, in that time period, if you look at the years that were soft markets from an insurance industry perspective, versus hard markets.

So the soft market -- during the soft market, so low premium growth, Verisk's average revenue growth was 6.8%. If you look in the hard market years, Verisk's average revenue growth was 7.3%. So a little bit of a headwind and a little bit of a differentiation between those, but it kind of still both around to 7%.

It's a band, a pretty tight one.

Yes. It's a band.

I would imagine at least a decent bit of that is just the consequence of contract pricing, right? So ...

I'm sorry?

Being on contract pricing, right?

Yes.

So longer duration contracts that kind of ride through and that gives you the stability of earnings and -- okay. That makes sense. So yes, I guess kind of maybe a similar vein, right? So Elizabeth, I think started your tenure in 2022, a lot of change. Kind of getting back to the basics, and I mean that in a very good way, pure-play company, a big market, clear need for what you do. When you're meeting with investors, and I'm sure you've spoken to a lot of them today, what do you think is still misunderstood, misunderappreciated about Verisk's market position, growth opportunities, however you want to answer it?

Yes. I think 2 things. We just touched on -- one of them is the premium, and there's a near-term bias of we're coming off 2, 3 years with a very strong premium growth. And so there's a sense of, oh, if premium growth is coming down, then your revenue is going to come down. To me, one of the charts that we had in the Investor Day shows from a longer-term historical view, this is just normalizing to an industry average, and we have sustainably been able to grow above the industry. So maybe a modest headwind, but not something that we are significantly concerned about.

The second topic that we've touched on a little bit here and that clearly I've spent a lot of time talking about, obviously, is the AI question. And I think it's important for people to understand that AI can enhance what we are doing for customers. It can enhance what the customers are doing themselves, but the defensibility of our business relies on the value proposition that we're bringing to the table.

The businesses that we have and that we go to market with, these are not generic workflow tools. These are not just some sort of random or analytics or piece of --

You're not a workflow platform.

Yes. We're not a workflow platform. If you look at -- we had -- there was a pie chart in our Investor Day that showed of our revenues in terms of defensibility to AI. We had 40% of the revenues come from contributory data. 20% of the revenues are built off of proprietary data. 25% are built off of proprietary IP and analytics that generally rely on that property proprietary data and then 10% from software, 5% from services.

But the 85% has -- the 85% of that business maps to essentially our 5 largest businesses, which each have in their own way a distinctive value proposition for the customer set that we think will continue to prove out. Our products can be modernized with AI. And what the carriers want to do with AI independently will not replace the value of those 5 strong businesses.

Very good. Maybe I'll just pause for a second if there are any questions just from the audience, happy to take them. Otherwise, I can go on. Cool. All right.

Two ones. One, just on capital allocation in the next, just do a lightning round of word association. So recently announced a large authorization, $2.5 billion, I think you are going to execute on $1.5 billion. so it seems like there is -- maybe you could say a shift in terms of where capital is going. And maybe given the valuation, I think that probably makes sense. I guess how do you weigh that, again, in terms of the accretion from that, the level of buybacks and then just weighing and being able to pounce on whatever the next big opportunity or not big opportunity, but opportunistic opportunity. Bolt-on, right?

Yes. Yes. So yes, I think, look, we're fortunate to have a cash-generative business. Yes, we will -- our capital allocation framework will look at any given moment in time, where is the opportunity to drive the greatest return. Obviously -- so at the Investor Day, we kind of gave the framework of the organic investments, the selective M&A and the return of capital to shareholders.

The organic investment portfolio, we feel very good about. We're driving strong returns. We showed some of the road maps coming there. We've funded that CapEx roughly in line with where we've been spending it. So we're very happy with those opportunities. There's -- we have a lot more ideas than what we're funding. So there's more there.

From an M&A standpoint, we will continue to look in the markets, particularly when there are valuation dislocations in an environment like this. Our priorities, first and foremost, we are still focused solely on the insurance industry as we have been since 2022. We look for proprietary data sets, whether acquiring new ones or enhancing our own, expanding into new insurance markets, new either customer end segments or new types of risk. And then third, bringing efficiencies and automation to our clients.

It's kind of our priority set. We -- in terms of things of scale, we will continue to look at -- we will continue to be open in the markets, but there's -- we don't see a significant need from where our portfolio is right now. And so in a dislocated market, we also see the opportunity of returning capital to shareholders.

At the right valuation, core business, nothing crazy, that makes total sense. Okay. Word association. Life insurance.

Growing.

Growing. Okay. Workflow tools.

Evolving.

Evolving, okay. Product velocity.

Accelerating.

Accelerating. AI.

Opportunity.

Opportunity. And we touched on this a little bit, but M&A in one word.

Selective.

Selective. All right. Very good. Cool. Elizabeth, really appreciate it. Thank you so much for the time and ...

Thank you so much. Thanks, everyone. Appreciate it.

All right. Good morning, everyone. Welcome again to the [indiscernible] talking about what you believe were the most important takeaways from the day before we get into some questions around the business.

Yes. Thanks so much, Scott. And thanks, everyone, here for joining and being inside with us here on what looks to be another beautiful day in New York.

Yes, we are just fresh off of our Investor Day last Thursday. If you haven't seen it yet, I encourage you to look at the slides as a great intro for Verisk.

I would say the three main takeaways, I'll start with the financials because this group cares about that. From a long-term financial targets, we essentially reiterated long-term financial targets for the next 3 years that are consistent with the ones that we stated 3 years ago and over delivered on for the past 3 years. And so we have consistent targets going forward. How we're going to get there is probably going to be a little bit different in a changing environment.

So that takes me to the second point, the theme that you heard really throughout our business presentations. As you've noted, AI is obviously a hot topic and a hot question in info services these days. From our perspective, we see it as an opportunity, not a threat. AI is useless without quality data to train on. And we believe we are -- that we house the largest, most comprehensive, most granular, most meaningful data set in the industry or for the industry. And for ways that we spent 3 or 4 hours articulating last week, we believe that is difficult to replicate. That still puts a great obligation on us to continue to modernize, to invest to make that data accessible to the industry in new ways of working and potentially to partner with others to do that, and we're committed and excited to doing that.

Got it. That's very helpful. And I have a few follow-ups on the Investor Day. But maybe if we go back a few -- a couple of weeks before that, you guys reported 4Q earnings a few weeks ago, and the results were, I think, better than expected, at least from the Street view, particularly, I think, on the underwriting OCC revenue growth. So maybe can you talk about the trends that you saw during the most recent quarter and some of the key assumptions underpinning your guidance for 2026?

Yes. Yes. So there are -- as we move from Investor Day and the long term, the strategic positioning for Verisk to just some of the near-term quarter in, quarter out, there have been some headwinds on near-term revenue. The primary driver of that really being kind of the light weather season that actually the U.S. experienced over the past year. So that is the primary driver for the headwind. Even despite those -- and that will persist into the first quarter because of the momentum dynamics in the business.

That said, there were some real areas of strength in the fourth quarter. There was our extreme -- our catastrophe and risk solutions did very well the catastrophe models, both from a new subscription and new customer standpoint as well as it was -- the fourth quarter was yet another quarter of very strong securitization market. As a reminder, the securitization market tends to be the most active in the second quarter of the year, followed by the fourth. So that strength is probably not likely to continue in the first quarter, though it may show up again for us in the second quarter.

There were some other areas of strength in our subscription businesses, the Life business, the Specialty Business Solution that we talk about and some good and actually some good transactional outcomes on our property data side. So there were some pockets of strength in the business even despite the weather headwinds. From what I highlighted, some of that may be -- may or may not recur in the first quarter. So taken all that together, we said at the time that we expect the first quarter to be the trough, both in terms of reported dollar revenue and growth rates as opposed to the fourth quarter.

But that said, but you were asking about opinions -- assumptions underpinning 2026. We're excited for 2026. Obviously, we reiterated our -- we gave the specific guidance range and reiterated our long-term targets. So we expect it to be another year yet again in line with the long-term targets. There are going to be some headwinds in the first quarter, maybe into the second -- into the first half. But going forward from there, we continue to see strong opportunity.

Got it. Got it. Now I guess going back to the Investor Day now, I think at least on the underwriting side, you discussed some of the results of like your Core Lines Reimagine program and how that has transformed your underwriting solutions business. So can you maybe go over what has changed over the last few years in your Core Lines and how you believe that division is sort of positioned going forward?

Yes. We're really excited about it. So the Core Lines Reimagine program is kind of our marquee reinvestment in our largest business, which is our forms, rules and loss cost business in the underwriting subsegment. That business goes back over 50 years to a consortium of the U.S. insurance industry who were contributing data to help build the insurance forms and the loss cost, the actuarially designed averages for what should be -- what is an expected loss across 32 different lines of business and a number of different sublines and regulatory filings in 50 states.

That business -- we asked ourselves about 5 years ago, what should that business look like today in a modern data-first environment, technology-enabled environment. And we came up with all the things we needed to do, which we put under the umbrella of Core Lines Reimagine. Now there were 20 different projects going on in there and 20 different work streams, which involved everything from -- well, starting -- before we started Core Lines Reimagine, we had moved the entire proprietary database to the cloud throughout the late 2018.

So we were -- now based on the cloud, what could we do with this data set? We were going to make it easier for customers to contribute data to us. We were going to speed the refresh and the analysis cycle on that data, and we were going to completely revolutionize the way that customers interacted with that data and consume the content from us. So if you think of the before era was -- well, way back when we used to mail people 300-page circulars, before Core Lines Reimagine, we had at least evolved to kind of PDFs that were downloaded from the web. But even 5 years ago, that was pretty antiquated. And so we've moved it to a much more workflow-agnostic way for the customer to access our data. If they still want to download PDFs and there are still customers that do that, that's okay. But for those who are moving into the -- moving with technology, you can get it via API, you can get it plugged into whatever policy administration system you have. And so you can imagine -- so it's just the next step of that of, okay, you can have your agentic AI talk to it.

So that's -- those are the modernizations that we've been doing. We've been going through it line of business by line of business, and we've launched now over 40 modules on a single platform. The end of the scope of that investment will finish by the end of this year, but we continue to see wide open opportunity for how we can continue to make it more easy and now more enabled for customers to interact with that content.

Got it. Got it. And then on the claims side, one of the topics we thought that was interesting from the day was your expansion of your partner ecosystem and your goal is to continue adding new partners in the coming years. So maybe can you give a few examples of the types of partners you've added to the claims ecosystem and how that helps better serve your customers?

Yes. We're super excited about this, and I'm super excited. I had a chance to spend some time in it in the last 6 months I was serving as Interim President of the Claims business. We now have a fantastic new President, Steve Kauderer, who just joined us at the Investor Day. But I got a chance to see kind of firsthand what some of those partnerships mean and look like and how important we are to the partners that are working with us. I'm going to give you two examples because the power of the ecosystem really applies in the two largest businesses in claims.

And starting with the property and restoration solutions business, they've had a history of partners, but we've significantly expanded it over the last 3 years. They now have 140 ecosystem partners on the system. As I said, we were at the conference for that business, Elevate was in February near Salt Lake City. I saw that. But the best example I see of an ecosystem partner is one where you can -- there's -- so the idea of the ecosystem is it's bringing new capabilities to customers that vastly increases what they can do on our platform. So one great example is a tool that turns a photo scan of a room directly into an estimation, like a sketch, an architectural sketch off of which they build the estimate.

So you can have -- so a property is damaged with a tree falling on the roof, you can have the adjuster and the contractor who are going to do the work. They go on site. They take an iPhone scan of like there's the broken window and the wall damage, and it will automatically turn it into a sketch. We now have AI-based tools. So our newest, but we've talked about the different evolutions of that from machine learning and rules-based tools to XactAI, which can then automate that photo of like here are the contents of the room and here are some pop-up options for how much those costs from a replacement value perspective. And now we have XactGen, which is an agentic AI tool to turn that sketch directly into an estimate for review by the individual.

Got it. Got it.

Actually, that's just one example, but I'll let you move on. You can ask me afterwards for the example in the anti-fraud space, which is very cool also.

Yes. And I guess if we take a step back here and kind of move to more broader insurance industry dynamics, I mean, one of the main questions we get from investors is around net written premium growth and how that has an impact on Verisk's organic constant currency revenue growth. And as we move from maybe a harder market in the last few years to some people say soft market, some people say more normalized growth. Can you just talk about the different puts and takes there, the overall health of the industry and how you would expect the changes in premium growth to translate to demand and overall revenue growth at Verisk?

Yes. So the good news is we think the health of our end market and our industry is very strong. That's always a good thing for us. The insurance industry had in the, call it, early '20s, '21, '22 had severe challenges on profitability, which is what led to the very high premium growth environment as they needed to reachieve profitability in their books. They now -- I think, broadly speaking, most would say they've achieved rate adequacy, meaning they're charging enough for the policies that they want to write. And they're moving to a world where they want to grow. They want to do more business. They want to write more policies, and that makes them more competitive on the premiums that they're writing.

If you want to be more competitive on premiums, then you want to price most accurately and you want to make sure you have the best data and analytics to figure out what's the right price to charge for the premium that you're bidding. You don't want to charge too much or you're going to get competed against. You don't want to charge too little or you're going to be writing unprofitable policies. So ongoing need for data and analytics in this environment.

More specifically, I know a number of people have focused on the stat we've quoted 20% to 25% of our revenues are on a contract that has an input from the premium growth of that carrier. That was set up many years ago when we separated out, we became an independent company no longer owned by the industry. And we set a pricing model for some of those products where we would grow as the insurance industry continued to grow.

We think that's a good thing because at the end of the day, it ties us to a healthy growing market and gives us an input from growth, from premium growth, which we continue to see growing at the mid-single digits. It doesn't need to be at the double-digit premium growth that it's been over the last year or 2.

The final point I'll say, even those contracts, the premium growth is an input. It is not the sole determinant of that growth, and that's how we've achieved the consistency and stability of revenue growth that we have over time.

Got it. That's helpful. We'll talk about some of the different moving parts on sort of the claims and transaction revenues next. But I guess subscription organic constant currency revenue growth continues to be, I think, a bright spot for the company, pretty healthy high single-digit growth in recent quarters. So could you maybe talk about what's been driving that growth between pricing, new logos, new products with existing clients and the different puts and takes there?

Yes. Thanks. Yes, we're very proud of our subscription growth. We've generally done in the high single digits range. I think the Investor Day, the 3-year average of it was 8.4%. That's been good. And we think that's a testament of the value that we're bringing to our customers. I think some of it is the impact of the Core Lines Reimagine investment and reinvestment that we talked about. We were able to show our customers significant investment and significant value and efficiency opportunities for them in interacting with content that they've worked with for several years. All of a sudden, they could get it much more easily. They could work with it in much more easy ways, and they themselves were saving a lot of time. That was basically monetized through price.

And so I mentioned at the Investor Day that we overdelivered on our pricing targets. We had previously targeted kind of 3 to 4 percentage points average pricing growth over that 3-year cycle. We delivered a little north of 5%. And so that's coming in on those subscriptions as we're seeing greater traction with customers.

It's also coming from greater market -- greater go-to-market and sales and customer engagement. And then finally, there's also a slide in our investor deck that shows our product penetration by size of customer. And you can see there an inflection in the growth rate. So the number of products per customer accelerated during that time period.

Yes. Makes sense. And then I guess on the claims side, I mean, you touched on this a little bit during your discussion around guidance and the shape of the year. But just wondering if we can kind of maybe click into that a little bit more and talk about how we should think about the trajectory of claims revenue in -- throughout 2026, given some of the different moving parts, the impacts from the storms of 2 years ago, combined with lower weather from last year and how that all kind of fits in.

Yes. There's no question, the claims business has some tough headwinds. Everyone was expecting them in the fourth quarter. Those definitely continue into the first quarter to first half of the year as the prior year had fairly elevated weather in the first half and continue. There was still 1 year ago, now there was still work and reconstruction being done in the aftermath of Hurricanes Helene and Milton. So tough comps in claims from that time a year ago.

There was also very strong subscription growth across the portfolio. I think we had double-digit subscription growth in the first quarter of 2025. We love to do that. It's part of the strong growth that you've seen. We'll do that any time we can. But we did say at the time that we didn't expect double digits to be the long-term subscription growth rate. So that also presents a tough comp around the business.

Got it. Got it. And then if we kind of go over to like the go-to-market selling environment, I think your sales commentary as of late has been pretty positive. I think even if we go back to the 3Q earnings call, you guys were talking about surpassing your quota for the second straight year at that time of the year. So maybe can you talk -- just discuss the overall go-to-market approach across the business and the overall state of the selling environment and any highlights from the Investor Day as well. I know that was part of the discussion, too.

Yes. So we go to market -- we have a sales force in each of the different respective businesses that focuses kind of specifically product by product and then supported by kind of a large customer, a client strategy group and supported by -- Lee has talked a lot about strategic engagement with the C-suite and with major customers. It's not just him. It's all the way -- our business leads are very actively involved with customers. So a ton of customer outreach.

I think continued opportunity and may even be an area of investment to expand some of our sales force or some of our coverage. We have focused over that last 3 years with Lee's focus on the senior level strategic engagement, starting with our top customers. We think there's more opportunity, and we can bring more and better coverage to kind of the mid-tier, maybe customers 26 to 50, 26 to 100 are very active customers, and we think we can see more engagement there.

Got it. Got it. And then I guess more broadly, shifting over to kind of industry competitive dynamics, how do you feel about just your positioning across the key areas of the business, whether it's the core P&C underwriting, property estimating business, the cat modeling, auto side. I guess what in your mind sets Verisk apart from competitors? And then also, are there specific areas where you may be looking to improve your offering suite to most of your competitive position in other parts?

Yes. Look, I think Verisk is unique. And the way I like to think about it, I mean, the whole is and can be greater than the sum of the parts. And as we have different competitors, they are -- they compete with individual parts of our business. We don't see anybody that has the breadth of data that we have across our business. And so we think that gives us an opportunity to be differentiated even in each of those individual competition areas.

One great example is property data. We focus on property data in the forms, rules and loss costs business covers property. The anti-fraud business covers property. But our underwriting data and analytics solutions has the world's leading commercial property database for insurance purposes, which is different from ones for real estate or valuation purposes. The catastrophe modeling business at the end of the day is really about property risk primarily.

And then -- and obviously, our property and restoration solutions business spends a lot of time going in there, getting hands on, being deeply involved in property repair. And so that gives us a uniform view around properties that -- and candidly, historically, I'm not sure we invested too much time in really bringing all of these data sets together. But as we focus on it and as the ability to invest and work with data becomes more efficient with AI, we think we can bring differentiated insights at the property level that, say, a competitor in our catastrophe and risk solutions business or a competitor in our property and restoration solutions business couldn't do on their own.

Yes. That's a great segue because it wouldn't be an info services fireside chat without AI questions. So can you talk about just the different risks and opportunities with AI across the business? And when we think about it internally, do you see it as more of an efficiency driver or revenue growth driver? Just how you see it impacting the business more broadly?

Yes. We see it -- first and foremost, I think we see it as a revenue growth driver. The opportunity to create new products, to create new products quickly and to bring them to market and the ease with which our customers can interact with our data will only drive usage over time, we believe.

Now there's an adoption rate for the insurance industry. And remember, this is a very heavily regulated industry. And so the regulators also need to be comfortable. There needs to be auditability and traceability of analysis being done. We think we actually have a differentiated ability to work with the regulators and kind of those relationships to help people get comfortable with the use of the data. So primarily revenue and product opportunity.

Will we use it internally for efficiencies? Absolutely. We think we can drive our own internal operational efficiency with it. We already are fortunate to start off with pretty high margins. So it's not like we have huge pockets of people doing inefficient and manual analysis. So it's more that it will take the insight that we have and enable it to be more effective and get more quickly at data patterns, insights, building new products and things like that.

So for us, the efficiency gains, we think, will be significantly repurposed and reinvested into the business to focus on the revenue growth opportunities we were talking about. And all of it would be netted together in the expected margin expansion opportunity of 25 to 75 basis points annually.

Got it. Got it. And then just as a follow-up, I mean, just on like the data side, right, because that's a big question that we do get from investors is around proprietary data and how it's differentiated in terms of warding off some of these threats. So maybe can you talk about how you believe your data is differentiated? I know you guys put some numbers around it at the Investor Day. And then maybe talk a little bit more about those industry dynamics given like regulatory considerations with the industry such that I think in our view, it gives you guys a healthy moat for AI. I would love to hear your thoughts on it.

Yes. So look, the heart of our data moat would be the contributory data which is contributed to us by the industry. I think we said in there, we have over 2,000 data sets contributed to us by industry participants. And it's not just that they kind of download it to us and somebody else could come in and like digitally ingest all of that. It comes to us in wildly different formats and wildly different and completely not uniform architectures and underlying projections. Like for example, when we were at the Investor Day, we were talking about the property that we were in was a hotel, and it had been -- hypothetically, it could have been underwritten by three different carriers. One of them would classify it as a hotel. One would classify it as a hotel with a conference center, one would classify it as a mixed-use entertainment building.

They each might underwrite the policy with three different deductible levels. And then they each put on their own limitations, endorsements, coverage levels. So those three policies, same underlying asset are not at all uniform. You couldn't have some big tech provider ingest all of that and decide what was the loss cost, what is the average? Like how do you uniformize those policies. So that's the big part of it.

Another -- I think we said another 20% of our revenues is based on proprietary data that we generate and build in-house based on our industry insights and based on, in some cases, physical field reps going on site and inspecting buildings at the invitation usually of our clients. So that is also difficult to replicate. And then there's other elements that are proprietary analytics that are built on the underlying data set. So if you don't have the data, you can't -- I guess you can make the analytic, but it would be -- it wouldn't spit out a meaningful answer without the data to build or train it on.

Got it. And then I guess we move on to capital allocation. On 4Q earnings, you guys announced and I think recently completed that $1.5 billion accelerated share repurchase plan. So I was wondering if you can maybe talk about your broader capital allocation strategy here as we think about the near term and then as well over the course of the medium term on what you guys -- the guidance you kind of gave at your Investor Day.

Yes. I think -- so our primary priority for capital allocation is organic investment in the business. We continue to see a ton of opportunity, and have been investing on the CapEx side to continue to build that out. Second is selective M&A. And then third is return of capital to shareholders. I think at the Investor Day, we had a slide that over the past 3 years, we -- of our capital generated for shareholders, I think 15% of it went to the organic M&A -- sorry, organic investment, 10% on M&A and 75% on return of capital to shareholders. That's probably a reasonable balance. I don't know that it's going to be exactly like that going forward, but some breakdown like that.

Got it. And then I guess on the M&A front, I mean, what are -- when you talk about selective M&A, what types of assets are you guys typically looking for? Is it capability expansion, geographic expansion? How do you guys sort of view the M&A market and what you're sort of looking for?

Yes. I would say our M&A strategy focuses on three priorities. The first is either acquiring new or enhancing our own proprietary data sets. So we are a data-first company, and that will be kind of our first priority on M&A. The second priority is on expanding our knowledge of different or growing emerging risk areas or moving into new customer segments. And so particularly, the customer segment can refer to international expansion, which we've had some international acquisitions or it can get us into -- get us positioned into new and growing areas within the insurance industry. So the important thing to know is that from a customer standpoint, we serve the insurance industry, but the carriers are not our only customer type.

I think today, it's about 70% of our revenue coming from carriers. But there's a ton of interesting growth in brokers, reinsurers, managing general agents, claims professionals like independent adjusters. So as the carriers change their business model and in some cases, outsource or create independent providers for different parts of their business, like you can think of the MGA trend as one like that, that creates new opportunities for us to service those pockets, and we can continue to do some of that organically, or we can -- or we may make acquisitions that puts us into new parts of the business.

And then finally, the third priority of those is efficiency, automation and workflow tools for our clients. Essentially, that is kind of almost a delivery mechanism for probably something of strength in the first two.

Got it. Got it. And before we get to our last question, I just wanted to just sneak one in on margins. And when you look at the medium-term guide, you guys reiterated your targets for 25 to 75 basis points of margin expansion. But I think over the last cycle, there was some outperformance. But for this cycle, you talked about really kind of being in that range given you will be investing back into the business. So can you maybe talk about some of those top investment priorities for the company over the medium term?

Yes, happy to. And at the last -- in the prior 3-year cycle, we had a margin target, at least for, I think, 2 of those 3 years, that was sort of agreed -- stated before the Investor Day. So we had a more aggressive expansion target in part to deliver on that. Now we think we've delivered -- we think we have demonstrated that we can be efficient growers. And so we're going to take the opportunity to invest in the business. It is primarily on projects like the Core Lines Reimagine, AI tooling for our -- for the full employee base as that continues to expand, could be a cost there, something we're investing in and we'll get efficiencies out of as well. And then I mentioned the sales force and expanding coverage, that could be an area that we might invest more.

Got it. Got it. And then just to wrap up here, if we were to be back sitting here 12 months from now and discussing what a successful year it was for Verisk, what would be the top 3 things you would point to that you would have achieved throughout 2026 that would make it successful?

Yes. I think, two or three things. One is we would like to see the adoption curve for AI in the insurance industry continue to expand and for us to be active participants in that and to drive growth from some of our new and AI-enabled products. I think that's probably first and foremost.

Obviously, we are not going to control the weather, but we do think from a transactional and environment standpoint, we could start to see more normalization of that growth. And then finally, on our -- in our catastrophe and risk solutions business, we have a major product launch midyear. And so we're excited to bring Synergy Studio to market and have the client receptivity of the real enhanced capabilities of that tool.

Got it. Well, Elizabeth, thank you very much. I think we'll call it there. We will have PayPal CFO coming up in about 5 minutes. Thank you very much.

Thank you so much, Scott. I appreciate it, thank you, all.

Good morning, everyone. It is so nice to see so many familiar faces in the audience, but for those of you that I don't know and are new here to Verisk I'm Stacey Brodbar, I'm Verisk's SVP of Finance and Investor Relations. So let me be the first to welcome you to our 2026 Investor Day. We are so excited to be here to gather together here in beautiful Jersey City. We're going to discuss our strategic priorities, our competitive positioning, and we'll detail for you how we are going to deliver durable compounding growth and strong shareholder returns over the next 3 years.

Before we begin, let me take this opportunity to direct [indiscernible] the slide on the screen and remind you that some statements made in today's presentation may include forward-looking statements about Verisk's future performance, including those related to our 3-year financial targets and our guidance. Actual performance could differ materially from what is suggested by our comments today. Information about the factors that could affect future performance is contained in our recent SEC filings.

With that, we have a full agenda for you today. We'll begin with a President and CEO, Lee Shavel, who will provide a strategic overview for our business. Then 3 of our key division leaders will offer details on their strategies to drive growth. We will then feature a panel discussion focused on how we are driving growth and supporting our clients by building out our ecosystem businesses. And finally, Elizabeth Mann will wrap it up with her financial review, including our financial target for the next 3 years. Based on your feedback, we will have dedicated lots and lots of time for your questions, so please don't be shy.

And with that, let me turn the stage over to Verisk's President and CEO, Lee Shavel.

[Presentation]

Good morning, everyone. It's really great to have you here. I appreciate you making time to be with us. There are, obviously, a lot of issues. The market has been sorting through. I'm very excited and we're collectively very excited to share with you the opportunity that we see ahead of us and how we're positioned for us. for it. I'm sure there's a lot on your mind. So we have a lot to cover today, so we're going to jump right into it. When we were together and many in the room were with us in this hotel 3 years ago, we outlined a vision for a Verisk that was wholly focused on the insurance industry, that was going to be working to elevate the strategic relationships that we have in the insurance industry that we were going to be integrating more of our data sets to serve comprehensively the needs of our client base. And we outlined financial goals in revenue growth and margin and overall financial performance. that I am very proud of this team in terms of what they have accomplished.

We have met or exceeded the revenue growth and the margin targets that we set at that time. Elizabeth will go into more detail, but I'm even more excited about the progress that we've made in elevating the dialogue with our clients and our ability to integrate data sets across our business and improve the core that we started with 3 years ago. And that's going to be a lot of the focus that you're going to hear today. And you're going to hear it not just for me. You're going to hear it from my colleagues in terms of the businesses that they operate. You're going to hear it from our clients importantly. And we know their word is worth 10x what we're able to say about the value that we're delivering to them and to the industry. And you're also going to be able, in our solutions gallery, to test and see and ask questions in the specific products and how we are innovating, how are we integrating the new technology.

And all of this will make very clear to you how we have strengthened the core foundation, the data sets and the platforms that are critical to the industry, how we have developed new sources of growth through innovation, through investing in and enhancing and integrating new technologies into our products, how we have elevated the dialogue with our clients and what that has translated into in terms of new opportunities and a greater ability to connect those relationships and how all of that has translated into the compounding growth and the improving margins that are the core of our value proposition.

So over my presentation, I'm going to talk about how we've strengthened that core, how we've grown the marketplace, how our competitive advantages will position us for that further growth and then underscore the ongoing strength of our financial model. I think all of you are familiar with the basic outlines of our business, focusing on the insurance industry with high penetration within that business, the strong recurring revenue, but what's important to understand is that this base gives us a massive embedded client base that we can deploy our data and our technology against so that we can deliver value to them much more quickly and much more efficiently than if they were to do it themselves and an ability to do that with breadth that no competitor is able to match and with data sets that are incomparable and irreplaceable to the industry. We sit at the center of a broad industry with a wide variety of risks, a wide variety of functions. And behind each of those risks or functionalities are very specific products, data sets, analytics that are embedded into specific workflows that are critical to the functioning of the insurance industry, and critical not just for our individual clients, but critical in terms of the necessary interaction between multiple constituents and critical in terms of their regulatory relevance to the industry. And behind each of those products are data sets that are unique and incomparable that underpin over 90% of our revenue. They consist of contributory data like the broad loss costs that we receive from the industry to help them calibrate their underwriting functions. The claims data that support our antifraud solution that saves the industry billions of dollars by their estimate in terms of fraud costs that are unique, historically deep and with tremendous detail that's necessary for the work that they do.

It also consists of proprietary data, data that we gather through our field survey forces, evaluating every fire department in the country so that insurers can know what is the quality, what is the response time, what is the level of training to assess their risk and fires, which is critical. Information that we gather on commercial properties like this building and virtually every other commercial building in the United States that allows insurers to understand very specific detailed data that's relevant to their underwriting, and we can source that data much more efficiently as one company acting on behalf of the industry than they could individually. And off of this contributory and proprietary data, we add proprietary intellectual property like our catastrophe modeling, which builds off a very detailed risk accumulation data, property cost data and repair data, claims information, underwriting standards, all of which support the value of that proprietary intellectual property that we have in weather, in construction, in claims and in underwriting. And software networks that we've invested in to deliver those data sets and those analytics and connect the industry.

So that's the foundation, and we have invested intensely in each of these data sets. They're not static. They're not what they were. And one of the benefits of moving to a purely insurance focus is that we've been able to dedicate more of the capital that we generate to investing in and strengthening those data sets, which will become even more important in this much more AI-driven world. We've improved the frequency with which we can take those data sets on the contributory side and provide more frequent updates more insights from that data that has been enhanced by AI and our analytics. We've allowed our customers to be able to access that data more easily, to query it more effectively and we've accelerated our ability and the breadth of the data sets that we can collect on the proprietary side. And we've also applied AI to improve our proprietary intellectual property by investing -- by testing our models more quickly and more actively. So these data sets are at the core. They will remain critical. You've heard it not just from us, but you'll also hear it from our clients, and you'll hear it even from the AI companies that have recognized the importance of good quality data for the importance of the effectiveness of this new technology across the industry.

So with the strength in core, let me move to the growing marketplace [indiscernible] supports our opportunity and the competitive advantages that we bring to bear in pursuing that opportunity. So the U.S. property and casualty insurance industry, our most important market, is projected to grow at a very solid mid-single digits, 5% growth rate, and that's higher than the historical rate of 4.3%. And the reason it's higher is that we are seeing increased severity in a number of areas and across various insurance product lines. And we're also seeing above-average growth in new markets like excess and surplus, which has been an important opportunity for us to gather new data sets and reference existing admitted lines data sets that are guiding the excess and surplus [indiscernible].

Now from that base industry level, our ability to grow at a higher rate has historically and will continue to be driven by ongoing increases in the demand for data and analytics from multiple sources. We see increased demand from carriers for more data to support more efficient automation of their core functions on underwriting [Audio Gap] claims risk management. We clearly see increased demand for data to support AI applications and particularly data that is broad across the industry and detailed in terms of level of costs, underwriting aspects, regulatory complexity, all of which are going to be relevant in how AI can make the insurance industry better. We're seeing growth in demand for data from market sectors, increasing growth in demand in the intermediary space, including brokers, agents, MGAs [indiscernible] creating a new source of demand that we're satisfying for data and technology. Growth in the excess and surplus in the specialty markets, as I've described, is also creating new opportunities for us to gather data sets and leverage the data sets that we have to meet their needs.

And finally, there are key macro trends that we are seeing demand for information from regulators and from our carriers on affordability, climate risk and social inflation. So all of these are contributing to a market environment where we have the unique ability to pull these data sets together efficiently and ensure the quality and the trust that the industry seeks and using them. And to pursue that opportunity, we have several distinct competitive advantages. I'm going to talk briefly about each of them.

The first differentiator is simply the quality of the data that we have built, that we have invested in improving. It is at the core of critical functions of underwriting and claims and risk management. It's used broadly by the industry. And because of that, it becomes an industry standard that our clients rely on to benchmark their own performance. It also becomes a basis for communication between multiple constituencies between carriers and reinsurers and contractors and adjusters and regulators that support the overall activity. And it's that regulatory aspect that I think is important to understand. The regulators want to make certain that the underwriting and the claims decisions that are being made are supported by reliable data, and it needs to be auditable. It needs to be transparent. It needs to be standardized. And that's an incredibly important role that we play for that constituency, and it's not an easy constituency to satisfy because we still operate in a state-based regulatory environment, and these regulations are changing across those states [indiscernible] and frequently with different issues and a lot of what we do is staying on top of what's happening from a regulatory perspective.

And finally, the unmatched [indiscernible] breadth of the data and the level of trust that we have in the industry is a unique advantage for us to be able to continue to expand and develop those data sets.

Now let me turn to the second differentiator, which builds on the quality of the data. And that's our ability to draw information, particularly current information and integrate it with our scale, with our technological capability, with our industry knowledge to be able to deliver real tangible functional benefits to the industry. We're able to utilize this data from across this industry [indiscernible] to improve underwriting speed, to get pricing uplift on the underwriting side, to improve claims estimates, to accelerate the settlement of claims, which saves insurers monies. We're able to build new catastrophe models, broader models, more frequently updated models. We can improve compliance cost and compliance speed, and we're now improving the distribution, the distribution effectiveness for brokers and agents within the business. So it's a tremendous breadth that allows us with our industry knowledge to apply it to real economic advantage for the industry

Now adding to that is our third differentiator, which is our unique ability. No one else has this capability to take AI and deploy it internally, where we're utilizing it to improve our knowledge, our insights [indiscernible] experts that we can deliver to our clients to improve the quality of our products, the efficiency and the productivity of what we are doing, not just in coding, but in the aggregation and the normalization of the data sets that we are gathering, our ability to query and gather insights that we can deliver to the industry.

Secondly, to enhance our existing products where there is already an existing revenue [indiscernible] relationship. And by integrating the data -- AI into those products we're enhancing the value of those, and I encourage all of you to spend time and ask questions in our solutions gallery. You'll see in each of those how we are utilizing AI to make those products more valuable, more usable and expanding their capabilities.

And then finally, an important dimension of this is that we've been directly engaged as a result of our elevated strategic dialogue with our clients around how we are matching our investments, our data sets to meet the very specific needs that our clients have for their AI strategy. We've already had multiple meetings with our largest clients. I just got a call 2 weeks ago with a client who wanted to talk about their data architecture and how we can integrate our data sets into that architecture to support their AI strategy. That's a true partnership where we're finding ways to deliver the data in a safe, protected way and allowing them to achieve their objectives from an AI standpoint. And all of this has been not just with dialogue with our clients. But with dialogue with other partners like the AI companies, whose large language models we're utilizing that we are brainstorming around how we can apply that technology to our data sets as well as with consultants that are working with our clients to understand how they adapt. And many of them are coming to us and saying, "Look, there is an opportunity for us to work with you to figure out how to utilize these data sets more broadly."

And I want to expand on that because from our perspective and from our experience, AI is not only leveraging the unique advantages that we have, but it's also reinforcing them. You've probably heard a variety of constituents say, without good quality data, AI is not effective. It needs that data. We have unique and valuable and critical data that supports this application. Now we need to protect that industry, not just from Verisk's perspective, but also from the perspective of our clients who contribute to it. But if we can deliver that in a way that adds value, it reinforces the value. It expands the value of that data set, and it encourages more contribution of that data.

The other advantage that it leverages and we benefit from is the ability to integrate those data sets into established workflows. The industry operates in a heavily regulatorily-driven environment. It also exists in a highly cooperative environment. And those established workflows are the means by which this can be integrated in an effective regulatory environment. And so our ability to tie AI into those workflows where we're embedded from a data standpoint is another unique advantage that no one else can provide at the breadth that we're able to deliver. And we're able to leverage the scale and the network that we've established across these various functionalities, which in turn adds value and reinforces the value of those existing networks. So we believe very clearly, and you'll hear today how AI and other new technologies reinforce and require the strengths that we have to offer to the industry as a whole.

And so finally, to turn to the final differentiator. All of this is something that we can deliver at a compelling cost advantage to the industry. We've talked about this before, and it's been a very positive trend. But our total revenues as a percentage of the U.S. net written premium is less than 1/3 of 1%. And if you take that revenue and take it across industry expenditures, it's slightly over 1/3 of a percentage. Now if you think about all of the data sets, all of the modeling, all of the analytics, that's an extraordinarily low cost relative to the overall cost of the industry. And we certainly believe and we believe our clients recognize that there is tremendous economic value to them of this relationship. And it's something that they can continue to leverage going forward. And in fact, we've seen a very clear trend as you see on this page that we've been able to increase that percentage of revenues and of net written premium by about 20% from 2015. And that's a sign of the increasing demand for data and its integration into the overall system. And that's on top of the historic base rate of growth in net written premium, and we'll continue to support our ability to grow at a faster growth rate.

So let me turn finally to our strategy to drive client and shareholder value. There are 3 clear pillars drive compounding growth from multiple sources and I'll talk about each of those, continue to deliver margin expansion from a variety of dimensions and deliver great returns through our balanced and disciplined capital allocation strategy. On the first front, A primary contributor to our ongoing revenue growth has been the elevated strategic dialogue that I spoke about as an ambition 3 years ago. And I'll have to tell you our progress in this area has exceeded my expectations. And it's been a function of the extraordinary receptivity that we've had to that dialogue. We've had clients saying, we've wanted to have a more strategic dialogue. We're dealing with issues at a business level that we think it's important for Verisk to integrate these data sets and provide more. And my team has been absolutely phenomenal in throwing themselves into broad discussions where we view our entire relationship and understand how we can better align our existing products and data sets to what our clients' needs are. as well as aligning our investments to where our clients see the greatest need. And beyond that talk, it's translated into a clear improvement in the overall revenue growth rate from our largest clients. You can see that our top 25 revenue growth rate over the past 3 years has accelerated from where it had been the prior 3 years.

Now in addition to us being able to better articulate the value of our products and how they can deliver strategic value. We've also been able to explain how they can get value from increased data contributions and how they can get more value out of the relationship. And that's translated into an increase of over 100 data sets over the past year that have been added to our capabilities and our data portfolio. So all of this is demonstrating the value of how that strategic dialogue has opened up new aspects of growth for us. Selling our products more effectively from a value standpoint, designing new products to meet their specific needs and investing in areas that we know our clients are going to value. Now another way to look at this and we know has been -- and a demonstration, which we know has been popular for our investors and our analysts in past Investor Days is looking at the number of products that we are selling our clients at multiple scale levels. And you can see on this slide that whether it's the top 10, the top 25, the top 100 or the top 500, we've been able to increase the number of products and importantly, increase the pace of the number of products that we are delivering to each of these constituencies. And it's been a function of our ability to better communicate the value, better understand their needs and also importantly, to innovate on the basis of what they are looking for and where the industry is headed, so that we can create new products in a variety of ways.

That brings me to the second growth pillar, which is the requirement of our constant innovation at scale. And on this slide, you can see our plan over 2025 and over the next 3 years of our largest innovation initiatives. This, by no means, are the only innovations that we are delivering, but they are the ones at scale at that have relevance to the industry. And you see innovations in core lines that you'll hear Saurabh talk about. Our core lines reimagine initiative, the ability to add analytical objects leveraging data sets from across our businesses in the auto suite, the ability to add regulatory capabilities on life. You'll see innovations and claims that you'll hear Stephen talk about in terms of our exact suite upgrade and platform improvement, the broadening ecosystem in anti-fraud and new products that we're developing and new innovations within our catastrophe modeling business. And in every one of these on this page, you will see AI embedded to support the solutions that we're providing to our clients and provide new dimensions of value to them and growth for us.

Now I realize to a noninsurance specialist that it's hard to appreciate the innovation that we bring to this industry. It's complex, it's diverse. But there is one metric that we use to understand how our clients feel about it. And our clients clearly view us as innovative in what we're doing across our product set. After every conference, in a survey on the effectiveness of the event, we ask them what word best describes Verisk. And at our most recent ELEVATE conference in Salt Lake City, which brought together not just carriers, but contractors and adjusters, this was the result. By far, our clients view us as an innovator within their businesses that is delivering value for them. Now there's a lot of other good stuff on this page. I love partner as being a prominent theme. Certainly, essential speaks to the criticality of what we are doing. Connected means an awful lot to me because they recognize how we are helping connect the overall industry. But this is a great demonstration. And if you were to look at not just ELEVATE, but also our Verisk Insurance Conference, you'll see very similar themes.

So turning to the third opportunity and kind of building off of that connected theme. Over the last 3 years, one theme that I have emphasized, and we talked about it at Investor Day, if you go back to the presentation, is moving from being that technology partner to being more of a network company. We have been building networks across multiple ecosystems, which has created a new dimension for us to deliver value to our clients and to gather new data sets that are relevant for their purposes and to capture other value that participants within those networks are able to provide. You'll hear Tim Rayner talk about what we've been doing within white space. You'll hear about from Aaron Brunko on how we've been better connecting the claims and restoration ecosystem. And you'll hear from Rob with our Synergy Studio platform and open model platform, how we are expanding the connectivity and the value we deliver through that function.

Now the white space platform will be a great example of the growth potential and how we've taken a great technology and been able to accelerate it because of the breadth of our relationships and our credibility with our scale and capital as a partner. This business in terms of risk place has grown tenfold over the last 5 years. We now have 385 firms trading on the platform and 16,000 active users. And it represented in 2025, over $15 billion of net written premium that was placed on the platform, and that's 30% to 40% of the Lloyd's specialty market with room to grow, and we are expanding, as you'll hear later today into Dubai and Singapore. But I'd like you to hear the perspective from a very important client, Dominic Samengo-Turner, who is the Head of Marsh's Specialty business. So in other words, anything that runs through Lloyd's goes through Dominic's business.

[Presentation]

So that's certainly is a tremendous endorsement. And while AI is incredibly powerful, and we're excited about the opportunity, one thing that it can't do is get complex constituencies to agree in terms of how they're going to work together there. And that's something that we have been doing for decades and is a great opportunity for us going forward. So I'll move to conclusion. In addition to that growth, you're going to hear Elizabeth talk about how we will continue to drive margin expansion through multiple sources. Our operating leverage from scale, investments that we're making with technology, including AI, to drive efficiency and productivity gains and good old-fashioned cost discipline. And you'll also hear Elizabeth talk about how our capital allocation strategy will remain balanced and disciplined. Over the past 5 years, we've generated about $10 billion of capital and invested about 15% of that inorganic growth with very attractive double-digit returns. We've made acquisitions for insurance, bolt-on acquisitions, for about 10% of that amount where we've been able to leverage our scale and rapidly penetrate the industry with these new products. You'll hear about several of those that we've been able to generate. And then, I'm sorry, 3/4 of that capital, we've returned to shareholders through increasing dividends and share repurchases, all with a very strong balance sheet that benefits from the consistent and strong EBITDA growth that supports our capital generation.

So the financial model is simple, but it's economically powerful. It consists of strong recurring revenue growth from multiple sources in a growing market where we have distinct competitive advantages. Our ability to drive margin improvement, which supports even stronger EBITDA growth, double-digit EPS and very attractive returns on capital from a wide portfolio of investment opportunities within our business and within the industry, as you'll see demonstrated in our solutions gallery. And so I'll return to the primary themes that I started with.

We have a phenomenal foundation that we have strengthened by more focused investment in our data sets and the expansion of those data sets in the platforms that tie the industry together. And with that platform and with the differentiation that we have in terms of the quality of our data, the trust that we've built and enhanced with our clients and our ongoing innovation drive, we have the ability to continue to deliver substantial value with ongoing attractive revenue growth, margin expansion and very strong returns on capital.

And so with that, I will turn it over to my colleagues, starting with Saurabh Khemka, the President of our Underwriting Solutions, and I will very much look forward to being together with you again during our Q&A session. So thank you very much.

Thank you, Lee, and good morning, everyone. My name is Saurabh Khemka. And at Verisk, I have the pleasure of leading our Underwriting Solutions business. I've been with Verisk for 12 years. And prior to that, I was at Bain & Company. This morning, I'm excited to share with you the progress we have made in scaling our underwriting business and our growth drivers for the future.

So let's get started, and let's start with an overview of the underwriting business. On your left, you will see that we are a $1.7 billion business, operating in 4 primary segments: One, the ISO forms rules and loss cost business; second, the underwriting data analytics business and then the life business and our international business. And each of these businesses is anchored by differentiated and proprietary technology and data assets. So for example, the 39 billion records that you see here, these are actual premium and loss transactions that we gather from hundreds of clients to create what we call our loss costs. And those loss costs are used by our clients as a critical input into their rating and pricing decisions. And there's examples like this across our businesses.

So let's look at how we've done in the past. Over the last 5 years, we've had steady and predictable growth. And if you look at the composition of our business, we are a high recurring revenue business with very strong client retention rates. In fact, over the last 3 years, we've accelerated our growth. And more importantly, as Lee mentioned, we've done that through innovation across our businesses, whether it's modernizing our core offering, expanding the data depth and market reach of our proprietary technologies, or penetrating the life and annuities market. Just as an example, in our underwriting data business, in the last 3 years, we've added 20 million new personal and commercial property records. And we've also expanded our proprietary LightSpeed technology to new customers, new lines of businesses and new geographies. So where do we go from here? Well, let's start with the underlying market. We have significant headroom to grow in the market that we serve. As you can see, we only have about 19% share of the market. And historically, we've been able to outgrow that market by 200 to 300 basis points by innovating to meet our customers' needs. And that underlying market, as we look at the future is strong, it's resilient, but the complexity is increasing. And we believe that we are uniquely positioned with our proprietary data, our expertise and our investments like the ones we're making in to help our clients meet their objective, which is profitable growth.

Now let me take a moment to talk about our proprietary data assets. And why in the world of AI, we continue to have a structurally differentiated offering. So I'm going to bring you back to those 39 billion records that I talked about. Well, these are actual premium and loss transactions that we get from hundreds of clients from their admin system from their claims systems, sometimes multiple systems at one client and we bring it all together and standardize [indiscernible] to create a loss cost. And what is standardization? So I'm going to give you a simple example. So we're sitting here in this building, the Hyatt hotel. Let's for a second, assume that over the last 5 years, this hotel was insured by 3 different insurers, okay? So the first insurer insured this hotel and classified it as a full-service hotel, makes sense. They offered a $500,000 deductible on their policy with certain limits on the payout and endorsements and coverages. The second insurer called it a hotel with a conference center, still makes sense. They had a higher deductible, different limits, different endorsements. And a third insurer classified it as a mixed-use hospitality with a much higher deductible, different limits. Now we bring all of these together and map it to our proprietary classification code, [indiscernible] map it to a standard base deductible base limits and this is all the constructs of our filed ISO program. And this is how we create what we call our industry standard loss cost. So quite honestly, after that, the fourth insurer can use it. And imagine doing this across 32 lines of business and hundreds of classifications within those lines of business. That is standardization. And we're not done yet. So we standardized. We created the loss cost. Well, then we go out and file those loss costs with regulators. As Lee mentioned, credibility, how much data do you have? What's behind these loss costs is very important in those discussions. So we file these and then our clients use it. And typically, they will coat it into their workloads.

This is what we call proprietary regulatory-grade embedded analytics. And this is why in the world of AI, our differentiation continues. So I talked about the market need. How are we going to meet it. We have 3 growth drivers that we're going to focus on, and I'll walk you through each one of them. So let's start with the first one. We have seen and we've proven that when we invest in our core assets, like our forms [indiscernible] and loss cost business like our commercial property business, we create more value for our clients and we can participate in that value. Let's take an example. We've talked to you about our core line Imagine program. It is our biggest investment in this product, and it has fundamentally transformed this product from one that was driven by a point-in-time analytic delivered over PDFs in a user experience that was dated and quite frankly, where there was a value perception gap at our clients, especially within the executives, to one, which is now driven by continuous innovation and insights backed by much more data delivered through a digital platform and where the perception has changed to, it's a premium product, but you're highly innovative.

And let me give you just a tangible example of the new value that we've been creating. And I'll stick with loss cost. You guys are all going to be really schooled in loss cost by the end of this. But put yourself in the seat of a product manager at one of the insurance companies who manages the homeowners insurance line of business in the State of New Jersey. Historically, we would have provided our annual loss costs to this product manager. So let's say that we provided that in December of 2025. Very important analytic and input into their pricing decisions. The next time we would provide this would be a year from December 2025. Now with reimagine, between that 12-month period, every 6 months, we're providing this product manager, executive insights, and ability to benchmark their book relative to the market across dimensions that's not available anywhere else.

Every quarter, we're providing the experience index which creates and tracks the trends in losses and experience over the 12-month period so that they can make pricing actions according to their time line. And every 2 months, our SMEs are looking at our proprietary market database and finding trends in segments that our clients cannot see. And in fact, the loss costs that we provided at the end of this 12 month is also in a totally new format, which you can see in our solutions gallery. So you can see a lot more value. And just to put this in context, we've talked about 35 new customer modules that we have provided to our clients to reimagine. These are 3. So how does that now translate to the conversations we are having with our clients.

This is an actual example of a top 20 client where that value perception gap was real. Taking Lee's lead, we elevated the engagement. We shared all the innovations. We shared our reimagine road map. And what you see is a perception difference where their understanding that we're providing a differentiated asset, differentiated insight that creates a lot of value for them. And yes, we are participating in that value creation. And what reimagine has really done is that not just a foundation from a platform perspective, it has really changed the culture of that product to one of continuous innovation. And we have a strong pipeline of new innovations that we can bring to market on this platform and continue to create new value for our customers as we move forward.

So let me now go to the second growth driver, which is focusing on differentiated analytics and technologies. And I'll use 3 examples to share here. Let's first start with aerial intelligence. Aerial images have become a critical part of property under riding. And we're investing behind it, but we're doing it differently. We realize that the coverage, so how many homes you have an aerial image on and the refresh rate, so how often you update that image is a critical differentiator. So we're taking a multimodal approach to make sure we have the broadest coverage and the best refresh rate in the industry. We're also incorporating aerial image into multiple existing products and enhancing the value that they drive. We're also connecting our various data sets with aerial imagery to create new analytics like wind and hail and useful life, which create extra segmentation power. This is resonating. Just last year, we signed 14 new customers on our products enhanced by aerial image.

Now let's move to auto. If you go out [indiscernible] today, to shop for an auto insurance quote. Prior coverage, so what coverage you currently have, is an important [Technical Difficulty] input into that process. And we compete in that market. But the use of that input hasn't really changed. We're changing it. We are looking at the 7 years of longitudinal policy history that we have to see if there are patterns in how a policyholder engages with their policy over that time period. What changes do they make? When do they make it? How many times do they make it? And we try to see if that could be indicative of their risk level. And we actually found 40 such patterns, we call it objects, that are predictive. And in fact, some of them identify risks that are 2 to 3x higher from a loss perspective, pretty significant. We are providing this differentiated analytics through our LightSpeed product, and we are sharing this with all our clients, and it's resonating. In fact, late last year, this was a critical reason why we won a competitive bid in the LightSpeed auto space.

Now let's talk about Advanced Technologies and specifically AI. As Lee mentioned, AI is now pervasive in all we do in underwriting. With guidance from our AI governance board, we are rethinking how we create products so that we can be the most efficient and effective. But beyond that, we're incorporating AI into our product strategy. First, we are enhancing our clients' experience of these proprietary data sets we have by adding an AI experience layer. And what we see is when we do that, there's more engagement from our clients, like in the case of our POS AI, which is the premium audit solution or there's more purchase intent as it's in the case with our [indiscernible] product. We're also finding opportunities to create new analytics and capabilities around our data and technology assets using native AI. So whether it's underwriting assistance, which sits on top of our commercial property database or our S-Max and Telemax capability that sit on top of our fast platform. And you can see both of these in the solutions gallery.

And then finally, we believe that this technology provides us an opportunity to serve our clients totally differently, whether it be through Agenetic or technologies like MCP. We're looking at opportunities to serve our clients so that they can be more efficient and use our products more effectively.

Let me now go to the third growth driver, which is our life business. Just as background, 6 years ago, we thought that the life insurance industry was ready for modernization and digitization. And we spotted an emerging differentiated platform in fast. Fast, low-code and no-code architecture creates significant value for clients, whether it's faster time to market or much lower operating cost. And as you can see, we've been able to more than triple this business over the last 6 years. And we've done so through continuous innovation and a client orientation. And we continue to see opportunities in this business, whether it be adding AI capabilities or moving into new segments like distribution, group, pension risk transfer. So as we bring all of these 3 growth drivers together, we can compound on that accelerated growth that I talked about, and continue to grow at a 6.5% to 7% growth rate going forward.

Now you've heard me talk about the value we bring to clients and what we offer. But let me now share with you what's most important, a voice from one of our key clients.

[Presentation]

Thank you, Dave. And just one topic here that Dave mentioned in situations like wildfire risk, Verisk is going to market and helping our clients with all our might, not just underwriting, but as you heard Dave say, our cat modeling business, our claims business all of those together to help our clients.

So let me summarize. We've delivered on our objectives in the past. Our underlying markets are resilient and growing. We are uniquely positioned to help our customers, and we have multiple growth drivers to support our growth objectives in the future. I thank you for your time. I look forward to any questions you have later on.

And with that, I'll pass it over to Rob Newbold.

all right. Thanks, S.K. Good morning, everyone. My name is Rob Newbold, President of Catastrophe and Risk Solutions. It's my 24th year with Verisk, all of which have been in the catastrophe modeling business. I joined as an entry-level analyst and have had the opportunity to build and lead global teams focused on client service, cap on analytics, sales, marketing, IT and operations. But by far and away, my greatest privilege is leading this organization doing the really cool and important stuff we'll talk about over the next 17 minutes or so.

We'll follow a familiar agenda. We'll talk about the business and what we've been up to since the last Investor Day. We'll turn to the markets in which we operate and the value our solutions provide and we'll close by talking about growth. So if S.K. made all of you experts in loss costs, my ambition is to make all of you experts in catastrophe modeling before we leave this room today. And if I could draw your attention to the circle on the right, the catastrophe and risk solutions business is built around the foundational principles of responsible scientific rigor, technological innovation and client-first client-focused, collaborative transparency that results in a global suite of natural apparel property catastrophe models that are so much more than just predicting the weather. These are translating current weather information of today into forward-looking projections of loss potential for property-specific catastrophes that have not happened, but plausibly could. We've also just released the [indiscernible] first probabilistic liability, catastrophe model, and we also have a global suite of external business risk and disease for things like political violence, social unrest and environmental factors that are delivered geospatially, which our clients tell us is valuable because it's so much more than just a risk number, you can visualize on the map, aggregations and accumulations. At a macro level, fundamentally, we are a business about assessing risk and in a world that's increasingly uncertain socioeconomically and climatologically, we have the tools that will help our clients manage this uncertainty and grow profitably into the future. [Technical Difficulty] A couple of slides by the numbers. The catastrophe and Risk Solutions business is roughly $400 million and comes predominantly from insurers, reinsurers and brokers. We report it as part of the underwriting subsegment. And on the right-hand side, you can see our more than 135 PhDs work together to create these global suite of risk indices and property catastrophe models for more than 120 countries around the world. Now because the risk we model is global, so too is our revenue, with more than 45% of our revenues coming from outside the United States.

Now it's going to become redundant, but I'm going to say many times throughout the presentation how proud I am and how excited I am. And the first time is right here. I'm incredibly proud of the fact we've delivered 9.4% compound annual growth since 2021. And our revenue is 90% subscription-based and characterized by a very high degree of client retention at over 98%. And I'm also, again, very proud of the fact that we are the benchmark for the global catastrophe bond market, being selected as the model of choice for more than 70% of the global securitized risk transfer space.

I'm going to spend just a minute on what we've been up to since the last Investor Day because it's foundational to the growth initiatives I'll talk about later in the presentation. Now starting from the left, it may feel like a technical detail, but we're the only catastrophe modeling company in the world who can do a global loss analysis on a completely rearchitected high-precision next-generation loss modeling framework in one single analysis. And our clients tell us this is important because not only do they get that high precision model output, but doing it in one run is something they can't get anywhere else in the market.

Number Two, as Lee mentioned, we continue to update and expand our global risk modeling suite. There are too many new and updated models to list them all, but a few examples. We've added new flood models for Indonesia and Malaysia, which include projections of future climate and maybe closer to home, we've recently updated our U.S. severe thunder store model and an update to our U.S. wildfire model that came to market in advance of the tragic events of Eaton and Palisades that occurred in January of 2025. We have built the foundations of a cloud-native AI-ready SaaS platform, already able to natively compute billions of loss calculations in the cloud and at scale. And we've taken deliberate actions to create the industry's first and only global open catastrophe modeling ecosystem, reinforcing our centrality in this market. And again, I'm incredibly proud of the fact that we've done all of this while continuing to deliver high single-digit growth and putting ourselves in a position to execute on Verisk Synergy Studio and other future growth initiatives.

Now before I leave this first segment, let's spend just a minute talking about AI and the impact on the catastrophe modeling space. Now catastrophe models as a genre exist to solve something of a small data problem actually. And the catastrophes are large, yes, but they're thankfully infrequent. And importantly, there's a huge difference between what's happening with the weather at an atmospheric level to what that means for a given shingle, at a given house, in a given location for a given event. Now we are already using AI to downscale global atmospheric data to local hazard level information and augmenting it with the scientific expertise of our PhDs across meteorology, seismology, hydrology, climatology, statistics and structural engineering to translate that local hazard information to future projections of catastrophe loss potential for a given property.

Now it won't surprise you that the cat modeling workflow is also ripe with opportunities for operational efficiency and things historically done via API or via automation can be reimagined using Agentic AI solutions, and we are natively building those into Veracity Studio as we bring that platform to market. Quite simply, AI is not a replacement for the value we provide, but an accelerator to allow us to provide it to our clients more efficiently.

All right. So let's now turn and talk about the market. Unfortunately, the world is not becoming any less catastrophe exposed. In fact, we would model the global average annual loss from catastrophes in excess of $150 billion and growing, driven by the 4 factors you see outlined here on this slide. Again, starting from the left, there's quite simply more stuff in the way. We continue to build more properties, inflation makes them more expensive to replace, and it seems to be human nature to put things directly in harm's way. People like to have their homes on the coast. People like to build up next to the wildland urban interface. And when you add to that rapid urban expansion, you all of a sudden get an aggregation risk such that a hurricane or a hail event in downtown Dallas is far more impactful in 2026 than it would have been in 2016 or even 2021.

Third, the nature of these events is changing. It is still, of course, about hurricanes and earthquakes, but so-called frequency perils, which we would label as severe thunderstorms, winter storms, wildfires and floods now account for nearly $100 of that $150 billion in global average annual loss. And underlying all of this is the specter of a change in climate, which we have a responsibility to help our clients understand how what they're experiencing is not an outlier, but in fact, a new normal under which they must manage their business operations.

One more look at increasing cat loss. On the left-hand side, you can see the 5-year average outpacing the 10-year average, indicating an acceleration of global cat experience. And importantly, when you look at the pie chart on the right, Verisk has models in market today to address these risks for all of these payrolls globally, adding value to our current client workflows. One more view of the market on the left, you can see we have roughly a 12% share of a $3 billion market growing at mid-single digits. What gives me optimism as I look at that chart is we have tremendous runway to grow and add value within the market in which we operate. And the second view on the right, you can see Aon's current assessment of global reinsurer capital at $760 billion, which incidentally is the highest that number has ever been, and it's an important benchmark for cat modeling because models are the currency by which reinsurance risk is transferred, indicating utility and need for our solutions.

So if I could try to wrap all this together into one summation of why the cat business is insulated from disruption. We have a unique and proprietary data advantage via the information on property exposure and loss validation information we can use together with complex science to put together cat models that add value to our clients' workflows. We are the industry benchmark for the catastrophe bond [Technical Difficulty] on market at over 70% market share, and we're deeply integrated into our client workflows, creating high switching costs and high barriers to entry for possible disruption. And as one example of the value we provide to the market and the way we partner with our clients. Let's here from Frank Fischer, Chief Analytics Officer of Elis Capital.

[Presentation]

Let's transition and close our discussion by looking at our future growth. So within catastrophe and risk solutions, we have 3 initiatives that will drive our next phase of growth. a technology transformation to Verisk unity Studio, activation of various data assets for better risk analytics and extension of our analytics into adjacent markets.

I'm incredibly excited about the transition to Verisk Synergy Studio because it's so much more than just a software transition. It is, in fact, a platform transformation to the manner in which catastrophe modeling will be done for years to come. Now this platform is a SaaS application. It's built on AWS. It's in client preview right now and plan for market production release of June of this year, and it delivers these 4 value propositions and so much more than this. But as some quick examples, faster delivery of updated models is critical for this segment because we just spent time talking about the accelerating nature of catastrophe activity and the change in climate. And our clients are relying on us to provide that information patients to them as efficiently possible.

The thin deployment nature of the SaaS platform allows us to get to adjacent markets, and we'll talk about that in more detail as our third growth driver. There's a ton of information required to do catastrophe modeling from location level hazard data to property information to hundreds of thousands of simulations. A SaaS platform allows us to do that far more efficiently than ever possible before. And it also opens up the door for us to integrate various data assets, which we'll talk about as our second growth driver.

Now it also sets the baseline through which we can create this open catastrophe modeling ecosystem that Lee talked about and I mentioned earlier in my presentation. In addition to the value our clients get from our solutions, they're also telling us they want additional opportunities to fill gaps where we don't have a model or to put their own assumptions and validations into our models to customize their view of risk. So as one may be tactical example to bring this to life, we do not have in our suite currently a model for Middle Eastern flow. But should one of these 15 providers across their model suite have that model, our client can engage with them and operationalize that view of risk directly in synergy studio to, in one analysis, get a full global catastrophe modeling curve. This offers tremendous operational efficiency, again, that they can't get anywhere else in the market.

And because I haven't said it explicitly yet, this platform is fast. So the ability to do enterprise-wide aggregation in less than 3 hours, 90% performance improvement for complex commercial risks and sub-10 second policy level analysis means, fundamentally, our clients can spend more time understanding their risk, looking at output and making risk decisions rather than waiting for a machine to calculate loss numbers for them.

All right. Second, reimagining various data assets for better risk analytics. Again, taking a step back, a cat model requires 3 fundamental pieces of information to generate a loss estimate. Where is the risk? What's the risk made of and how much does it cost to replace it should something bad happen to it. And you can see in the box on the left, Verisk [indiscernible] proprietary data to answer all of these questions. And Synergy Studio gives us a platform where we can operationalize that data either at the point of sale or at a portfolio level for millions of risks to give our clients a better loss accuracy and clearer visibility into their loss patterns.

So again, one more example, maybe tying our sessions together, S.K. talked about investment in aerial imagery analytics. It won't surprise you that it's incredibly impactful, no pun intended to hail, to know the quality composition and age of the roof. We can capture that data via aerial imagery and put it directly into a cat modeling workflow to allow our clients to get a much more accurate view of their hail risk, and that's just one of many examples.

And last, while of course, we are focused on the global insurance and reinsurance markets, all of these corporations, financial institutions and investment managers have exposure to catastrophe risk. But the historical paradigm of the rather heavy client server application and large catastrophe modeling teams meant it was difficult to get information on cat risk into the hands of these stakeholders. A SaaS platform built on AWS reduces that friction and allows us to access new markets and new revenue streams by giving information to people that so badly needed and have not had it historically.

So to wrap all of this together, these key growth initiatives of transitioning to Synergy Studio, activating Verisk data and expanding to adjacent markets will allow us to continue to grow this business at high single digits over the next 3-year time horizon. So to summarize this discussion, I'm incredibly proud of where we have been and what we've done and even more excited for where we're going. We have market leadership in a critically important and fast-growing catastrophe segment. We already have our platform transition underway and in market via client preview, unlocking speed, scale and operational efficiency and we have clear line of sight into how to continue to grow the business via expansion to adjacent markets.

With that, I will conclude my session and invite Lee and S.K. back up for questions. Thanks.

I'm going to ask, we'll welcome your questions. And we'd just ask for you to wait until you get a microphone so that those on the broadcast, portal cast are able to listen.

Lee, I just had a question on, obviously, the data. So the 20% that you classified as proprietary cell source through in-person collection, can you just elaborate on some of the examples there and how comprehensive that is? And just a quick follow-up to that. You also had a chart showing the number of data contributors increasing, I guess, just some perspective on what the limit to that is? Like just what are the drivers of these incremental data contributors?

Sure. Excellent. Actually, I think a great opportunity to turn that over to S.K. Can speak specifically to those proprietary data sets that we gather.

Yes. So on the proprietary data set, I'll mention 2. One is our field force that goes out and looks at commercial properties like this to understand the risk, to understand the occupancy, the fire protection they have. And that's something that we do for buildings across the U.S., and we have a database of almost $16 million. Some of that is site verified as we've gone there and some of it is modeled. So that's one. The second that we've talked about is we work with communities thousands of communities to understand their building codes, their fire response so that we can understand and help our insurers figure out what is the risk if something bad happens [Technical Difficulty] house, how quickly can the fire department get to it, what are their capabilities. So those are 2 self-sourced proprietary data sets that we have.

I think your second question was about new contributors. As part of our reimagined program, we've gotten commitments from 100 new insurers to provide data to our contributor database. So we're very proud of that. That signals to us that when we can show the value that we provide to our clients, that they're willing to give us more and more data.

And Manav, if I can add something that I think is an important distinction about what makes what we do so defensible on the building code data sets that SK referred to, actually a terrible acronym B6. It's building code effectiveness grading survey. And what's important about it is it's not just the detail of what the building code is, but how effectively it's enforced within those jurisdictions. That is a judgment that we're able to make on the basis of actual survey and data that support that. That's one of those really nitty gritty elements that make it so defensible.

Lee, you were really incredible at showing us the different network effects of your data sets. -- and how AI will be even more impactful on the insurance industry by overlaying that on your data sets. My question is, is Verisk taking a closed architectural approach maybe like a Bloomberg or is this kind of AI in partnership with companies like Claude, like would you be part of Claude for financial services?

Our philosophy is to an open architecture, and that's a deliberate strategy that we have developed over the past 3 years. in a variety of areas that you'll hear my colleagues speak to in the panel that we're doing. So in each case, and you just heard Rob describe how we are opening up the modeling ecosystem to be able to integrate those other providers, and you'll see that in a variety of ways. We also are approaching this with an open architecture in the AI providers because our clients are using a variety of models. And as we pursue and evaluate how to work effectively with the AI providers, and we have active dialogues with all of them, we are going to want to maintain flexibility to meet the broad needs of the industry, but we also need, importantly, to make certain that we are defending the integrity of our data sets, the value of the data sets because it is the industry's data. And so we want to make certain that we are exploring those opportunities, understanding how the industry wants us to work with them. We think that can be a very powerful partnership. But we have to do that in a way that's protective of our assets. and also important for the integrity of those data sets from a regulatory context.

Right. You didn't answer the last part, Claude for Financial Services, is the industry interested in Verisk data being a plug in there?

Absolutely. And that's -- and I'm sorry, I wasn't clear on that. We are certainly interested in exploring that. I could see that as a possibility within the [Technical Difficulty] the review of making certain that, that's done in a safe, ethically appropriate way and with regulatory support to it. But we're open to any of the ideas that the industry believes is necessary to support their needs.

Toni Kaplan from Morgan Stanley. Lee, you talked [Technical Difficulty] the regulatory barriers or moat that you have, does that underpin sort of the entire business? Is that how investors should be looking at it? Or are there specific areas within the business that maybe don't have that regulatory barrier?

Toni, it's pervasive across all of our businesses because it dictates how underwriting decisions need to be made and supported, particularly from a rating and pricing standpoint, it certainly involves policy language that we support the industry with and the ability to understand that those policies and those submissions on a state-by-state basis. It influences the claims dimension in terms of how carriers respond to claims, the information that they utilize to estimate and adjudicate those claims it has influence in the specialty markets and the reinsurance markets in terms of how those markets transacted. So I think it's pervasive across the industry.

And as we are integrating more data sets in order to adjust that, it really affects the entire business, which is why I think that expertise and that knowledge, which is more than just reading the regulations, but understanding and working with the regulators to facilitate faster approvals, more better substantiation for an evolving risk environment and how both the carriers and the regulators need to adapt to it. One simple example of we've cited and our clients cited the new wildfire model. In California, that required our proactive engagement with the California regulatory authority to allow the use of forward-looking models in order to allow California to move forward from an insurance and from a reinsurance standpoint. So that's the level of engagement and the level of detail that we're able to provide for the industry.

I'm Gregory Peters with Raymond James. I guess I have a question in two parts. First of all, being not a subject matter in all areas of technology. When you use open architecture, I pivot over to the insurance industry, and they're very protective of their own data assets. And so I want to make sure that there's still this Chinese wall that exists between the insurance companies and their data assets and opening it up to the entire customer segment. I'm just trying to understand that.

And then the other piece -- other question was just on the OCC guidance that was offered in the farms business. And just if you can unpack some of that the components and I've asked this question before around the component that relates to price increases versus other areas?

On the open architecture question, and then I'll hand it over to SK to talk about on the OCC growth guidance for the underwriting business. When I refer to that, it is not opening up access to data in an uncontrolled fashion. It is entirely with the support of the industry and how we are able to integrate other analytics, other providers into that and promote more connectivity across that ecosystem. But it is one where we will be extraordinarily attentive to how that data is used. And we have established regulatory framework and established ethical AI policy as well as contractual obligations in how we are utilizing that data, and we have a governance board to evaluate whether new applications of data are appropriate as well as exploring with our clients what they're looking for. A lot of it, Greg, is driven by what our clients are looking for and what you've heard from both Rob and SK, and you'll hear from Steve and others is that our clients want to be able to integrate more data sets and analytics and we're the natural platform with our scale and our expertise to be able to deliver that value.

Yes. On that piece, I'm actually going to defer to Elizabeth for her presentation on the kind of the composition of the OCC growth, if you don't mind, and happy to answer questions after that.

David Paige from RBC. I guess just more broadly speaking, when you overlay AI innovation onto your data assets, is that more driven from Verisk? Or are the insurers coming to you and saying, "Hey, can you put more AI into it?" Or I guess just how does those conversations above.

sure. So it's both, but I -- what I want to emphasize and I think as you will see in the solutions gallery, we're doing the hard work across a broad set of products and a wide range of data sets of understanding how we can utilize AI. And it's not just generative, it's Agentic. It's also, we think, prospectively, neuro-symbolic of where we can utilize AI to enhance the interrogation of the data, to improve the workflows and it's with that expertise that we have the unique ability to deliver that to clients at a much lower cost.

Now that is informed at varying levels of scale. For our smaller and more midsized clients, I think they are looking more to us to be able to drive that because of our scale and our expertise. But for our largest clients, they clearly have an AI strategy, but they want to talk with us about how we deliver our data sets where we are investing specifically so that they can dedicate their resources to the differentiating factors that are important to them, but there is no mistaking the fact that our data is central to their ability to extract more value because of the breadth and the depth of the data that we're able to integrate into it.

Surinder Thind with Jefferies. A question about product penetration. With your largest clients, we saw products in the teams. But when we think about the long tail, can you talk about the gap there? Is it an education issue? Is it a scale and client sophistication issue? And how should we think about where product penetration can get to?

SK, do you want to talk about that from an underwriting standpoint?

Yes, absolutely. I think there are a couple of elements, right? So one is there is an education element, and that comes to sometimes when our clients are doing things internally themselves. And we are able to come in and say, "Hey, you can use our technology to make it better." I'll give you an example. We have already in content, and we provide that through our platform. And certainly, our clients can take that and they can embed that into their workflows, as I talked about. We also have a software element, which is our electronic rating content and more and more our API-based rating content.

When we go and share that with our clients, sometimes they're like, "Oh, I didn't know you had that. I'm already doing it, what is the ROI?" And we're able to demonstrate that ROI, then it becomes the next sale. So that's one [Technical Difficulty]. The other is competitive, right? I mean we have competitors, and our clients are using competitive products, and we have to go make our case and expand our opportunity from that perspective. So I think both those things are there. And then the final thing that Lee mentioned we're all innovating every day. We're coming up with new things that we just -- it's not even education. It's more about marketing and working with the marketing team and highlighting the new innovations that we're coming up with.

And one thing I'd add, I think, SK articulated the scale and the sophistication and also the breadth of those larger clients businesses. On the smaller and mid side, there may be a smaller line of businesses. So the importance of integrating, but there also is, I think, an opportunity for us where the focus on elevating the strategic dialogue and thinking at an enterprise-wide level for our customers. We've been very, very successful with a focus on our top 25 customers. We're expanding that. And I think as we're able to broaden that out, I think that will accelerate our ability to make that value sale and improve a broader set of clients with that enhanced go-to-market strategy.

David Motemaden from Evercore ISI. Just had a question on the contributory data. Great to see the increase over the last year, the 100 more data contribution dataset contributions. Could you just talk about sort of how to think about some of your largest clients, how they're thinking about contributing data if they're contributing more, less? And how this -- like how those 100 data set contributions? [Technical Difficulty] split between maybe between top 10 versus outside of the top 10, I'd be interested in hearing.

I would say [Technical Difficulty] it's a broad subset of different clients. Again, as Lee mentioned, our clients, especially the large ones, have multiple lines of businesses. So sometimes there -- we're adding a line of business from a contribution perspective. And how they think about it is very simply, what is the value they get from contributing to us. And if we can share the value, we can show all the different ways we can provide insights to them. Then that makes that opportunity real for us. And then the final thing I'd say is we're finding new ways to help the industry kind of bring data sets together, for example, in our excess and surplus, E&S market, where we've launched a new initiative where we said, look, there isn't this database that exists in the admitted side, we're going to build one on the E&S side, and that was from feedback from our clients. And there, we're already seeing clients coming in and contributing data to us. So it's a broad spectrum of that.

Andrew Nicholas with William Blair. Lee and Rob, I think you both, at various parts of your presentation either on the screen or in your words, talked about pursuing new adjacent markets. And obviously, I think, Rob, within your business, in particular, there's competition there that's already maybe has a foothold in the asset management or the banking space. So could you just talk broadly to maybe what the opportunity looks like outside of the insurance end market and maybe what you're right to win is in those end markets as well.

I mean I'll start by saying we operate in competitive markets within the insurance space as well. We've had success growing our business over a long time horizon even in face of that competition. We continue to believe of the value of the solutions we provide and the Synergy studio platform gives us an opportunity to access those markets in a way we've not done before and speak to the underlying value of the data in our models and describe how we believe they're advantageous to models they may already be using. We'll continue to expand ecosystem partnerships. We know that we have a partnership with S&P we put in place already that helps us to produce future projected climate scenarios, but it will also be beneficial as we to get into some of these markets where maybe our competitors are already playing.

And from a broader context, it's driven by the value of the data and our ability to deliver value to those adjacent client sets. And Rob described that in terms of catastrophe risk and the other elements, but you'll hear from my colleagues when we talk about the networks, how we already serve adjacencies that are relevant to the insurance process. So in claims, serving the contractors and the adjusters and the estimators that are involved within those businesses. Regulators are an adjacency as well. So it's driven by an understanding of where our data or our connectivity creates value within those ecosystems and premised upon where the value of that data can be realized by our clients and monetized by us in that content.

[indiscernible] Fernandez from Pinson Asset Management. Just really curious to hear about how you think about the impact of AI on your analytics business and how you're protecting the pricing power of that business for potentially being impeded by AI. And also, if we could hear a few words about how you're monetizing those AI solutions? Are you going to market with different packages? Or is this more just a general price increase that is supported by the added efficiencies and solutions that AI provides you?

So it varies. And I'm going to ask Rob and SK to talk about how the analytics that they provide, whether it's in cat modeling or on the underwriting side is being influenced by AI. But to your fundamental question is, it's a range of how we're applying it. So we have certain product sets, you'll hear Aron talk about exact expert and exact AI and Exact Gen, which are specifically AI applications that we have integrated into our product sets. And we've seen great traction and momentum with those. In other cases, it's integrating that AI into an existing product to enhance its value, which will then support pricing opportunities as our clients see and realize the value associated with it. So it depends upon where we think it's most effective. But the important point is that we're able to do that at speed and at scale because of that embedded base that allows us to deliver that value and capture that value. It may not be a flashing partnership announcement, but embedded in all of these products, as you will see outside is our ability to get that value to our client, which means we're in a better position to monetize it.

But let me turn to Rob to talk about how he's seeing the impact of AI on the analytics that we provide on the modeling front.

Importantly, I'd start by saying, AI is not new to the catastrophe modeling space or Verisk generative AI may be, but Machine Learning has been in place to translate large scales of data to location-level insights for quite some time. And we've been deploying that readily in our model creation for decades. The way generative AI or Agentic AI can help us is by some of the workflow enhancing I mentioned before and giving our clients opportunity to engage with the output data that we're creating with our proprietary data advantage, putting it in better places for better risk decisions. At least for our business, it's not new. It's an operational enhancement that makes our data more available.

Yes. I will concur with that. It's not new. And given the proprietary nature of our data and how we collect it and permission access and how we normalize it, where we see the impact is it's actually helping us. It's helping our clients query that database in a natural language way and get a lot more value out of it. So for us, it is really a force of good in some sense, right? We're kind of using it across our products so that clients can get more value from it. And that drives that flywheel of more value, they give us more data, we provide more analytics.

This is Kelsey from Autonomous. So when I look through various transcript over the last 10 years, you basically started talking about integrating AI into your workflows from 2016. So as we think about measuring that pace of innovation, I guess one way to measure this is the percentage of revenues that come from new products every single year. So what would that look like in the last 5 years? And what do you envision that will look like in the next 5 years?

So as you know, we have been integrating AI for at least a decade in various permutations. And in all of those cases, it has been a process of us innovating and deploying that AI, and then our clients adopting it at varying degrees of pace. And so because that AI is often integrated into our products, we can't quantify how much of that is AI-driven because it's embedded in the natural analytics that we're [Technical Difficulty] for delivering to those customers. But I will say that it is accelerating and the pace of what you see in terms of having all of our products that I described as our largest innovations schedule, all of them integrating AI, the pace of our ability to integrate that as well as our clients' appetite to see how we can develop it has clearly accelerated from where it was 5 years ago and certainly 10 years ago. But there is an adoption phase.

And I would say a year ago, as we were exploring the application of generative AI on the underwriting front and we had minimum viable products that we were testing for that. There was a very clear caution around what is the data exposure? How do we know that it's protected? How do we know that it's reliable. And that's something where the industry has had to get comfortable with it. And it will continue to need to be proven out from a regulatory grade standpoint. So I think that will continue to be the case, but the breadth of enthusiasm for how we can integrate that into existing product sets is a critical advantage that we have. It's much harder if you come at it from the outside and say, "Hey, I've got a new product that isn't directly connected to an existing regulatorily approved workflow or an established data set that is being utilized." So that's where our advantage, scale and expertise and embedded workflows become such a potent advantage for us. And we do expect it will increase the value of what our data and our technology delivers to our clients.

Jeff Meuler from Baird. So it's interesting to me to see aerial inventory listed on the slide among the so growth drivers, given Verisk has a colorful history with it. Maybe just an update on that strategy and how you view that as an opportunity, and I get that it's multimodal, but I'm wondering if satellite imagery resolution is getting to the point where there's increasing applicability to insurance use cases in lieu of higher cost plane or drone sourcing?

Yes, it has been an evolution. And from our perspective, it's been a very positive one, both from an economic and from a functionality standpoint. So SK.

Yes. So we are focused on analytic first. So we're not focused on capturing the images. We're focused on getting the best analytics out of it and making sure that we can embed it in many of our products and create new analytics. And you're right. The reason why we looked at multimodal is because these technologies are changing. And so we want to be agnostic of that. The goal [indiscernible] best coverage, best refresh and in the most economically possible way. So if satellite gets there, sure, we'll be ready. We've looked at balloons. And now we're looking at flights. So that's why we are focused on analytics and not the image capture. You're right, satellite is getting better, especially as you look at wildfire, that's an area where that is helping kind of zone in on like where the issues might be before we get to more kind of minute data images.

We're going to have to cut it off there, but you'll have another crack at us for our next Q&A session, but great questions. Really appreciate them. And we're moving to a break at this point. Okay. Thank you.

We invite you to enjoy a short 15-minute break and encourage you to visit the solutions gallery.

[Break]

[Technical Difficulty] On the right-hand side, I'm particularly excited about the third number. The $1.9 billion plus claim records. And those are proprietary records that we've accumulated and that we continue to accumulate every day. And it's through that, the insights that we create that creates the value. So how are we doing? Strong growth and great recurring revenue. On the left-hand side, you could see we have about 7.5% growth, and that's actually at the high end of what we said 3 years ago at Investor Day. And on the right-hand side, I'm excited to say that our subscription or recurring revenue is up 4 points from 74% to 78% over the last 3 years.

And let's talk about our customer base. It's actually the most diverse space within Verisk. It's approximately 50% insurers or carriers. And then the other 50% is a combination of third-party adjusters, contractors, and that 7% represents ecosystem partners. That's growing significantly. It's actually grown 28% CAGR over the last couple of years and continue to accelerate that growth, and we'll talk more about that shortly.

Since the last Investor Day, we made significant progress across all parts of what we've set out to do. I want to just hit on the second and the fourth circle for a moment. That accelerated product innovation, again, we're taking our proprietary data set and creating from the ground technology solutions to address pain points across the ecosystem of claims. And we're infusing AI into that to create great insights. And on the far right-hand side, as I mentioned, we've dramatically expanded the number of partners across the claim ecosystem to help us to create data for us and for more importantly, for our customers to create insights.

Let's talk about how we're investing in growth for the business. As you could see here on the left-hand side, very large addressable market, a relatively small market share, which means there's a lot of white space for growth. And speaking of growth, we've delivered 1.5x the industry average over the past 3 years. There are many factors and concerns that are facing the industry today. As you could see on the left-hand side, and we at Verisk are creating a set of solutions based on our data, based on technology, innovation and working with our ecosystem partners and embedding AI into all of that to create great outcomes for our clients. If we take a step back for a moment, when we look at our carrier customers, the make or break of profitability is the sum of the daily decisions, actions and behaviors that happen every day on every claim. At Verisk, by embedding our solutions into the very workflow and processes of our of our customers, particularly our customer claim adjesters, whether they be third-party adjusters or carriers, it ensures that every decision, every action, every behavior is at a world-class level of execution, and that is the difference of creating profitable growth for our customers.

Our proprietary data and platforms are the industry standard. From anti-fraud business to the property restoration solutions business, to our federal and state filings for Workers' Comp claims. And these products, as I mentioned, are embedded into the very workflows and processes, and they cannot be replicated without that data. As I mentioned earlier, my previous employer, I built an AI set of solutions that created value across insurance companies. But every insurance company CEO said to me, can you please bring in data to these solutions. [indiscernible] said, no, we don't have any. That's the difference at Verisk. We have the data. We have that proprietary data, which is the backbone and the core for our customers to create profitable growth. So AI without data is a nonstarter. We have incorporated AI into all of what we do. And just to talk about AI, the way we see it, there's 2 branches: One branch is the generative and the associated Agentic AI. That's [indiscernible] for efficiency and productivity. So back to the loss investment expense part of the sort of claims triangle, it's great to optimize that using the AI. The other branch of AI is the neuro-symbolic AI, which does math and statistics. So it's greater claim outcomes or accuracy. It's also, by the way, auditable and traceable, so regulators love it.

So what we're doing is we're taking our data -- we're infusing both generative and Agentic AI to improve productivity and efficiency of our customers and infusing neuro-symbolic AI to get the right claim outcome. Again, all of this is creating enormous enterprise value at our customers. And you could see here for us, expanding revenue per client on the left-hand side, significantly improving our scale economics, and maybe most importantly, this compounding or multiplier effect AI data together. Don't take my word for it, let's listen to Dimitrius King from the Hartford, one of our customers talk about this.

[Presentation]

I had the privilege of meeting Dimitrius at our Elevate Conference, which is our property ration Solution conference a couple of weeks ago in Salt Lake, and he is passionate about the partnership that we have together.

Last but not least, on the agenda, let's talk about how we're leveraging our competitive advantage for growth. Based on carrier feedback and the evolution of tech and platforms and data in this space. We have identified 3 growth drivers to fuel our overall growth. Let's start with our expanding claim ecosystems. As I mentioned, we invested heavily in growing this partnership, and we are planning on tripling this to about 400 over the next few years. This enables us to actually improve our technical and operational claim handling for our customers and increased revenue and stickiness for Verisk.

If we bring this to life with an example in this case, it's in our anti-fraud business. stolen cars is a big problem in the industry. And what's particularly interesting is this increasing number of when there's a stolen car, it's actually not really stolen. It's a fraudulent claim. It's all fabricated. It's very hard for insurers to actually figure out is this a real stolen car or not. We have partnered with an organization that locates missing assets. In this case, we see cars. And they could know whether the car or parts of that car are for sale on any part of the website or somewhere else. So now we're when an insured brings in or puts in a stolen car claim because we embed this into the carrier workflow, the insurance company immediately knows if this is real or not. If it's not real, they deny the claim and prosecute. If it is, they efficiently and quickly administer the claim and create and come up with the right settlement. It's a huge win for our carrier customers and our third-party addresses because it saves them from paying out from fraudulent claims. It's a win for insurers. And obviously, it's a win for Verisk.

The second growth driver is around back to the data again. Data is at the core of improving every decision. Those carriers, by the way, that don't leverage information and data and insights are adversely backed against because they can't make those frontline decisions around underwriting our claims. And conversely, those that do deliver best-in-class results. Let's provide a real-world example of the data [indiscernible]. And this is unlike the last one we partnered with another organization. This is homegrown from the bottom of design, leveraging our data to create solutions for our customers. In this case, let's talk about fraud again. Verisk is about to come up with a new report. And it has, among other things, 2 statistics that are frightening. The first statistic is 30%, 30% of all U.S. consumers think it's okay to manipulate a picture that's sent to an insurance company to bolster their claim, 30%, 1 and 3 of us. And the more frightening figure is 55% [Technical Difficulty] Gen-Z, the youngest among us, I think that's okay. So over half of the Gen-Z folks think it's okay to take video or a bunch of pictures and change those pictures or video to get a higher claim payout imagine how hard it is for insurance companies when they get these videos or pictures or photos to know is this real or not? How much -- is this manipulated? Is this fabricated. What we've done is we've created digital media forensics. It's based on all of our data, and we have over 600 million images, and it's growing by over 1 million images a day, and it's embedded into every one of our customer workflows, carrier workflows and third-party adjusters.

So now when a claim comes in and an insurer takes photos or videos of a basement flood or a leak from a roof or some other damage to their home, the insurance company immediately knows if this is manipulated or not. If it is, the claim is denied and hopefully begin for prosecution. If it's not, they efficiently and quickly said all the claiming at the right outcome. Again, a huge win for our customers in terms of saving money that they should be paying a huge win for honest insurers and a huge win for Verisk. This is one small example of many from the ground up solutions that we have created over the last couple of years and we're accelerating that growth based on our data set. And this is a huge unlock for every one of our customers, every one of our carriers, contractors and third-party digesters.

Another example, this one in our property and restoration solutions business, exact expert. We have created a rules engine to figure out exactly how much damages there are in a home. And again, we embed this into the workflow and processes of every claim adjuster and third-party adjuster of our customers. And this, as you can see on the right-hand side, resulted in almost a 50% reduction in cycle time. That's that loss adjusted expense part. And over 15% improvement in actually the estimate, which is the loss ratio or the loss cost side. So very, very -- it's a repeatable model here of creating huge impact in enterprise value for our customers and it creates stickiness for us, of course.

Since I'm the new guy in town, they gave me a second video. So I'm going to -- let's hear from Ramon Lopez, another valued customer.

[Presentation]

I've had the privilege of also of Ramon for many years. He was a senior executive at a major insurance company, as he said, when I told them I'm joining Verisk he said, "Wow, congratulations. You guys are the lock for us in creating claims enterprise value." Last but not least, and I'm really excited [Technical Difficulty] now this growth driver. It's our go-to-market. We've changed how we go to market. And as Lee said, we're going to market overall across the value chain, underwriting and claims. But within claims, we're going less product by product and more holistically in an integrated way, which is really what our clients want to do and we want to see to elevate our conversations to the C-suite, and we're helping them address their pain points across the entire insurance value chain, in this case, particularly in claims, and creating value for them.

This is enabling us to align our incentives and outcomes with -- that of our customers, the carriers and adjusters. It's enabling us to create longer enterprise value and larger enterprise value contracts, not in seat pricing and just overall greater stickiness. Just to bring this to life with one example here, this is a top 10 carrier by changing how we go to market with them we've dramatically increased the number of products that we're selling to them and with them. We've increased the contract length from 3 to 5 years. And then last but not least, we've increased the contract value by over 20%.

This is one example. There are many of these in the top 10 carriers and then many in the regional set of carriers right below the top 10, and we've done the same with our contractor customers and with our third-party adjuster customers. It's a real unlock for us, and we believe for the industry. So bringing all this together, these 3 initiatives will result in a 6% to 8% annual growth over the next 3 years. In summary, bringing it back to the beginning, I am so excited to be here at Verisk. We believe that if we bring everything together as we're doing our proprietary data, incorporating from the ground innovative tech solutions, bringing in our ecosystem partners and then bringing in neuro-symbolic and generative and Agentic AI on top of all that to create real insights. And then finally, embedding everything into the core workflow and processes of all of our customers and their frontline adjusters, it's going to create enormous value for our customers, great value for policyholders for Verisk. Thank you very much.

So bear with me. Lost my mic there for a second. Can you guys all hear me? So I want to bring -- invite 3 of my colleagues up here. Given what I've emphasized about the value of networks in our business, I wanted to drill into it with each of these folks on the stage with me to help you better understand the value that we create through these networks, how it's contributing to our growth and also how AI is accelerating the value that we're realizing across these new networks.

And so I've described this ecosystem, and this is kind of a broad illustration of that ecosystem, both from an entity standpoint, you can see along the outside, we have carriers, policyholders, regulators, brokers as well as functions that we provide through this pricing, loss cost estimates and claims. And this creates a unique opportunity for us to integrate more and more of these components into the services that we provide to facilitate data transfer, better decisions and more efficient outcomes. So that, in a broad sense, is the opportunity that we have across this global industry. So I'm going to start -- 3 of my colleagues going to ask each of them, introduce them briefly and then we'll talk about each of their networks.

I'm Aron Bronco. I'm the President of our Property Restoration Solutions business unit. I've been with the organization for 25 years now. I started in technical support, building contractor calls after perhaps a release of our software that might have interrupted their day and I've held just about every position within the departments that we offer and happy to be here with you today.

I'm Ron Biderman, I'm the Chief Product Officer for our core lines business. I spent my entire 30-year career at Verisk with the majority of the time being spent in our core lines area. Happy to be here.

Good morning, everyone. I'm Tim Rayner. I'm President of Specialty Business Solutions. I've been at Verisk for 7 years, having spent the prior 18 years on the broker side of the London market.

Okay. So thanks, guys. Aron, tell the audience what they need to know about your business as a starting point for our discussion today.

Excellent. So if you've ever had a property claim, damage to your property, let's call it, roof damage, or maybe a hell event, fire damage from -- in maybe your kitchen or perhaps a flood in your basement, odds are pretty good that your home was restored or your claims settled using our platform and capabilities. And so when you think about that capability within the network, we're really the industry standard. We are what connects contractors to insurance carriers to the independent adjusters and create a virtuous kind of circular loop, if you will, flywheel that brings information to and from those participants within the network in order to be able to restore the lives of policyholders after damage happens to their property.

And so in a way, we're creating the language through data and through workflow standardization that facilitates their communication.

Absolutely. And it's an orchestration of how that.

And 1 great example of this, I referred to the ELEVATE conference in terms of the word cloud that we showed. I mean, if you're there, you would -- and hopefully, you may have an opportunity to attend, you'll see the incredible community and connectivity that, that ecosystem represents. They really take a lot of great pride in addressing policyholder claims and helping them in their most difficult moments. But with that as background, Aron, can you describe the network dimension and how we are adding value as a network to that ecosystem?

Yes, I think a good way to start with us is to come up with a real kind of evaluative example. So how many of you have climbed on other than Lee -- how many of you have climbed on a roof and measured out the full dimensions of a roof. Anybody? It's okay. You can raise your hand. No, nobody has. Okay. Well, think about the complexity of being on a roof with a tape measure, trying to measure the ridge length, maybe rafter lengths, trying to sketch it out. Elizabeth was the interim claims President for a while, and I think, Elizabeth you learned what the contractor's favorite formula was or theorem. The Pythagorean theorem. So imagine being up there, trying to do the math and trying to sketch all of this out in a situation that probably is very physical and perhaps not even the safest environment. If you think about how we have connected the ecosystem participants, especially on the technology side.

So the question around the aerial imagery. We have some very great partnerships around that as an example, where the imagery is coming in. So imagine you're a desk adjuster in San Antonio. The imagery comes into you through our platform. The measurements are automated. You're not climbing on the roof and the scope is nearly automated as well. You can evaluate the hell hits, if you will, on that particular property, and essentially be able to settle that claim using to your point, the same language and construct that the contractor would use.

This creates significant efficiencies and time savings for all of the participants that are involved in that exchange. And that one simple example, right, it's just kind of a one-to-one example. Imagine what happened. So Rob had talked about the DFW area, maybe a major thunderstorm. Imagine what happens maybe in Denver, the same type of a hell event. Literally overnight, you have 40,000 claims and properties that have been damaged. Using our capabilities, you understand the hell impact and energy through our respond product, you're able to better understand which properties of yours are damaged, and then you can begin resourcing. You can procure your resources you can set up reserves and then you can start distributing claims through the process and then referring jobs over to the contractors. And all of this then comes back into the system. So we have all of the data, all of the models. So the next storm, we continue to get smarter and better, and that's really the compounding effect of the capability we have.

Excellent. And by the way, your life insurers, thank you for not getting up on your roof. Try to avoid that, if possible. So Aaron, with that and the value that we're providing, how do you think about the growth opportunity for your business as a result of our development of the network.

So when you think about the network and the efficiencies that we create within the network, each new participant added continues to add more and more value. So from an overall retention or customer acquisition, we get better with new and interesting partners that are added to the system. So I would say that from a retention perspective, you really don't want to leave that. That's number one in terms of some of that value for the organization. Number two is revenue. And you heard Steve talk about this before, we have what's in our particular business unit a 28% compound annual growth rate since 2022 of that particular segment of our ecosystem providers. So it's growing pretty dramatically and healthy.

And then three is going to be the reach. which is there's so many different unique and interesting inputs that can be brought into the ecosystem to make the process more efficient and more valuable for everyone we see a large market opportunity to continue to expand that ecosystem approach in order to be able to grow business and most importantly, solve for challenges within the insurance and restoration Market.

And Aron, just to put one last number on this. We are now at over 140 technology partners that we have integrated into the platform over the last 3 years. So it gives you a sense of the scale and for our clients the ability to get that partner integrated into their workflow at a much lower cost where they don't have to do the development work is a massive economic advantage for them. So thanks for that.

Ron, A lot of folks might not naturally think of the Core Lines business as a network business. But at its foundation, it effectively was a network in a utility form. But tell us -- give us a little bit of background on the forums rules and loss cost businesses that you're responsible for?

Sure. Thanks, Lee. An easy way to think about our core lines business is our forms, rules and loss costs are the foundational components of the insurance products that insurers sell. So if you think about any insurance transaction that you've had, there are really 2 components to that transaction. One is you get an insurance policy, which is a contract. And the other, which you probably remember more is the premium that you're paying for that policy. So how does that relate to our products? Well, our forms are what insurers use to create that insurance policy and our loss costs and our rating information derived from that contributory database that SK talked about is what insurers are leveraging to determine the premium for that policy. And when you think about doing that, providing the forms, rules and loss costs across 32 lines of business in personal lines and commercial lines, we become deeply embedded in our clients' insurance programs.

And so let's talk about building from that. Let's talk about the network dimensions and how our clients get value out of that network.

Yes. When you think about core lines at its 50-plus-year history, it really is one of the original insurance networks and continues to play a foundational role in the industry today. With connections and strategic engagements with insurers, agents, brokers and regulators, we're creating value across the industry ecosystem.

And let me give you an example using our forms. Every year, we introduced hundreds of new and revised forms updates in response to compliance issues, in response to emerging issues and market trends. We then filed those forms in 50 jurisdictions and work with the regulators to get those forms approved. So that our insurers can start using them in their insurance programs. By Verisk doing that work once versus hundreds of insurers doing it themselves, we are taking significant costs out of the industry and accelerating speed to market by streamlining that regulatory approval process. And from a claims perspective, if you'll let me of claims, please.

You may not realize this, but insurance policies are one of the most litigated contracts, meaning that the policy language that's in our forms has been court tested over decades. So insurers that are using our insurance wording have confidence when they're adjudicating claims based on policy language, which helps them reduce claims cost and litigation risk. And that's the power of the core lines network. The more participants that are using our forms, the more value we're bringing to the echo system.

Yes. And I think important thing to emphasize, Ron, is that we aren't doing this in isolation or a vacuum. It's with intensive engagement with the industry to get their input and feedback, talk about what we're seeing. One of the most rewarding conversations I had was with the CEO of one of our major clients who said they really appreciated our emerging issues list because we're able to look across the industry and see what's developing to guide what they're doing. And a lot of that input is then reflected in the work that Ron is describing. So as you think about the growth opportunity as we continue to build that network, Ron, and how it impacts your business, describe that to us.

Yes. As SK mentioned earlier in his presentation, reimagine has been a success for Core Lines, and it has accelerated Core Lines growth by 250 basis, and we believe there's opportunity to continue creating value by expanding both who's contributing data to us and the types of data that's being contributed. And we've heard already this morning talk about the 100 data contributors that have been added to our database. What that means is more participants means more data. More data means more credibility of our data, better benchmarking and faster actionable insights for our insurers when they're making their pricing and underwriting decisions. And that's creating value for them that we will look to participate in that value creation. Then we also mentioned the E&S area where historically, the E&S data has been fragmented and hard for insurers to use. But by partnering with insurers and MGAs and by leveraging AI, we've been able to ingest carrier datas -- carrier-native E&S data into our industry standard data structure, which has allowed us to prevent -- provide benchmarks and industry insights that previously didn't exist in this market. Today, we have 8 insurers contributing over $10 billion of current and historic E&S claims, and we're on track to build the industry's first scalable E&S contributory database.

Now that may -- E&S may not be exciting to you, but I can guarantee you it's incredibly exciting, one of the most exciting things that I think we've accomplished and actually came out of a CEO conversation that I had three years ago, shortly after I stepped into the position where the CEO said, "Lee, love what you do on the admitted lines, but can you provide us more data on the E&S side?" And so we took that ball, the team ran with it. We now have an E&S actuarial specialist. And the important thing is not only is it -- are we getting new data sets, as Ron is describing, but it's leveraging our existing admitted lines, which are referenced by the E&S market, which is another dimension of growth for us. So thanks, Ron.

So Tim, it feels that we kind of stole your thunder or at least Dominics [indiscernible] Turner from Marsh did. But nonetheless, why don't you give us some background on the Specialty Business Solutions business?

Absolutely. Thank you, Lee. And we're extremely proud to have the video testimonial from Dominic that talked about the Whitespace platform. But Specialty Business Solutions is more than just Whitespace. We're a 30-year-old deeply embedded software company that serves the specialty insurance market globally with solutions from rating, pricing, policy administration, claims management and exposure management. As Lee talked in his presentation, the network, the ecosystem that we're proud to present to you today is the Whitespace platform. That's got over 385 firms, 16,000 users and over $15 billion of premium was transacted through that network in 2025 alone.

And could you distill the value that the participants in that network are extracting relative to the way that they work previously?

So Whitespace is unique in itself. Unlike our competitors in the marketplace, Whitespace has been built over the last 7 years on a data and an API-first basis. That data and API-first basis has unique capabilities for upstream and downstream efficiencies through automation and AI. Ultimately, it simplifies the broker to insurer connectivity. It reduces the administration burden. It allows brokers to source capacity on a much more efficient and effective manner. It allows insurers to deploy that capacity. And as I said upfront, it simplifies that connectivity because we are uniquely positioned to support the many to many trading for our position in the industry.

And how do you think about that in terms of the growth impact for SBS overall, Tim?

So Whitespace in 2025 grew 40%, 4-0, year-on-year. Our mission, our aim and the growth underlying this is more firms trading, more risks being placed, more premium going through the platform. But the Whitespace marketplace is not just about placement, leveraging assets from across the Verisk ecosystem from claims, from catastrophe monitoring, from underwriting data sets. We see huge potential future growth in terms of augmenting and extending that capability into more disciplines and reusing that data.

Thanks, Tim. And so we're going to do a little bit of a lightning round, and I'm going to start with Tim and bring it back on here. Tim, describe how you're integrating AI to support the network dimension at Whitespace and even more broadly at SBS?

So we are deeply embedding AI in every solution that we offer to the market. So in the white space context, we're primarily using generative AI to summarize complex risks, and I'll give you an example to bring it to life. Specialty insurance contracts are bespoke, they're proprietary, they're complex, and they're lengthy. So if you're an underwriter, you might be presented with a 60-page insurance contract. You might have underwriting guidelines that go to 20 or 30 pages. The manual process of assessing that risk, reading the guidelines and coming to a comparison can take days, weeks and hours in the back and forth. With generative AI, we're able to provide a real-time assessment that immediate feedback to the underwriter and indeed the broker if they have equivalent guidelines in their systems. Moving on to Agentic AI. We're moving beyond the multi-tenanted SaaS marketplace, which we're extremely proud of, and we're moving that into an intelligent workflow. We have proof of concepts which support agent-to-agent negotiation, and that will deliver even further value to our clients and participants on the marketplace. Overall, by deeply embedding AI in the marketplace, we're deepening -- we're extending Verisk's ecosystem moat, and we're delivering long-term revenue defensibility.

Great.

Thanks, Tim. So Ron, Core Lines Reimagined has integrated AI in multiple dimensions. Where has it been most impactful from our client standpoint?

Yes, sure. Let me share one specific example of how we're using AI in our Mozart platform to transform forms management. Now earlier, I talked about the hundreds of forms updates that we make every year. And our clients are building on top of our foundation and also creating their own forms. So when you think about year-over-year, all of these forms being created, it starts to become a challenge for our clients to manage their forms portfolio. What we've heard from some of our clients is that rationalizing and understanding differences in their forms portfolio is a process that could take months of manual effort and some of them even outsource the effort because of the amount of time that it's going to take. Well, our Mozart AI is changing that by instantly analyzing and rationalizing the forms by highlighting the key differences, but most importantly, providing an insurance-specific executive level summary of the material impacts between the forms. And that last part is the part that really gets me excited because I think that's what differentiates our Mozart AI. If you think about an insurance policy and a paragraph is being added to Section A of it. It's important to know that. But what's more important to know is that by adding this new paragraph, you've now broadened coverage beyond what was previously provided. And that is the information that is really critical for our insurers to understand, and that's the intelligence that our experts are bringing to AI informs management.

Thanks, Ron. So Aaron, we've been deploying AI in a variety of generations in our property estimating solutions business. Why don't you walk us through how we've been doing that effectively?

Absolutely. So if you take the consideration of the base, which is the core products that we offer, we have 200 million-plus assignments that have been distributed over time. That's billions of line items, billions of photos, all kinds of information that we're able to tap into. So now when you start to layer on top of that, give you an example, Exact Expert. Exact Expert is the rules management capability. So when Ron talked about making changes to like forms and endorsements, you can ensure that you're compliant. Our customers, our clients can ensure that they're compliant in those estimates based upon the way that, that policy form and that contract was ultimately written. And then when you layer on top of that, some of the additional capabilities. You have to remember, we're not just data. We're also very much tapped into the workflow aspect. So the actual job to be done that people are trying to accomplish. So if you're labeling photos as an example, putting in detailed descriptions, that's a really important task and opportunity for us to add more value. That's really an example where Exact AI comes in on top of that. And so it's a little bit more horsepower, if you will. It supercharges the experience and the workflow for some of our customers. And then you set the next layer on top of that, which is Exact Gen that we just announced at Elevate, that's where we bring those capabilities together to move things forward in a more agentic step-by-step process. And just a simple example, if you look at Exact Expert, our customers are hungry for this type of information for these types of capabilities. Exact Expert has grown by over 130% year-over-year. We launched Exact AI in October of last year. We already have 3,500 users who are using it today. So our clients are hungry for this additional capability that helps to supercharge their workflows.

And if I can just add one point to help you appreciate the scale, for Exact Expert, we have tens of thousands of users of that platform. And our clients, just at Elevate was with one of the largest adjusting firms. They're training thousands of their adjusters on the platform. We're talking about tens of thousands of professionals in the industry. And that's a great example of where as we deploy this technology into their workflows, they can get the value much quicker at a much lower cost of investment, and that's a great demonstration of our competitive. So I'll close there. We took you pretty deep into the insurance detail. I was watching. I don't think anyone passed out over the course of this. But hopefully, it really made it real for you in terms of what we're doing to integrate this technology and doing it at scale. Thanks to the panel for your insights.

Thank you. We invite you to enjoy a short break of 15 minutes and I encourage you to visit our solutions gallery, and we will continue at 10:45.

[Break]

All right. We'll go ahead and get started. Hi, everybody. I'm Elizabeth Mann, Chief Financial Officer at Verisk. It's great to see so many of you here today, and it's great to see so many familiar faces that I've spoken to quarter in, quarter out over the last 3 years. So it's a real pleasure to take a step back and take a look at everything we've accomplished over that last 3-year cycle and then focus in on the trajectory of where we go from here.

I want to start by talking about where we are today and our resilient growth engine. Let me start at a high level with a quick snapshot of Verisk. We are a growth business with a strong presence serving the insurance industry. We have strong growth driven by our subscription-based revenue model with very strong retention rates. And when we say we serve the insurance industry, we really mean it. Of the top 100 U.S. P&C carriers, we're proud to say that every single one is a customer of ours somewhere. We do serve the global insurance industry, and we go to market, as you've seen, with a number of different businesses. You can see them mapped out here. We report on a -- in two subsegments of underwriting and claims. So you can see how those are reported here. And our businesses range from our two marquee businesses that started as a consortium of the U.S. P&C industry in the forms, rules and loss cost business and the anti-fraud over 50 years ago as the industry came together. And over time, we've grown into many exciting new areas that you've heard us talk about over the course of the day. You've heard us say we serve the global insurance industry. The carriers are not our only customer type. As you can see here, they are our largest customer type, but we have a number of products and growing customer segments in the contractors and the claims professionals, in the brokers, MGAs and other distribution throughout underwriting, in reinsurers. And we do today have a small number of clients that are not themselves directly in the insurance industry, but still do carry a focus on risk.

And that brings me to my favorite slide on the power of our compounding revenue growth. On the top, you can see we've grown consistently every year going back to our IPO in 2009. And our reported growth rate has grown consistently. In fact, in the last 5 years, it's inflected upwards to a growth rate of nearly 9%. We typically look at it on an organic constant currency basis, which is what you see on the bottom. And you can see on the bottom that we have been within that 6 to 8 percentage points of organic constant currency revenue growth every year going back to 2009, with the sole exception dipping below that in 2 years of global crisis in 2009 and 2020. And just to spotlight how remarkable this is, if you ask yourself today, how many companies in today's S&P 500 can boast revenue growth no less than 5% each and every year going back to 2009. And the answer is Verisk and 12 other companies in the S&P. So we are in the top 2.5% of that S&P, and we are the only company in our sector to have this consistency and stability of the revenue growth. We've achieved that consistency and stability in a wide range of insurance industry markets. So what you can see here in the gray line is the insurance industry direct written premium growth. You can see that, that averages out over time at about 5% or mid-single digits, we say, but it's a wide range of outcomes ranging from negative growth in some years to more recently poking into double-digit growth rates. But throughout those insurance industry cycles, the Verisk revenue, OCC revenue, which you see in the Navy line has been -- has shown that resiliency and stability, averaging out at around 7%. So through the cycle, we have grown faster than the insurance industry.

How do we achieve that stability and consistency of the revenue? It is based on our subscription-based revenue model. So you can see here, 83% of our revenues today come from subscription with average subscription length of just over 2 years. And over the last 3-year cycle -- over the last 5 years, those subscriptions have grown just over 8% organic constant currency revenue growth. On top of that, we have our transactional revenues today at 17% of revenue. And those revenue types are inherently a little bit less predictable. It's often how we go to market in a new business or a new customer segment. And you can see even over this time period, they have been additive to growth, in this case, in the low single digits. Going forward from here, we do continue to expect our transactional revenues to be a contributor to growth.

Let me move now to our EBITDA margins. We have a consistent track record of overperforming on our margin expansion targets. Here, we've grown margins by over 400 basis points in the last 3-year cycle, even while continuing to self-fund a number of the great investments that you've heard my colleagues talk about and that you can see in the solutions gallery out there. Going forward from here, we do continue to expect margin expansion driven by some of these same drivers. But given the opportunities for investment, we expect the rate of margin expansion to be a little bit closer to the guidance range that we'll talk about shortly.

Putting that all together in our report card, this is what we have delivered over the last 3 years. On each of the major metrics that we committed to you at the last Investor Day, we've come in at the high end or above the range. So very proud of that achievement, and we have done it all on those metrics even while continuing to deliver a very strong return on invested capital in the mid-20s.

With that, let me turn now to our capital allocation framework. We have a clear and consistent capital allocation framework, focused on driving the highest return on invested capital. Here are the three priorities, and I'm going to focus on each one of these in turn. Let me start with our organic investments. And our primary mode of organic investment besides everything we do day-to-day in the business is our capital expenditures from a cash flow perspective. Our CapEx is almost entirely in internally developed software and technology assets, represents our organic investment. You can see on the left, the investment over time. I'll remind you, this investment has funded the investments, including enhancing and building new proprietary data sets. It's also focused on the investments that we've talked about in AI in 35 different projects that we have in use today. And today, we're investing about 10% of our CapEx in AI-based initiatives.

Now we get asked sometimes about competition from insurtechs or other start-ups. But I want to point out on the left-hand side, you see our CapEx invested over this 5-year cycle has been well over $1 billion. And so we like to remind people that at these levels of scale and investment, we are bringing unique insurance technology solutions to the market that we believe are unmatched by others.

Finally, I just want to highlight, we track the returns generated by this CapEx and by the products that come out of it, and we continue to drive very strong returns. Because of that, we intend to continue CapEx at roughly this rate as a high single-digit percentage of revenues. And just some of the projects that, that CapEx is funding, you can see here all the initiatives that we're looking at across our businesses. You heard my colleagues, Saurabh and Rob talk about their transformative programs, the Core Lines Reimagine and Verisk Synergy Studio. These programs put us in a position to deliver to the industry groundbreaking new ways of accessing our proprietary and unique content. And they are just two of the examples of investment programs that we are funding across the business.

Core Lines Reimagine as just one example of those is probably the signature example of what we have been able to do with our organic investment. You heard both Saurabh and Rob talk about the impact of that investment. Here from a financial lens, you can see on the left-hand side, we've invested over $100 million in that program on a 5-year basis. And for that investment, we have managed to drive growth accelerating by 250 basis points in that business, which is all the more remarkable when you think about that business as one that is highly present within the industry has existed for a long time and is a business at a scale of nearly $1 billion today. By the end of this year, we will have completed the original scope of that investment program. But we are -- we think there is a lot of runway still to go; number one, from clients adopting the scope of what we've already put out there, and we'll put out by the end of the year. Number two, a lot of runway for us to continue then to invest in that platform as a modern starting point for new and exciting initiatives with the data. And number three, therefore, we think there is a long runway for the benefits that Verisk can continue to derive in our business from these investments.

Finally, I wanted to highlight on organic investment. If you take our financial capacity to invest and combine that with our presence in the industry, what that gives Verisk uniquely is a differentiated ability to scale investments and new ideas. So I often think of the $100 million mark in revenue is often seen as a key milestone for a new business to prove out its scale and durability, its value for an industry. And there are many insurtechs or indeed start-ups in many industries that start off with a great idea, start off with a lot of buzz and maybe a lot of funding, but find themselves unable to scale through that threshold level. Here at Verisk, we have a track record of nurturing businesses to expand and grow and scale. And I'm proud to say that just since our last Investor Day 3 years ago in this room, we have scaled not 1, not 2, but 3 businesses through that $100 million mark and beyond. And I'm talking about our Specialty Business Solutions business, our Life Insurance business and the growth products that are reported in the Forms rules and loss cost portfolio. I think these are a testament to our ability to take ideas and investments and scale them on behalf of the industry, deliver value for clients and build fantastic businesses inside the Verisk portfolio.

With that, let me move to our second capital allocation priority, which is on selective M&A. We have used M&A in the last several years to make our portfolio of businesses better. In the last three years, we've acquired seven different businesses, and we've divested two. The seven businesses that we've acquired have enhanced our revenue growth, growing collectively in the strong double-digit range. The two businesses that we divested were clear headwinds to growth. But beyond just enhancing our financial profile, the acquisitions we've made have positioned us in better and more attractive and growing and interesting subsegments of the insurance industry with new customer sets and types that can enhance our networks.

We have a clear M&A strategy that focuses on the three priorities that you see here on the left. Proprietary data sets, whether acquiring new data sets or enhancing our own proprietary data sets; number two, focusing on emerging and new risk areas and expanding our customer base; and number three, bringing efficiencies, automation and exciting workflow opportunities to our clients. The SuranceBay acquisition that we did last year was a great example of priorities two and three that you see here. We already had a great presence in the life insurance industry with our FAST platform. The SuranceBay acquisition brought us a new customer set and new functionality and capabilities to bring to that market. We've added now the agents and the distribution side of life insurance and bringing new functionality and efficiencies to both sets of customers.

Our third capital allocation priority is driving returns of capital to shareholders, supported by our strong balance sheet. We are fortunate to have a very cash flow generative business with efficiencies in working capital and supported by a strong investment-grade balance sheet with a target debt-to-EBITDA range of 2 to 3x. Our insurance business has had very strong free cash flow growth, and we've demonstrated our track record of returning that cash flow to shareholders. As you can see in the percentages in the bars represent the percent of free cash flow that we've returned to shareholders each year. You can see that we've returned over 70% each year with well over that in some years, often generated by the disposition proceeds that we've had. I do want to note that the 2025 free cash flow here was elevated by some onetime elements on interest and taxes. But I do want to highlight that going forward, we do continue to expect free cash flow growth to be in the high single-digit range. And because we have that strong free cash flow growth, it's enabled us to return that capital to shareholders. It's been nearly $7 billion in the last 3-year cycle. On the left-hand side, you can see our dividend growth has been double digit on a per share basis. And we are now at a payout ratio in the mid-20s with room to grow over time.

On the right-hand side, you can see our share repurchases, which have been strong over time. And including to say, I'm proud to say we've already executed on the $1.5 billion accelerated share repurchase that we announced on our earnings call just two weeks ago, bringing that total to nearly $7 billion of capital returned.

And that takes us to our outlook for the next three years. These are the characteristics that drive our attractive financial model. Let me talk for a few minutes about revenue growth and margin expansion, which power the rest of the model. On the revenue growth side, these are the functional building blocks to our sustainable 6 to 8 percentage points organic constant currency revenue growth. The building blocks themselves will look familiar. They are the same as the building blocks we gave you three years ago, but the relative contributions of these has shifted a little bit. Let me start with the biggest one, which is pricing. Three years ago at Investor Day, we gave you a target for pricing contribution to growth of 300 to 400 basis points based on our historical experience and the industry outlook at the time. Actually, in 2023 to 2025, we ended up delivering just north of 5 percentage points in the pricing growth contribution to revenue. We did that primarily based on the value that we were delivering to customers, the product acceleration that you saw in Lee's slide and the better strategic client engagement were the primary drivers of that with a secondary assist from a high inflationary environment and high premium growth. That gives us the confidence to raise the target range by 50 basis points to 350 to 450 because we believe we can continue to realize the benefits from the product innovations in the core. A second way to think about revenue growth is simply the contribution by business. On the X-axis here, you can see all of our businesses laid out. And I've often been asked what is the long-term growth profile of the different businesses. So here is the view into that. On the Y-axis, you can see their target growth range. Finally, the bubble size of each business represents their relative size. If I start here -- if you start with the industry growth in the dotted line in gray at about 5 percentage points, you can see that all of our businesses are growing faster than the industry, and it ranges from our largest businesses, which are growing mid- to high single digits range to our higher-growth businesses delivering double-digit growth.

Finally, on our margin expansion, we continue to have ample opportunity to grow our margins, and that's driven by a couple of different factors. The operating leverage that we continue to expect from all of our businesses, even as they self-fund some of their investment programs. We also see numerous opportunities for efficiency gains, both from the methods that we've used successfully over the last three years and also now from efficiencies generated by new and enhanced technologies and AI opportunities. Finally, those two opportunities for margin expansion may be somewhat offset by a mix shift as we continue to invest in higher-growth businesses, both organically and inorganically. But taken all of that together, we continue to expect margin expansion opportunity in the 25 to 75 basis point range. And that results in our new long-term financial targets. We anticipate revenue growth of 6 to 8 percentage points organic constant currency on an annual basis, adjusted EBITDA growth of 7 to 10 percentage points annually, adjusted EBITDA margin expansion of 25 to 75 basis points and double-digit EPS growth. Those four targets may not seem surprising to you. They are the same as the ones we articulated at our last Investor Day, but we are proud to reiterate them, now compounding off of a higher base, which has grown north of $3 billion and into this evolving environment. And to those four metrics, we want to add a fifth metric on return of capital with the intention to return at least 75 percentage points of our free cash flow to shareholders in the form of dividends and repurchases.

In summary, we are proud of our compounding growth, our continued margin expansion and our disciplined capital allocation, all of which power our attractive financial model.

And with that, I'm going to invite my colleagues back up on the stage with me to take your questions. Thanks.

Coming up on stage. There is going to be a survey. We're always looking for ways that we can improve how we approach this. Is this the survey? Okay. So you can use that QR code and probably be available through other channels, but we welcome that input from you.

And Andrew?

Andrew Steinerman, JPMorgan. Elizabeth, I love the bubble chart and X and Y axis, very helpful. So the thing that caught my eyes up the one in the upper right, SBS. If I look at the Y-axis, it looks about 13% to 14% growth profile going forward. My question is, when I look at like kind of that exciting growth, I know it's a relatively smaller bubble. Is that 13% to 14% growth already included in SK's slide that we already saw Slide 56 with this 6.5% to 7.0% underwriting solutions growth? And just talk more what's driving SBS. And you have to remind me, SBS is sequel in SBS?

Yes. As is Whitespace, so to your first question -- your second question really, it is not included in the underwriting solutions bubble. But Tim, maybe that -- maybe you should talk about the drivers of the growth.

Yes, very happy to. So Whitespace that I talked about in the panel is a key component to that. The other two pillars of the digital solutions, how do we embed Agentic and generative AI across our technology stack. And the third is not losing sight of our heritage products in terms of policy administration, leveraging the network capability that we've established in Whitespace and delivering that platform effect to deeply integrate and embed the end-to-end workflow to support the global specialty insurance. So in summary, three pillars to the growth, developing that marketplace, delivering digital solutions and modernizing our heritage.

Is it very non-Europe today? Like I remember the Sequel acquisition had a U.K. heritage?

4

Yes. So Whitespace, all of our products are deeply embedded in the London market. But as Lee talked about in his presentation, we've launched Whitespace in Bermuda, in Dubai, in Singapore, and that's very much a global foundation that we'll build out and support the specialty industry.

Greg Peters with Raymond James, again. So I want to go back to the CapEx slide that you put up there, which I thought was kind of interesting. And in the past, I think the way you've characterized technology investments and CapEx is developing a best use case and sort of going through that and deploying it as appropriate. Elizabeth, in your comment, evolving market. And so when I think about CapEx going forward, it seems like accelerating change is going on in technology in the marketplace. Can you give us some additional color on how you're thinking about your best use cases for CapEx going forward? And how quickly those best use cases change from quarter-to-quarter?

Yes. Thanks. We do -- so we balance our priorities on investment from the time scale, to your point, we want to be evolving with industry change, but we're also not changing the programs quarter-to-quarter. I think the good thing, data investments, I think, are evolutionary. And so while a lot of the things that we have accomplished over the last three years, when they were originally scoped and designed may not have been focused on the latest AI developments. They were very much built on existing AI technology at the time. But they've given us the right data foundation and framework to continue to evolve them and enhance them as capabilities improve.

Scott Wurtzel from Wolfe Research. Elizabeth, just on the revenue sort of building blocks algorithm, it looks like you're also relative to the last guide, expecting greater contribution to growth from new clients, but also some elevated attrition as well. So just wondering if you can talk through the changes in those building blocks relative to the prior guide.

Yes, happy to. And we're now saying 100 to 200 basis points increase and then offset from those two factors. Three years ago, we said 50 to 150. That reflects a couple of different things. On the new customer side, it reflects some of the growth that we're seeing in other evolving segments of the insurance industry, including the rise of MGAs and our increased focus and presence with brokers, the growth from reinsurers. So various different types of capital coming into the insurance industry that we are in a -- maybe in a better position to capture and some new markets and new customer types. On the flip side, as we go into some newer areas, there's also industry change that can affect that both ways. One is they may be new areas to us. And so inherently maybe a little bit less predictable, giving some variability to there. But also -- you're also seeing an environment over the last three years, insurance industry M&A was at a relatively muted level. Going forward from here, there could be a bit more M&A in the environment. Obviously, we just saw one announcement this week. And so we're building headroom for that in the model. I think the important thing to know is that this is kind of part of our revenue algorithm, and we have continually been able to sustain growth even with that.

It's Jeff Silber with BMO Capital Markets. On the pricing component within your growth algorithm, I'm curious, some of the other companies in the space are talking about potentially moving more towards a data consumption model, switching pricing based on that. Is that something you're thinking about? And why or why not?

It is something that we are thinking about and exploring. I think we'll continue to evaluate it over time. But our forecast that we showed assumes kind of the revenue model that we have today.

I think an important element of that from a data consumption standpoint, as we think about it is the value that's being generated by the data that's being used. And so if it is -- and so if the data consumption is being defined as, all right, here are the data sets, and you're paying one price for them, then I think that becomes restrictive. I think we've always approached it as if there is a new application that data can be applied to or we can integrate data sets and that provides incremental value, we always want to be motivated to create more value for our clients and to participate in that value creation. So I think that's an important underlying philosophy that I see persisting.

Faiza Alwy from Deutsche Bank. I wanted to follow up on the question around software analytics, particularly on the underwriting side. And maybe you could just take a step back and just help us think about the competitive landscape there. I think we understand that your data is very proprietary. But I'm curious what's -- how many of your customers are your top customers sort of using those analytics that you have, or is it more your smaller customers that are using it? If you could just frame just the competitive dynamics there, just as we're thinking about the evolution and how software is consumed, that would be helpful.

Yes. So let me -- on the underwriting side, highlight for the different segments. So if you think about our forms and loss, the consumption of our data, whether through a human or an agent or from a software perspective has not changed, and it's not changing. We're providing more insights, so we're getting more of that data out to our customers. On the underwriting side, I talked about whether it's aerial imagery, whether it's our differentiated analytics, we're going to market in a competitive environment that has always been competitive and it continues to be, and we're offering a differentiated asset from that perspective. And then finally, from a software perspective, in our FAS business, I think we still see the same competitive environment that we've seen. We are the leader there from a differentiation perspective. So we're driving that penetration in that market.

Manav Patnaik, Barclays. Just two questions. Elizabeth, you showed the chart with net premiums and growth. You've given us some stats before. But just to clarify, in the past, you've talked about the percentage of revenues exposed to that and whether it is directly tied or multiyear, if you can just clarify that? And then the second question is, thank you for all the disclosures and mix today, but just we always want more. So just two quick ones for you. The mix between personal and commercial because there's a lot of debate on whether personal is declining. And then similarly, auto versus other?

Yes. So on these ones, I'll repeat rules of thumb that I've given before. On the input from premium, it's around 20% to 25% of our revenues that are on a contract that have some input from the premium growth at that particular carrier. It is not the sole determinant. It is one input to the negotiation. On the other questions, from a personal and commercial, very rough rule of thumb of about 60% commercial lines, about 40% personal. And auto still represents as an end market, roughly 10 percentage points across the portfolio.

Henry Hayden from Rothschild & Co. Redburn. I was hoping to get some color on the state of discussions with your clients. So are you seeing acceleration in carrier thinking when it comes to working with new technologies? And what does that look like as you think about cross-sell and upsell opportunities?

Yes. We are seeing an acceleration of our engagement with our clients across two important dimensions. The first is engagement with them in terms of how we can deliver data sets and support their AI strategy, which we've talked a lot about today. But the other dimension of the accelerated dialogue with our clients is how we can deliver enterprise solution to their purposes. And what I mean by that is -- and I'll paraphrase a conversation that I had with the Head of Personal Lines at one of our major clients who said: "Lee, look, we really value the data that we get in the claims function and the underwriting function, the risk function." But as I'm running our broad personal lines business, I need to integrate all of those. And so that has become a very frequent part of our dialogue with clients. And when we have a strategic review, as we do with all of our top clients, it's probably the area of the greatest interest and the greatest opportunity for us because it allows us to design specific solutions that meet their particular needs. So in both of those, we've seen an intensification of our dialogue in the sense of partnership that we've developed with our clients over the last three years.

Curt Nagle, BofA. Liz, a couple for you. One, just going back to the CapEx, AI, 10% of total. Where specifically is that investment going? Where does that compare to prior years? And maybe somewhat of a question kind of why not higher? It's about $30 million, a little lower. And then the second one, just a little more specifically how M&A fits into the capital allocation framework, which verticals, data sets, workflow solutions might be most attractive? And given it looks like you're going to be below your range or close to your range, right, the low end by the end of the year, how do we think about the appetite for, let's call it, larger bolt-ons?

Is that enough for you, Elizabeth?

Sorry for a long question.

Yes. Okay. Let me see if I can. On the CapEx and the AI investments, and that's just what's coming in our CapEx bucket. Obviously, a lot of our ordinary operational activities and OpEx is now impacted by that as well. In terms of types and products, I can either talk about it from a functional area, but maybe sort of product-wise, I think it really covers the product investments across what you've heard each of my business colleagues talk about. So it's very broad across the portfolio. On M&A and the target leverage range, we have ample capacity from a balance standpoint. We will continue to look at opportunities in the market. We gave our three priorities, the enhanced data sets, the customer base or new risk areas and then the efficiency and workflow automation for our clients. I think the first two are sort of strategically foundational to us and get at things that can have synergies with what -- where Verisk has a unique opportunity to create value. The last one is more of a value enhancer for things that -- for businesses that have strategic value in the first two categories.

David Motemaden from Evercore ISI. I wanted to just follow up on the core lines reimagine. And after you guys finished the rollout this year, you spoke about higher client adoption is resulting in just a continued follow-through of that initiative. Could you give us some broad perspective in terms of where client adoption is now, and how you're driving that going forward?

Yes, I'm happy to. So what we've seen since the launch is now almost 90% of our clients are using the new platform. What we also see is the growth in unique users and visitors to our platform has quadrupled year-over-year. And so you can just see the amount of adoption that we're seeing within our clients with the user base. And what we see is as we go to our clients every day, we are showcasing this platform, and that's just driving more and more usage. I think really Core Lines Reimagine is creating more consumption of our insights and the new insights that we're bringing, and we continue to see that in the future.

Yes. And it's -- one thing that I've observed is that a lot of the industry is used to a certain process, and you have to almost force and break them out. And a lot of that is concerted focus from a senior management perspective where we can partner with them and work on the training. And so that's -- I think there's a lot more opportunity for our clients to get more value out of that. But we already heard from a variety of sources that it's clear that the productivity has been enhanced.

Toni?

Toni Kaplan from Morgan Stanley. Elizabeth, I wanted to go back to the organic growth build again. You mentioned the confidence in raising the pricing by 50 bps from last time. I think 2026 is supposed to be a little bit of a lighter pricing year than '25 was. So just wondering, are we going to see sort of more of the price uplift in '27 and '28 versus this year? Or is it -- maybe it's across the whole period, but just wanted to clarify that. And maybe also on the 6% to 8% OCC growth for 2026, if you include M&A and the divestitures and net all that out, I think we're a little bit below that range for '26. And so again, like should we see sort of accelerated growth from all the investments and things that we've heard about today in sort of the later years? Is this a post 2026 story?

Thanks for the questions, Toni. I'll start with your second one because I remember it. So yes, the 6% to 8% organic growth, yes, in 2026, we are experiencing some near-term quarterly headwinds. We expect those to abate over the balance of the year. So even for 2026, we expect to be in the range. But yes, as those headwinds abate, and we don't expect to have them in the future, so we do see more opportunities going forward. Your first question was on the pricing side of things. And actually, sorry, can you repeat on the pricing...

[indiscernible]

Oh, yes. Okay. Yes, we are raising the long-term target range. On the flip side, we're coming back, although the old target was 300 to 400, the actual experience, as I said, was just over 5%. Now all of those metrics are a very broad average across a number of products, across a number of customers. But basically, we have room to raise the target even while having some cushion to the historical levels.

This is Kelsey from Autonomous again. Could you talk a little bit more about your strategy in life insurance after the acquisition of FAST Insurance Bay? I'm just wondering what the road map looks like for the next five years?

Yes, I'm happy to. There are three areas that we're investing. First, FAST is still in its early innings of adoption in the life insurance industry. So we continue to push for penetration within the industry. It is a little bit dependent on our customers and when they want to make changes, and that's when we come in. The second is we're investing in AI so that we can create some workflow efficiencies for existing customers around our platform. And the third is new areas like distribution with SuranceBay, like group benefits and pension risk transfer.

Surinder Thind with Jefferies. When I think about the big picture here, I feel like you guys have done a good job with discussing the moat, but from an outsider's perspective, can you maybe help us understand where the risk from an AI disruption is in the portfolio? Maybe can you quantify what revenues might be at risk and how that might differ your internal view versus what the external view of what's at risk might be?

Sure. So we do think at a fundamental basis that the power of AI, which we embrace, depends upon data sets. And so there are a variety of moats that we discussed, but the underlying quality of the data sets that we provide and their unique aspect is the most important defense and the economics associated with producing and sharing those data sets -- now if we were to define the risk, it would be that AI would have an ability to -- through other data sets, which we can't hypothesize to deliver the analytical function that our analytics and our data support. But I think we view that as challenging because the data sets that we have come from the industry. They are at scale, they're efficient, efficiently gathered, but that's one dimension. But that also has to be effective in a highly regulated industry, which I think is an additional and a significant challenge. This goes to the embedded nature and the regulatory grade aspects of what we are doing. I think that AI is going to be powerful in improving the functionality and the productivity of insurance professionals within the industry, and that will have a bigger impact. It will accelerate the interactions between parties, but it will still require an existing framework that is necessary to operate. So certainly, there are risks. But from -- on the basis of what we have heard with our clients, what we've experienced in our product development, the upsides are substantially greater and more immediately actionable than what we see as the prospective or hypothetical risks that we have ahead. We will certainly keep our eyes on those. We will work to defend the advantages that we have. But right now, it is, in my mind, 90% opportunity and 10% risk, and that 90% opportunity is in front of us. We're acting on it at multiple levels and across nearly all of our products.

Very rarely do we have an opportunity just to keep asking questions. So if everyone is going to be quiet, I'm going to certainly stand up and ask more questions. So Elizabeth and the team, I did an informal survey last year from some of your top customers just to get some feedback. And it was -- I wasn't out there looking for good news. I wasn't out looking there to validate their -- I was out there looking for the dirt. And one of the themes that came back was around customer service. Now I understand you've made a lot of investments, Core Lines Reimagine, et cetera. But maybe you can talk a little bit about your effective on customer service and other initiatives you might have in mind to upgrade it. So when I go on a search and destroy mission for bad news, they won't have to pick it customer service anymore.

So thanks for the question, Greg. And we're always looking for areas that we can improve in. And I think when we started three years ago, we got -- I got feedback, and I know that we got feedback that we could do a better job in being responsive to our customers, listening to our customers. And so that's been a concerted effort. It's not just been kind of relationship-driven, but how do we improve their overall experience. And so since we have the time, I'm going to ask each of my business leader colleagues to talk about what they have heard and how we've responded to it. And I feel bad for Rob because nobody is interested in catastrophic risk modeling.

Well, I just explained it so well.

But why don't you kick off, and then we'll go down here.

Thanks for the question, and I guess maybe the challenge. We take an enormous amount of pride in our client service. And in fact, the first job I had with Verisk was in a client service capacity some 24 years ago. I think where we differentiate ourselves in the market is, for example, if you have a question about a model, you're not looking up a piece of documentation, but our two guys in the solutions gallery today are engineers who will pick up the phone and talk to our clients about what makes every model tick. We are proactively in the market in advance of a model release, talking about what that model looks like, how the change impacts your book of business, and how you can begin to operationalize it right now. And the last thing I'll offer is we've talked about the Verisk Synergy Studio release coming in June of this year, I challenged our team to get out to every one of our clients in every market, everywhere around the world and talk to them about what this platform means for them, and what transition looks like, and they've done that. So we have an exceptional degree of client service interaction, and we'll continue to lean on that as we grow the business.

And I'm going to step in and square Steve because I can provide historical context here.

One thing I will say is in my 3 weeks here, I been to two of our industry conferences, our property conference that I mentioned in Salt Lake. And this week in Phoenix, we had our anti-fraud conference. And each one, one had 800 customers, one had 600 customers. I didn't talk to all 1,400, but I talked to a bunch at both. And the sentiment was incredibly positive around the partnership between Verisk and each of these organizations. So we are ensuring that we, going forward, always exceed expectations, but the sense I got at least from the first three weeks of meeting folks is very, very positive.

Yes. And let me give you some historical context because there's a lot of progress in terms of what we achieved because I think where we faced the greatest pressure and criticism was in our property estimating solutions, where under past leadership, it was a very closed system. There was a view of this is what we provide, and this is the right way to do it. And some of our clients got frustrated and that had consequences for us. But that situation has changed 180 degrees and particularly because we listened to what our clients had to say, the opening of the ecosystem and integrating 140 technology partners into that and facilitating better interactions between the carriers and the contractors and the adjusters has dramatically improved that dimension. And you hear it, as Steve indicated, in the feedback that we're getting at our conference, and you see it in the reaction and the perception of how Verisk is changed. So -- and depending upon where you're talking within the organization, some of those perceptions may take a while to change. But at the root level, I know that that's been something that we've improved dramatically. And we're seeing, I think, a similar dynamic in our anti-fraud business as we're also opening that ecosystem and bringing new technologies to it. SK, you address it from an underwriting standpoint?

Yes. Let me make three points. First, I'll agree with the points that Rob made. At a user level, at an SME level, we get very high marks in how we work with our clients. Our clients love the access to our experts, and they know that our experts are passionate about what they do, and they love getting to those experts. I think we -- historically, we've had some challenges on the underwriting side; one, on the Core Line side, we've gotten some feedback around we need to understand more about what is this product, how do we price it? Remember, I talked about the value gap perception. Well, we fixed that. We've gone in, in every client situation, we take them through, what are they subscribing to, what is the value we provide, and how do we price for that value. And I think that has made a huge difference in the feedback that I'm receiving from clients. And the second place where we have gotten feedback is it's the corollary to the fact that we are so integrated, and what we get from our clients is so proprietary. When the data that we get, because we have to -- it is regulatory grade, you have to make sure that we are looking at errors and mistakes and trends to make sure that data has the highest fidelity. That requires us to work very closely with the same clients who are giving us data. So there's a lot of back and forth. And here's an application of AI where we're using this. We're putting AI chatbots on that interaction so that now you don't have to go through a human, you can answer your questions on why my data was not submitted right. So I think we're working there, but we do that so that we have the best fidelity data, which is regulatory grade.

Just a question about just the net written premium growth expectations. When we think about the implications of AI and the ability to potentially price risk a bit more efficiently, how does that work as we look over the next 5 or 10 years in the sense of could we have a situation where net written premium growth is maybe below expectations because risk is priced better, or do we go in the other direction where maybe there's a catch-up period where risk has to be priced more appropriately and then those costs are higher? And then how does that work through in the political environment?

SK, do you want to take a crack at that?

Yes. So there are a couple of things playing here. Your point about AI and better pricing. Well, first of all, if you think about the kinds of risk and the complexity of risk, the exposures, the exposures are going up, right? So premium is exposures, and how you price that exposure. So we look at -- from an exposure perspective, it's going up. You look at loss costs, especially in some of the liability lines, it's going up. So I think that element of that demand element is still going there. I mean, Rob talked about we're putting stuff in places we shouldn't be putting, like we're continuing to do that, right? So that exposure is going up. Yes, risk pricing becomes probably more efficient. But if you look at the returns on equity on the insurance industry, underwriting profitability is still in the 2% to 3%, right? So it's not like there's a huge room to kind of compress that. So I think that what happens is probably there's more competition because people are able to do more, and this is where we come back to our data becomes more important. You want better segmentation, and there's more people looking at a quote and able to fulfill that quote because they're being more efficient from that perspective.

Yes. And I would personally take the plus side of that equation in the technological environment; one, because I think the sheer economics of increasing income levels on a global basis provide the means for more financial products, including insurance against a broader population. So you have that increasing severity. And I think with technological capability, it expands our ability to price a wider range of risk and so an increased segmentation, which I think is additive to the overall pool of net written premium on a global and even on a U.S. basis.

And then one follow-up. Just on some of the CapEx spend. Elizabeth, when you think about the levels that you're spending at, can you maybe talk about the decision there given that we're in an era of accelerated change? Is there the possibility to want to spend more at this point, or could you spend more to maybe accelerate your innovation curve?

Yes. Thanks for the question. There is potentially or we will consider over the long term, whether there's opportunities to continue to invest or to continue to drive high returns. The governor will be the ideas that we have and the returns that we think that we can generate. It will also be our bandwidth and our focus as an organization to put the investments in areas where we think, again, not only just that there's a good idea, but scale and a commercial opportunity. And so putting that together, our CapEx has been growing. And so we expect it to continue to grow roughly in line with our overall financial profile. Today, I don't see a need to accelerate that further. But we'll keep our minds open if there are new ideas.

One short answer, we have no shortage of capital. And when we see good opportunities to invest and create value, there is not a constraint on that.

Yes. Just given the change in the consolidation or attrition in the bar chart, I know a question was asked, but it sounds like that's an assumption on industry consolidation relative to historical experience. Can you comment on what the retention rate trends have been where a carrier stays in a state and continues to underwrite a line, and if there's been any change in that regard? And then I don't know if this is related to that or not, but any comments on innovation within auto underwriting. There's been some headwinds there, and there's been some comments about headwinds where there are less differentiated products. And I know you have a tough competitor, but just what's the opportunity to change that trend?

And maybe I'll start with the first question and Saurabh you can talk about the other piece. On the retention, no fundamental change in the experience that we're seeing, as you saw in the metrics that we've put out, which are consistent with what we've had before. So any dislocation comes more about capital moving out in or out, people stopping writing certain lines of business or in certain states or unfortunately, liquidations should they happen. But no fundamental change in our own retention rates.

Yes. And then on auto, look, I'm encouraged by what we see when we create a differentiated product and go to market, whether it's LightSpeed, whether it's the coverage verified analytic objects, our customers are looking for the edge. They're looking for better segmentation. And if we can bring that to them, it is something that they are willing to listen to us. Now in places where we don't have that differentiation and given the entrenched nature of the industry, that's been the tough place for us. But I'm encouraged by where we are in differentiating, and we'll continue investing in that.

I think we have time for one more question, and then I'll wrap it up.

I had a question on the claims side. So I believe your market share is unchanged from the last Investor Day. What has been the main barrier here? And Steve, as you step into the new role, what do you think needs to happen to catalyze expansion of that market share as we go forward?

Sure. I can't really speak to previous, but I will say that the new product innovation that I spoke about as examples are -- we believe that our market share is going to go up quite a bit as we sort of create answers to the pain points of our carrier -- our claim carrier executives and frontline folks. So that's exactly what we built our -- all of our ecosystem partner solutions around and our homegrown solutions around taking that data and addressing the points that need to grow at our customers. So we believe that our share will go up. It is going up now. So we believe it will go up in more of an S curve.

And I can add on the historical. I mean, it's been healthy -- it's been a period of strong growth in the market. So we've grown in line with that and have delivered corresponding revenue growth on the claim side.

So with that, let me try to wrap it up. First, I want to thank all of you for your dedication of time today, but also across the years of understanding what is to us a very exciting business. But for others that aren't as enthusiastic about insurance, sometimes arcane and difficult to understand. So we appreciate you making the effort to understand what we do. We think it's pretty cool. We think it's pretty neat and pretty powerful. What gives us confidence about our ability to continue to deliver are, in my mind, three things. One, economics. I always try to boil things down to economics. And the economics of our scale, the economics of the value of the data sets to our clients, the economics of the networks that we're facilitating are absolutely compelling. And I would encourage you to think about that dimension. It's relevant to the carriers and it's relevant to our shareholders.

The second thing is the detail. We'd love to be able to answer things with one simple answer, but we've provided themes. And to me, the confidence is seeing those themes reiterated and echoed in all of the products that we are investing in AI, how we're creating value, how we're responding to the industry's overall needs. And if you spend the time and go product by product across our organization, I think you'll see those themes repeated again and again, the value of the data, our ability to monetize new investments and innovations across a broad installed base.

And the third thing is it's more the pure enthusiasm and spirit of innovation that I see every day and with almost every interaction that I have with my Verisk colleagues. These folks love to find new ways to apply solutions and technology to help the insurance industry. The -- our industry clients appreciate that energy enthusiasm, and that really is the fuel that powers our ongoing success of finding those solutions and being able to get that value to our clients. So that's something we're going to continue to do. I know everyone on this stage is fully behind that and shares those values, and I'm immensely grateful to all of them for their leadership, and what we've accomplished. Thanks again for your time, and we look forward to continuing the dialogue.