Moodys Stock

Good day, everyone, and welcome to the Moody's Corporation Second Quarter 2026 Earnings Call. At this time, I would like to inform you that this conference is being recorded [Operator Instructions] this call is scheduled to last approximately 1 hour. I will now turn the call over to Shivani Kak, Head of Investor Relations. Shivani, please go ahead.

Thank you. Hello, and thank you for joining us today. I'm Shivani Kak, Head of Investor Relations at Moody's. This morning, we reported our second quarter results. The press release and today's presentations are posted at ir.moodys.com. We'll reference non-GAAP or adjusted measures. Please see the tables in our earnings release for reconciliations to U.S. GAAP.

Today's remarks may include forward-looking statements under the Private Securities Litigation Reform Act of 1995. Please see the safe harbor language in our earnings release and the risk factors and MD&A in our most recent Form 10-K and other SEC filings available on our website and the SEC's website. These factors could cause actual results to differ materially from those expressed or implied. Members of the media may be listening in a listen-only basis. With that, I'll turn it over to Rob.

Thanks, Shivani, and hello, everybody. Thanks for joining us today. I have the dreaded summer cold. So I pardon if my voice sounds a little bit gravelly today, but today's earnings are certainly making me feel much better. One quick update before we get to the results. In late June, we welcomed Christina Kosmowski, as CEO of Moody's Analytics. And Christina brings 3 decades of experience scaling technology and analytics businesses. And I have to tell you, just 5 weeks in, she's already moving with the pace and focus that MA's next chapter demands.

And we're thrilled to have her, and I look forward to all of you connecting with her soon. So turning to our results. Moody's delivered a standout second quarter with strong performance across the board. And at the enterprise level, we achieved 15% revenue growth, we grew adjusted operating income by 25%, expanded adjusted operating margin by 440 basis points to 55.3% and we grew adjusted diluted EPS by 31% to $4.68. And that's a great progression from the top line to the bottom line.

And I think what's most encouraging is not just the strength of the quarter, but how broad-based it was. In Moody's Investors Service, transaction revenue grew 34% and we rated more than $2 trillion of debt for the second consecutive quarter. And that reflects both the rebound in market activity as well as the enduring value of Moody's ratings in large complex financing markets. like we've got right now. MIS also delivered adjusted operating margin of 68.3%. That was up 410 basis points from last year. Moody's Analytics also continued to perform very well.

ARR reached approximately $3.7 billion. That was up nearly 9% from the prior year, with trailing 12-month retention remaining strong at 95%. MA also expanded adjusted operating margin, in this case, by 150 basis points to 33.6%. And these results reflect the continuing demand for our decision grade intelligence to help customers manage risk, to improve productivity and to make better decisions.

And taken together, I really think this was a quarter that demonstrated the power of the Moody's model. a franchise that's capable of capitalizing on strong issuance activity, durable recurring revenue growth in analytics and disciplined execution across the company. Now we're raising select full year 2026 guidance metrics, including our rated issuance expectations and capital return guidance and by narrowing our adjusted diluted EPS range, we are increasing the midpoint of our range to $16.75.

Now we'll talk about this more in the Q&A. More broadly, we continue to believe that the trends shaping our business reinforce our long-term opportunity. And capital markets are evolving, risks are becoming more interconnected, and AI is transforming workflows across industries. And in that environment, customers are increasingly turning to Moody's intelligence, our ratings, analytics and insights to make consequential decisions with greater confidence, and that's creating meaningful opportunities across our business, which we're translating into powerful operating leverage and earnings strength.

So now let me turn to Moody's Investor Service. In this past quarter, Ratings delivered 25% revenue growth with broad-based strength across all asset classes. And global issuance was powered by the multiple funding deep currents that we've been highlighting over the last few years. And reflecting this, we upgraded our issuance growth outlook to mid-single-digit percent growth for the full year. And this quarter really showcased a real breadth of funding drivers. That included refinancing, AI-related investment, private credit, digital finance, energy transition and emerging markets. And our comprehensive global coverage and our very deep targeted sector expertise really allowed us to capitalize on these drivers. So I want to give you a few examples from the quarter to really bring this to life for you. So starting with AI and data center financing, and obviously, that's a topic that's dominating the headlines. but it is only 1 of several powerful drivers that's supporting issuance growth.

So Beacon Point D.C. is a very good example of the large data center transactions that we're rating across the U.S. That was a roughly $4 billion financing for a 350-megawatt hyperscale campus developed by HUT 8. And I think more importantly, it illustrates how AI is becoming 1 of the largest capital formation stories in the global economy. It's creating financing needs that extend well beyond data centers into power and infrastructure and other sectors and supporting what we believe is a sustained pipeline of issuance activity.

In fact, hyperscalers have already exceeded our 2026 forecast for issuance and issued more debt this year than in the last 3 years combined. And the opportunity stands well beyond hyperscalers, to construction, power, hardware chips and the broader infrastructure required to support AI at scale. Hyperscaler CapEx alone is expected to approach $800 billion in 2026 and grow meaningfully again in 2027.

And even excluding AI data center and hyperscaler activity, issuance still grew double digits year-to-date. In the second quarter of the issuances over $5 billion approximately 20% were tied to AI-related investment and supporting infrastructure. That means that the other 80% was very well diversified across a range of sectors. Now private credit is another important tailwind with more than 40% growth in private credit related transactions, including structured finance mandates versus the second quarter of last year. and more than 110 new first-time mandates this quarter as investors and issuers demand more analytical rigor, transparency and independent insight.

In digital finance, our leadership and trust earned Moody's ratings the distinction as Best Digital Asset ratings and analytics provider this quarter. and we're the first rating agency to deliver ratings on chain, and now we extended our token integration engine to Solana through Alpha ledger, embedding our ratings directly into tokenized fixed income assets on a leading public blockchain. We've been building on our Canton deployment. This reinforces our network agnostic design, bringing our independent credit insights to where the markets transact. And we rated double-digit digital issuances globally this year.

And while it is early, we're encouraged by the green shoots as we have more transactions in the pipeline than we have rated year-to-date. We also recently rated BlackRock's tokenized money market fund. That's the world's largest at $2.6 billion market cap, and it's a cornerstone of the tokenized liquidity stack as a stable point reserve and on cash -- on chain cash entry point. We're also a critical rating partner to innovatived transactions in the emerging markets.

And this quarter, we rated a second emerging market CLO from the International Finance Corporation. That's similar to the 1 that we called out on our third quarter 2025 call. And we were again the sole agency on this unique transaction, which securitized corporate loans to borrowers in emerging markets, and it's helping the IFC and other multilateral development banks broaden access to institutional capital and mobilize more private sector investment.

I'm also happy to share that we marked our reentry into the insurance-linked securities market in the second quarter. And we served as both credit rating agency and modeling agent on EUR 100 million flood risk cat bond in the quarter. And this really, I think, exemplifies our One Moody's strategy in action, combining ratings and catastrophe modeling expertise to play a critical role in addressing the insurance protection gap which we recently estimated at $375 billion and by some estimates could be as high as $1 trillion. And like the other areas that I spotlighted, we are building pipeline here as well.

And in Africa, where we own the largest rating agency on the continent, we were pleased to celebrate 30 years in the region this quarter. So a shout out to all of our colleagues there who are playing an important role in Africa, developing the growing debt capital markets. And taken together, these examples really reinforce, I think, the same point, which is Moody's plays a critical role in global capital formation, and we continue to be exceptionally well positioned to monetize the massive funding deep currents around the world.

Now turning to analytics. ARR grew nearly 9%, reflecting strong second quarter execution and we're maintaining our high single-digit ARR growth outlook for the year. And we're embedding trusted decision grade intelligence directly into high stakes customer workflows. That's lending, underwriting, compliance and more. And that's really our sweet spot at the intersection of speed and trust and explainability and auditability.

And during the second quarter, we made further progress in broadening how customers access Moody's Intelligence and how deeply it's woven into their mission-critical day-to-day workflows. So with Amazon, we brought Moody's connected intelligence directly into Amazon Quick, giving AWS customers access to our ratings and research and curated data on hundreds of millions of public and private entities without requiring users to leave Amazon's AI experience.

This quarter, we announced our Sunset time line for our on-prem modeling solutions in insurance, which means we plan for our remaining customers to migrate to our cloud-based intelligent risk platform over the next several years. And to further support this migration, we partnered with AWS to add the IRP to our AWS marketplace catalog and that enables our migrating customers to count their IRP spend towards their AWS cloud commit.

With Microsoft, we launched our first AI skill on Microsoft 365 copilot co-work, and that enables agents to apply Moody's analytical frameworks and subject matter expertise. not just retrieve content. And joint go-to-market activity is building momentum with more than 20 engagements globally and initial customer trials underway. We now also have more than 100 MCP and smart API connections being used and trialed by our customers, which is an encouraging signal of demand for our trusted intelligence delivered through AI platforms.

And together, these integrations led customers spend less time questioning output and more time acting on it while giving the industry the intelligence infrastructure to accelerate enterprise adoption. Now our massive company data state now covers more than 630 million entities and our proprietary ownership linkages remain 1 of the most heavily used data sets in KYC and across the company.

And that data advantage is translating into growth in KYC and compliance use cases. helping customers reduce unnecessary screening alerts. And to that end, our AI-powered screening solutions are helping drive an approximately 50% reduction in costly and time-consuming false positive alerts, and our customers are making high stakes decisions that have little to no margin for error, which is why good enough data is not good enough for these kinds of use cases.

Now a recent competitive win in EMEA shows our strategy at work. And we had a global Fortune 500 home appliance maker that's where we displaced an established incumbent. And it wasn't just with 1 point solution for credit decisioning, but we brought together our company data, our credit models and our intelligence screening for broader third-party risk management. But back in June, I attended Exceedance, which is our flagship insurance event, and it drew a record attendance of more than 600 leaders across the property and casualty insurance sector. and we announced further enhancements to our cloud-based intelligent risk platform, including our risk data lake, more high-definition models and new agentic AI capabilities plus the extension of our casualty solutions.

And I got to say, I came away feeling very encouraged by our position and opportunity with the global insurance industry. So I want to share a few recent proof points. So first, our new capabilities enabled us to grow ARR by nearly 60% with a top 3 U.S. auto and property insurer. And this win reflects strong demand for our geospatial AI integration into property underwriting and broader adoption across personal and business lines, along with continued volume growth.

And this is a particularly important win because it's going to be a lighthouse customer that will support further expansion into the primary carrier market where historically, we've had less penetration. Second, we expanded our relationship with 1 of the top insurers and reinsurers in the Lloyd's of London market, and we deepened our penetration into their workflows, including data preparation, pricing and regulatory reporting enabling us to grow ARR by 12% off of a multimillion dollar base.

And third, in APAC, we more than doubled ARR with 1 of the world's largest life insurance and financial services groups. And this insurer now uses our credit value at risk framework as part of their investment in risk decisioning. It's supported by our credit models and economic scenarios and it's a great example of how we're helping leading insurers connect credit, macroeconomic and portfolio risk intelligence across their institutions. Now turning to banking. I also recently joined more than 400 customers at our Annual Banking Summit. And 1 message really came through clearly.

And that's that banks are under pressure to make better decisions faster, but many remain constrained by fragmented data, disconnected systems and increasingly complex risk environments. And I think the conversations were really less about AI itself and more about how AI can actually deliver outcomes and improve lending and strengthen risk management and streamline compliance and ultimately, as I hear from our banking customers all the time, help them operate more effectively and more efficiently. That's exactly where we're focused, and it continues to create some attractive opportunities across our banking franchise.

And again, I want to give a couple of examples from the quarter here. So first, with a top 3 Southeast Asian bank, we moved from proof of concept to production on an enterprise-grade AI-enabled early warning solution spanning wholesale and commercial banking across 19 countries. And what won the deal was governed explainable workflow orchestration, combining our proprietary data analytics and AI-driven narratives so that their bankers can spot and investigate counterparty risks earlier and with greater confidence.

The result, 20% ARR growth was an already very important customer. Second, we expanded with a major regional bank in the Northwestern U.S. turning a 2-bank merger integration into a meaningful growth opportunity. And through sustained executive engagement, we cleared implementation hurdles, replaced legacy tools and help the combined institution modernize credit risk assessment at scale. And rather than becoming a cost synergy, we became a growth partner lifting ARR by 8% with a clear path to broader AI-enabled workflow adoption. So some great examples from ratings and analytics from the quarter, all contributing to exceptional second quarter results and further positioning us to capitalize on the opportunities ahead. So with that, Noemie, let me turn it over to you.

Thank you, Rob, and hello, everyone. Echoing Rob, our second quarter results reflect impressive execution against the durable demand drivers we've been highlighting. Let's dive into the numbers, starting with analytics. MA delivered a very strong quarter with healthy recurring growth, disciplined investment and operating leverage. Over the past 2 years, adjusted operating margin has expanded by more than 500 basis points, while we have continued to invest in our highest priority growth opportunities. .

The story in MA is consistent. Recurring revenue is growing, transactional revenue is shrinking by design and ARR and margin expansion remain the clearest indicator of underlying business performance. MA revenue increased 4% reported or 8% on an organic constant currency basis, following our recent divestitures that closed in the second quarter, and reflecting robust demand across the franchise.

Recurring revenue grew 7% as reported or 9% on an organic constant currency basis and now represents 99% of MA revenue. Transactional revenue declined 72% year-over-year to about $10 million, consistent with the deliberate portfolio repositioning we've discussed previously. ARR ended the quarter at nearly 9% year-over-year growth and remains on track for high single-digit growth for the full year.

The quarter reflected strong sales execution with proactive contract renewals, robust cross-sell and upsell activity across the portfolio as well as new logo wins. Decision Solutions remains MA's primary growth engine, representing 44% of total MAR and delivering 10% ARR growth. Within Decision Solutions, KYC grew 13%, driven by deeper penetration within existing banking customers and expansion beyond financial services. A notable win this quarter where the new logo deployment of our investigation solution and company intelligence in a mission-critical government security application.

Banking, ARR grew 10% with lending an important contributor, delivering mid-teens growth again this quarter. Customers are migrating to our new lending suite packages, generating meaningful uplift on renewal. As customers consolidate multiple workflows onto a common platform, we believe this deepens our role in their day-to-day decisioning processes, creating additional opportunities, cross-sell and long-term ARR growth. We anticipate the banking line of business exiting the year more aligned with the typical historical high single-digit ARR growth range.

Insurance ARR grew 9%, supported by strong demand for catastrophic data models and underwriting solutions delivered through our intelligence risk platform. And a good example of that is a large specialty commercial insurer that has historically utilized on-premise modeling and is now piloting the IRP platform. What began as a modeling relationship has the potential to evolve into a broader platform deployment, illustrating how we create value in insurance, 1 platform with integrated data, analytics and workflows that increases customer value.

With less than half of our insurance customers fully transition to the IRP and following Santen announcements at Exceedance, we see a clear runway for continued growth, although the trajectory may not be linear. Research and Insights ARR grew 6%, supported by demand for CreditView and an early momentum from Moody's OneView launched in April. One view goes beyond bringing together our data research and analytics.

It now embeds research assistant as an agentic context of that available across every company page, giving customers deeper insight while working more efficiently. These migrations continue to generate attractive upsell opportunities while making it easier for customers to access a broader set of Moody's capabilities. Data and Information ARR grew 8% year-over-year, driven by continued demand for ratings data fees and Orbis data in noncompliance workflows.

In the second quarter, we expanded a long-standing relationship with the German government. embedding Moody's data and AI-enabled capabilities into core tax administration workflows, audits, investigations, transfer pricing and risk assessment. In government, in particularly in EMEA were a source of double-digit growth within the data and information business. And the same dynamic is also visible across our corporate customers.

The mega cap e-commerce and technology company we first highlighted several quarters ago, has more than doubled ARR since the end of 2024 and now is more than 8-figure relationships. What began as a targeted credit decisioning use case has expanded into a broader workflow deployment, powered by company data credit models and predictive risk analytics. This is a powerful illustration of the MA model, establish a foothold in a high-value workflow, demonstrate measurable customer outcomes and then expand as that workflow scales across business units, products and geographies.

Across banking, insurance, government and corporate markets, we're seeing a trend towards embedding Moody's into critical workflows rather than purchasing stand-alone products. And those relationships tends to be larger, stickier and create greater opportunities for expansion over time. giving us confidence in both our ARR growth outlook and continued margin progression. Turning to profitability. MA continued to deliver adjusted operating margin expansion and remains on track for full year margin guidance of 34% to 35%.

As we simplify the portfolio and consolidate platforms, we're generating operating leverage while funding our top growth priorities. Benefits that both build and support continued margin progression toward our mid- to high 30s target by year-end 2027. Switching over to MIS, rated issuance exceeded $2 trillion for the second consecutive quarter, up 33% year-over-year, 20% year-to-date. Despite the geopolitical volatility, issuers remain focused on accessing capital with constructive credit conditions, strong investor demand and continued financing needs across both corporate and structured markets.

Importantly, Q2 results were not driven by a single market dynamic. There was broad-based participation across asset classes. The diversity of issuance activity reflects the multiple secular and cyclical funding drivers we've discussed over the past several years. Revenue growth outpaced issuance growth in several key areas. benefiting from favorable transaction mix and larger, more complex mandates. At the same time, recurring revenue grew 6% to $369 million supported by our pricing initiatives, new mandates and growth in monitored credits.

First-time mandates increased by about 45% and RMP for the 750 to 850 expected for the full year, reinforcing the health of our new business pipeline and supporting future recurring revenue growth. Looking across the portfolio, Corporate Finance and PPIF benefited from a number of jumbo AI and infrastructure-related deals, while speculative grade and bank loan activity remained robust, with transaction revenue growth of 33% and 50%, respectively.

Structured finance and financial institutions rounded out the quarter with steady ABS, RMBS and frequent issuer activity. Taken together, these results demonstrate the breadth of opportunity available to MIS and the value of our global franchise, sector expertise and market position. On profitability, MIS delivered impressive adjusted operating margin expansion that underscores the substantial operating leverage embedded in the business.

We absorbed significantly higher transaction volumes while maintaining analytical rigor and without commensurate cost increases, aided by ongoing technology investments and disciplined resource management. As we continue investing in the franchise, we believe we remain well positioned to convert revenue growth into attractive earnings growth over time. We're raising our issuance outlook from low to mid-single-digit percent growth while maintaining our MIS revenue outlook.

Markets proved resilient through the early April volatility supported by AI-related financing, infrastructure investment and FIG activity. Hyperscaler and large transactions drove strong issuance in the first half and are already reflected in results. Our increased issuance forecast is concentrated in PPIF and banking driven by more data center activity in PPIF and frequent banking issuers in vague.

Because these issuers can carry lower average revenue yields given their pricing programs, the higher issuance outlook doesn't change our full year revenue expectations. As previously communicated, we're maintaining both MIS revenue and ARR guidance in the high single-digit range. For MIS, we expect low single-digit revenue growth in Q3 as market activity slows through the Sur. With Q4 revenue roughly flat versus prior year, consistent with normal seasonality. We expect that MIS margin will follow a similar seasonal pattern. For MA, we continue to expect ARR growth in the high single-digit range and margin expansion remains on track.

For modeling purposes, we expect our tax rate for the full year to be towards the high end of the guidance range of 23% to 25%. On adjusted diluted EPS, we are raising the low end of the range by $0.10, bringing full year guidance to $16.50 to $17 or 12% growth at the midpoint. We are also expanding our restructuring program envelope by $100 million and expanding this program through year-end 2027.

When completed, the full program is expected to result in annualized savings of $300 million to $350 million. This program extension expands our ongoing transformation agenda, driving further organizational health, capturing efficiencies from AI adoption across the enterprise and creating additional capacity to reinvest in our highest return growth opportunities. Our capital priorities of the business are unchanged. Fund growth, expand margins and return excess cash to shareholders.

Year-to-date, we have executed approximately $2.2 billion in share repurchases and we are raising our full year share repurchase guidance to be up to $3 billion in 2026. Free cash flow was $688 million in the quarter, up 47% year-over-year. We're adjusting full year free cash flow guidance by about $100 million to $2.7 billion to $2.9 billion, reflecting our latest working capital forecast and restructuring costs.

We are now on track to return more than 130% of free cash flow to shareholders this year, supported by proceeds from recent portfolio actions while preserving balance sheet flexibility to continue investing in growth. The through line is consistent. We're converting revenue growth into margin expansion and durable cash generation while reinvesting with discipline in our people, AI, data and workflow integration. And with that, we'll be happy to take your questions.

[Operator Instructions] Your first question comes from the line of Manav Patnaik with Barclays. Please go ahead.

I just wanted to understand the guidance, the assumptions in the second half, maybe some cadence commentary on third and fourth quarter. I think I understand the explanations of mix, but just -- it feels like it's pretty conservative. I'm just trying to appreciate where you've drawn those lines.

Yes. Thanks, Manav. So I frame the second quarter as us catching up to where we always expect it to be just a bit sooner than we planned. If you remember and go back to our April guidance, we had assumed a meaningful portion of the, call it, March air pocket will get recovered in the third quarter. against what was a tough year ago comp. So what actually happened is that recovery came through in the second quarter instead, a record June issuance pulled that activity forward.

So I guess I'd say at the halfway point of the year, we're sitting where our full year plan always expected us to be. Now what that means for our issuance guidance, we're raising our outlook from low single digit to mid-single digit percent range growth. We're holding revenue guidance at high single-digit growth for the year. The issuance upside Meacham with a bit of mix that's a bit less rich than we'd expected. More of the growth is coming from data center, financial institution transactions and these tend to carry lower average yields given deal size and a bit less from areas like insurance issuers or CLOs or CMBS, which are typically more revenue accretive per dollar of issuance.

So the increase in volume doesn't translate on one-on-one into incremental revenue. So we're not raising the outlook. We continue to feel very good with where we are and what we told you at the beginning of the year in February. Q2 reflects the planned recovery in lending earlier than we expected. It does derisk the second half a bit. We can talk about the puts and takes as well. We're no longer meaning on an outside third quarter against what was a pretty difficult prior year comp. We think that's a meaningfully better, lower risk setup than what we were sitting 3 months ago. even though the headline full year revenue guidance hasn't moved.

Yes. And I just want to double click on that, Manav, because like Noemie said, I mean, we talked about this in the April call. And Obviously, we had some air pocket at the time, and we decided not to move the guidance. And we've caught a bunch of that up. We're right where we thought we were going to be for the year. And I think last year was pretty instructive as well. If you think about what happened last year, we had Liberation Day in April. We really had a last April, we did adjust guidance down and then we brought it back up. And we ended up finishing the year pretty much right on where we thought we were going to. So I think that has also, Manav, informed us this year where we thought we were going to be halfway through the year, and so we're holding guidance.

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

I just wanted to follow up on the same question on issuance. Just wanted to better understand what would be, as you mentioned, the puts and takes going forward, what could provide upside. You obviously talked about some of the pull forward into 2Q, but are you also assuming a more conservative approach just given the geopolitical uncertainty and then maybe on the same line, how do you think about these post mandate? You talked about that being up 45%. How could that provide upside also to the numbers?

Yes, Ashish, thanks. I'm happy to talk about kind of puts and takes. And obviously, there are some variables here. We're in a complex operating environment. But there's a few things that I think could add to the upside. So this would be tailwinds for us. If we see kind of a sustained pickup in M&A activity, obviously, that's going to be good. Obviously, Noemie talked about us moderating our assumptions for hyperscaler and data center issuance through the second half of the year.

But if it runs hotter than what we've already built into our issuance guidance, then that's going to be some upside. And we know that there is multiyear demand, and we're happy to kind of double-click on the hyperscaler stuff in a bit. If inflation remains under control. And if we actually get a rate cut, that could trigger some incremental opportunistic refinancing. We've got some very big maturity walls now sitting out not just '27 but really into '28. But 2 things, Ashish, I do want to note here as, I think, possible tailwinds for us. One, we're watching high-yield spreads. And our original assumption for the year was that they were going to widen modestly into the second half of the year.

I mean there's still -- and there's actually still very tight by historical averages. and our spec-grade default rate outlook continues to decline. So that tells me there may be some support for tire spreads further into the year, which may provide greater support for leveraged finance issuance than we've been forecasting, right? So we'll see. The other thing I want to flag, Ashish, is, there's a seasonality angle here that I think many of you are very familiar with.

And issuance is historically skewed to the first half of the year. In fact, if you go back to the period from 2015 to 2025, roughly 55% of full year issuance came in the first half. And so that would be 45% in the back half. And this year, we expect that mix to be shifted more to the first half of the year, kind of in the high 50s. Again, because of the things that Noemie called out, particularly around the pull forward of the hyperscaler issuance and some of the frequent FIG issuance.

But if conditions hold, it's possible that we see a first half, second half split, that looks more like that historical pattern. And if so, that means that there would be some more upside for the second half. And I'd be remiss if I don't acknowledge maybe a few of the risks that we're focused on. Obviously, headline risk. It still exists out there, and that can trigger some risk off windows.

We saw that actually at the beginning of July in the high-yield market. And so we're just keeping an eye on that as well as any I think, extended disruption to global energy flows that may put more pressure on inflation expectations. and potentially lead companies to defer M&A. And then I think Noemie also kind of noted the second half of '25 is also a tough comp. It was a very robust second half of the year last year, and so that's also informing the guide. But net-net, I think we have a very constructive environment heading into the second half of the year.

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

I was wondering if you could talk about how much of an uplift you're seeing from NCP adoption right now? And how we should think about it as we go forward, should this continue to be a positive driver as more companies adopt MCP or well lapping sort of the initial uptake of it, great, tough comps for you? And everyone who maybe will have already wanted it, will have adopted it? Just how should we think about the dynamics there going forward?

Yes. Thanks for the question, Toni. As you heard from our prepared remarks, we've got some very good traction with customers, both buying and trialing our intelligence through MCPs and smart APIs. We've also got, I think, an encouraging mix. Some of the very big banks are accounting for some of their early paid customers for all of this. So that is encouraging. And I would say there's kind of 5, so far -- it's early, but 5 primary content sets that are driving a lot of the demand. We've got the AI-ready research entity data, news, economic data and our credit models. And as you said, we're seeing a real willingness to pay for this. And I would say that going forward, I think you're going to see us increasingly focused on what I'm going to call kind of agentic assembly and delivery of our connected intelligence where we've got the opportunity to be more integral to customer workflows than just through MCPs and smart APIs.

And that's something that Christina is focused on. So I think the bottom line is, Toni, good momentum. We've got good runway. We have good pipeline. And I think there's an opportunity to go from the early adoption of MCPs and smart APIs for our content to this idea of connected intelligence, agentic connected intelligence. And I think that's a very interesting opportunity for us that's got some legs.

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

Rob, could you just kind of talk through how you're thinking about the deep currents on a multiyear basis, especially the private credit activity monetization build for you as well as the broader infrastructure build-out. Just how do you think they build on a multiyear basis? And just what risks are you monitored and managing to on those deep currents..

Yes. Thanks for the question. So we started talking about -- we were -- I was trying to think about when we first started talking about these funding deep currents on the horizon. It was at least a couple of years ago. And we're really seeing that. And obviously, we've got this, I'd say, relatively new deep current with all of the AI infrastructure. But as we talked about, there's a lot more than that. And so if you just step back and think about what's going on in the world, there are massive infrastructure financing needs.

And this isn't just data centers and everything related to it but it's also related to good old-fashioned infrastructure. BlackRock had a number that was something like $68 trillion of infrastructure funding by 2040. And the real, I think, challenge around the world is that governments don't have a lot of fiscal space. So that means that you've got to have the public and private markets playing a very important role in funding all of this.

And if you think about it, so it's I'd say, traditional infrastructure, a major theme, AI-driven infrastructure, energy transition, let's not forget about that. military buildups around the world. And then, of course, private credit is a funding mechanism for a lot of this. And there are drivers for private credit. And I would say, first of all, private credit is about to -- is pushing into retailization, right?

That's -- and I think as private credit pushes into retail markets, that's going to drive a need for greater transparency, a common language for risk assessment, valuation consistency. You've got the NAIC engaged in some regulatory modernization and overhauling its investment framework to address this shift towards complex structured private assets that insurance companies are investing in. So I think there's some good tailwinds behind private credit.

And I would also say that private credit went through a little bit of a correction this past -- these last few months. And I think that's been a good thing for the private credit market. Investors became a little bit more circumspect that probably tightened up underwriting and some of the structures. And I think ultimately, that is good for the sustainability of private credit growth trends.

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

I wanted to go back to MIS. You mentioned a couple of times about the lower yield on some of the data center financing and the related financing. Is that because it's moving more towards free went issuers? Or are there different fee structures? If you can give us a little color on that, that would be great.

Yes, Jeff, thanks for the question. And I would say this stuff comes into the rating agency in all different ways. It comes in through corporate finance. We see it through the big hyperscaler issuance, those hyperscalers, as you can understand, have become very frequent issuers. It comes through our project and infrastructure finance area. It comes through, in some cases, structured finance and CMBS.

So it depends kind of who the issuers are, the complexity of the structure. When we see big frequent issuers doing big investment-grade bond deals, like with any other investment-grade frequent issuer, that tends to be revenue mix unfriendly when we see complex structures sometimes in project finance and in CMBS, that tends to be revenue mix friendly. And we also have a rating assessment service. And so sometimes, the issuers in project infrastructure finance will come to us to get a view on their proposed capital structure, and that presents a few different monetization opportunities for us for any given particular issuance.

So that tends to be a revenue mix friendly.

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

Maybe just turning to MA for a bit thinking about the organic growth, a nice number in Q2 at 8%. I guess for the kind of the remainder of the year and thinking about the sequencing, is that a sustainable rate? Could we perhaps see an acceleration on product road map picking up or easier comps? And how should we think through that?

Yes. So rounding up to 9%, Curtis, for the quarter. And obviously, we feel good about the momentum there. I want to caution a little bit against extrapolating that acceleration going forward, we continue to -- we didn't change our guidance. We continue to call for high single-digit ARR growth. I think it's worth remembering that analytics sales have always really been more heavily weighted to the back half of the year, particularly the fourth quarter, and that's just given the rhythm of enterprise budgeting and renewal cycles.

And so this year is no different, and we're building a real pipeline of opportunities going into the end of the year. But time -- obviously, time will tell. And I also would note that we have a new leader of MA, She's been in the seat 5 weeks, and she's doing exactly what you wanted to do. taking a very close look at our go-to-market execution and sales productivity and where we can sharpen the model further.

But I would say there are some things that are supporting this growth, just at a very high level, you've heard us talk about lending. That's a great growth story, and we've got the migration from credit lens into our new AI-enabled lending suite. That's a theme I think we're going to see throughout the year. In insurance, you heard my enthusiasm about what we're doing around insurance and it's not just around the further migration of our customers from on-prem into our cloud-based IRP. That's a great monetization pathway for us.

Lots of new high-definition models sitting on that platform that customers are now consuming but also our extension really into casualty. And that market has been underserved historically. We've gotten a lot of interest from the casualty market. We just recently formed a casualty steering group with the biggest players in casualty insurance. And so I think that's -- I feel good about the product road map there. And then, of course, we've got 2 other things I'd say that are supporting growth. One is around our solution for KYC, customer onboarding and monitoring and compliance that we're rolling out to corporate customers.

So that's for customers who need a kind of a less heavy-duty solution than financial institutions, and we've got interesting sales that we've spotlighted in the past and a good pipeline. And then we've got the migration of customers from our CreditView to our -- CreditView research platform to our Moody's OneView platform. And this is the ability to consume -- Noemie mentioned it consume a lot more of our content in 1 place enabled by AI and agentic capabilities. So all of that together is supporting kind of the growth theme that you're seeing across MA.

Your next question comes from the line of Surinder Thind with Jefferies.

Just following up on M&A. Just any color on maybe some of the key initiatives that Christina might be looking to pursue at this point? I think you mentioned go-to-market execution and sales productivity. But also any revisiting of the tech stack or anything like that? And then maybe what that would potentially mean for if there's -- would we be entering a period of accelerated investment or anything like that?

Surinder, welcome to the call. I hope you gathered from my opening remarks that we are very excited about Christina joining us and experience and perspective that she brings to us. And as I said, she's got 3 decades of scaling technology and analytics businesses out of Silicon Valley. That is exactly the experience set that we need at this moment in time. And she is thinking differently about the business. And for those of you that have heard me at these investor meetings over the last year or 2, this is going to sound familiar. She's focused on how do we think about simplifying our offerings and reducing the selling friction across cross-sell and upsell, sharpening our go-to-market motions including how we price and package our agentic solution.

She's got a lot of experience with that. So that's fantastic. I would say her early priorities line up with again, our own thinking, and that's going to start with strengthening our data layer, which really serves as the foundation for connected intelligence, accelerating the build of our intelligence layer for agentic integration and then ultimately, enabling us to up-level our solution suite. So the other thing I'd say is she's just, I think, very focused, again, early days. It's -- this is her fifth week, but focused on organizational clarity and making sure that MA structure and operating model can move at the speed that this AI first moment demand. So very excited about what she brings to the table.

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

I had a little bit of a bigger picture question here. Last week or so, we've seen some lower cost frontier models emerge. And with that kind of pointing to the potential for a significant decline in coping costs going forward, I'm curious how you're thinking about the second order impact on Moody's. Does it impact your expectations for client usage, your internal efficiency efforts and maybe relatedly, there's a lower cost model environment change the competitive dynamics or disruption risk at all in your view?

Maybe I'll take a crack at this first, and I'll let Rob chime in. I think, first on token cost. Our internal AI and token cost today is actively governed. We have a variety of tools that we put at disposals of our engineers, our back office teams. We have very strict monitoring and training to ensure they are using the best tools for the task at hand. And I'm pretty proud of what we've implemented if I listened to some of my peers and the different noise around token cost explosion.

We're not in that fact pattern at all here. When it comes to the lower costs and frontier models, I think it's still early to tell, but I would tend to view this as a tailwind keeper tokens ultimately would expand usage more than they would press price, I think. The customers would move towards increased usage of AI which I think is -- we're well positioned to benefit from. The other thing I would want to say, though, is if you look at our customers and where we deploy AI-enabled solutions today, what the use cases they're leveraging AI for in terms of gaining productivity, gaining efficiency, getting more effective performing the controls, especially in banking and very heavily regulated environment.

I think they want us, partner with us and make sure we have the right controls around our models and using the proven market leader model. So we're not there in deploying -- experimenting sort of see we're using well-established providers.

Yes. And I might also add, I mean, again, this is all evolving very quickly, right? But as you -- if we see a lowering of token costs, I think we look around, there's a lot of AI native companies, but there's a lot of companies that have basically just built an AI wrapper using somebody else's model. And I do wonder how sustainable all of that is. And that goes back to -- look, if token costs come down and they come down for everybody, for the AI natives, they're going to come down for us as well.

And it's going to enable us to be able to build and innovate faster and more cheaply. But we're going to keep capitalizing and reinforcing our source of competitive advantage. And that's this decision grade intelligence. We aren't just an AI wrapper using somebody else's model. we have an intelligent system that is integral to financial markets. And so I think that's something we're going to keep doubling down on that advantage.

We have reached the end of the Q&A session. I will now turn the call back to Rob for closing remarks.

All right. Thanks, everybody. Great quarter, constructive environment, good momentum. Let's go and talk to you next quarter.

This concludes Moody's Corporation Second Quarter 2026 Earnings Call. As a reminder, immediately following this call, the company will post the MIS revenue breakdown under the Investor Resources section of the Moody's IR homepage. Additionally, a replay will be made available after the call on Moody's IR website. This concludes today's call. Thank you for attending. You may now disconnect.

Good afternoon, everyone, and welcome to today's call. We're excited here at Moody's to have Andrew Steinerman, Managing Director and Equity Research Analyst at JPMorgan moderating this session with Cristina Pieretti, who is a General Manager and Head of Generative AI Solutions at Moody's Analytics. The questions have been presubmitted, and Andrew will be moderating. And so Andrew, thank you so much for doing this, and over to you.

My pleasure, Shivani. Thank you. Thank you, Cristina. We enjoy this research dialogue with you. Cristina, what you just start out with how should people think about the AI strategy at Moody's?

Of course. Thank you, Andrew, and thank you, Shivani. A pleasure for anyone that's listening to be here speaking about this topic that is highly relevant and which we're extremely passionate about. So when I think about GenAI strategy and Moody's GenAI strategy, the first thing I think we have to keep in mind is everything sits inside Moody's Agentic solutions, right? And I would encourage that everyone that's looking at this thinks about 2 layers and a third pillar that is about how those layers reach customers, right? So if I think -- and if we can show in the slides, we're going to show what those 3 pillars are, right? So the first pillar is Connected Intelligence. And this is highly relevant. This is a foundation and the sequencing actually matters here, right? Because you cannot build decision-grade agents on poor data.

And what makes Moody's unique, it's just not the volume of data, which, of course, is 600 million entities, 2 billion ownership links, our research, our ratings, but it's the depth of the domain expertise embedded in this data over decades, right? In credit risk, as an example, we have Moody's Ratings which are originally proprietary. For KYC and compliance, we have our Orbis database, which provides beneficial ownership mapping and entity resolutions across 170 data sources, right? So that's -- and what we do is we collect that data, we connect it, we curate it. So that's the foundation of everything. Then we go to Pillar 2. Pillar 2 is about agentic workflows, right? And it's how we package that connected intelligence into purpose-built end-to-end workflows. And there are a couple of things that are very important. First, we focus on workflows where making that decision is going to cost you a lot of money.

And what we mean by that is you don't want to make a bad credit risk decision because you're going to lose a lot of money. You don't want to underwrite the right insurance policy and not look at the risk. Again, there's big financial consequences. You don't want to lend to and engage into a relationship with -- that is the result of making a wrong KYC check because, again, it's going to cost you fines, a lot of money, a lot of reputational risk, right? So it's about developing workflow solutions in those high stake areas that are leveraging all the connected intelligence of Pillar 1. And then in the case of Pillar 3, it's how do we then reach and distribute both the connected intelligence and the agentic solutions, right? And the idea behind this Pillar 3 is we want to meet customers wherever they are building and working with AI.

So when we think about Anthropic, about AWS, about Microsoft, OpenAI, Databricks, Salesforce, we want to make sure that we are meeting our customers where they're doing their work. We don't really see them as competitors. We see them as partnerships as partners that amplify our reach. And I think there's a couple of very important things in terms of that. First, it allows us to reach new buyer personas. Second, in each of these cases that I named, we are maintaining the customer relationship, and we retain the IP, right? So if you think, again, to recap what I've said about the strategy, we are addressing 3 things. We are addressing the customer need for trusted defensible intelligence in high-state workflows. We are addressing also customers' GenAI maturity from those building their own models, their own with our data to those that prefer to consume decision-ready workflow outputs. And then we're also reaching them where they need us to meet them. And that's basically the strategy.

Okay. Cristina, Moody's has announced partnerships with 4 of the big AI players, AWS, Anthropic, Microsoft and OpenAI. Could you just give more color about those -- the nature of those partnerships?

Absolutely. So -- and I want to start by Anthropic and probably because Anthropic is every day on the news with a new announcement, right? So when I think about Anthropic, it's probably our most architecturally distinctive partnership. We have basically built 2 things with them. Back in November, in Q4 last year, we announced the launch of MCPs, right? MCPs that allow our common clients to access our data through Claude. The other thing that we most recently announced, and we believe it's the first of its kind as far as we are aware, is the launch of an MCP app, which is an interactive agent interface that lets users access Moody's agents, generate outputs and trade the sources without leaving the Claude environment, right? So it's not a data feed or an API.

It is Moody's Intelligence that is rendered in the first case as data that is -- can access through chat and in the second case through actually a workflow, right? And an example of that workflow would be running ownership an ownership check or running a portfolio monitoring workflow or running a credit memo write-off, right? So that's Anthropic. In the case of AWS, think more about 2 things. One is access of our agents and our data through the Claude marketplace through the AWS marketplace. And then most recently, we've also integrated into Amazon Q, which is AWS native generative AI chat interface, which means that customers can query voice intelligence conversational within the AWS environment.

So you don't have to leave again, if you're using AWS, you can buy our agents, and that gives us, again, increased customer reach through the marketplace and then you can also converge with our data and our agents through Amazon Q, right? I'm going to move now to the third partnership, which is Microsoft. And we think Microsoft as our productivity layer play. We all know the reach that Microsoft have. We are all users of Microsoft. We are basically embedding decision-grade intelligence directly into Microsoft 365 Copilot, researcher and Excel through a dedicated Moody's agent and MCP integration. And I want to be clear when we talk about a Moody's -- a dedicated agent is this is the way that the Microsoft environment works. It packages things to an agent.

But what it means if you are in using Microsoft 365 Copilot, if you're using Excel, if you're using Teams, you can interact with the Moody's data directly through any of those environments, of course, provided that you're already a Moody's customer, right? And then the fourth partnership, which I'm going to describe today is OpenAI. There are MCPs live in ChatGPT Enterprise. And basically, again, similar model to the other ones. You have to be a customer of Moody's and you can then -- you are using ChatGPT Enterprise and you can access the Moody's data. So if you think about the 4 partnerships I've described, there's a common thread here in every case. Moody's retains the customer relationship. Moody's controls the pricing and fulfillment, and our data is not used to train third-party models. The partners are the distribution surface, the intelligence, the IP, the customer relationship remains ours.

Right. And Cristina, you would imagine those premises that you just said will continue going forward as well. I mean, obviously, we're at the early days with these partnerships.

Absolutely. And you actually see how we have now dedicated teams inside Moody's. And when I talk about dedicated teams, I would describe them as squads that are working with these partners. We've been very deliberate in the partnerships we form, but we are -- this is not a one-off. You're going to see continuous announcements from Moody's as these partnerships launch more features, more skills, more tools, et cetera.

Okay. We'll talk a little bit more about the partnerships. But what I wonder is about LLM token economics. Like when I hear the words agentics and MCP applications for Moody's customers, I wonder who bears the cost of the tokens and obviously, tokens could be inflationary. Is the client bearing the token cost? Or are there also times when Moody's in these agentic workflows or MCP applications are bearing token costs?

Yes, yes. And this is a question we get a lot of questions around this topic. And I think it's worth answering it very careful because the model of token economics is going to depend on how the customer is accessing Moody's Intelligence. And there are basically 2 paths, right? In the first path, the customer is consuming Moody's workflows directly through Moody's own environment. So let's leave those partnerships that I described aside for a second. We are basically contracting with the customer directly because the customer is buying from us an MCP or it's buying from us an agentic workflow. In that case, Moody's carries the underlying token cost and builds them into our pricing.

So if you think about the risk of the token, it's on us to understand what is the cost per token. Of course, we do have -- we do negotiate the volume with the customers. But at the end, that token cost is beared by Moody's and it's including in the price. So the customer gets kind of a clean, predictable relationship. They pay for Moody's Intelligence and outputs without managing the variable token consumption separately. What they do have to mention -- they have to manage kind of the volume, right? If they contracted for a certain number of outputs, then, of course, if they go above that output, then they would have to -- they would pay more. So that's when they contract directly with Moody's. In the second path is when they're contracting, they're using our MCPs on our agents through the partners I described in your previous question, Andrew.

So basically, the customer is interacting with Moody's MCPs through a third-party AI environment like Claude Enterprise, like ChatGPT, like Microsoft Copilot. And in this case, the token cost sits with the customer because they are already operating within and paying for the platform environment, right? They already have a relationship with Claude. They already have a relationship with Microsoft Copilot. So Moody's is not in the billing path for those tokens. The customer has a relationship with that provider and then they have a separate relationship with Moody's for the intelligence layer on top of it, right? So you can see -- yes, I'm sorry, go ahead.

Yes. So just maybe -- I totally understand the second point. Why don't we -- just to make sure we get it on the first part, where you're like, hey, when we're contracting directly, we build token prices into the contract. My question to you is, as token costs go up or the volume of consumption goes up, you're saying the pricing to the client adjusts, and so this isn't a possible mismatch for Moody's, right?

Yes. Yes, it could be, but we are, needless to say, very careful about it, right? So first, we are monitoring every single thing that the customer consumes, and we're also monitoring very closely our token costs, right? And it's not only about the token cost, but what is the model? We have the ability to select the model we're using for everything that we're providing to the customer, right? So -- and we are very careful to use the model that makes more sense, not only from an economic standpoint, of course, but also from a performance standpoint, from a reasoning standpoint, from a follow direction standpoint.

But that us -- that gives us freedom to say, well, we're not maybe used for this task the most pricey model because it's not worth. It's not really going to make a difference, right? So we have several levers here to control. First, we are looking at token costs very closely. Second, we're looking at the volume and the consumption, what is the cost for us of clients consuming and then we have the lever of controlling the model. So as of now, we feel pretty comfortable, and we have the necessary buffers built in. So that's how we're approaching it right now.

Okay. That sounds good. I think you sort of just led towards this term that we hear a lot about consumption pricing. And maybe you're going to say, I just defined it for you. But just because there's so much discussion about consumption pricing in an AI context, how does that work for Moody's?

Yes. So I think this is something we've been extremely careful about. And I think we want to be -- we want to continue to be careful about, right? So yes, as I think consumption pricing can be something very powerful because as customers consume more data, run more agentic workflows, this is something that can be beneficial for us. So I see it as a potential uplift, right? Now we've talked before with you and many other of our analysts and investors about there's a downside to it as well, right, which is the volatility here.

So when we're thinking about consumption price, we're basically thinking about a base price, and we always price our arrangements so far as a base price that guarantees a minimum consumption. And then if you go above that consumption, then there's kind of consumption derivative pricing, right? So yes, we -- as the customer -- as this gets more ingrained in the customer and the customer consumes more, we kind of benefit from the uplift on that. Of course, with a pre-agreed pricing arrangement with our customers, but we also want to make sure that we minimize the variability or the volatility of our revenues.

It sounds like the volatility could really only be to the upside, right, because you have your base amount of pricing and then you're paying for overage if you go above that.

Yes, yes. Yes. That's basically the idea, right? And just to -- because I also want to be mindful with our clients there, right? So when you think about the data in the data, there's a potential to be more overage because as the data gets more democratized, and we're seeing when we talk to our clients and we engage our clients, there's more appetite for enterprise licenses, right? One of the things that has happened with GenAI, which we actually see as a tailwind is it has democratized the access, right? It makes simpler to use the data. It allows for more data to be used in more parts of the organizations. So you could see more increase there. I would say when you're talking about agentic workflows, you kind of know what's your business volume, right? So it's more difficult to go above that. But it's again, what you stated, Andrew, is, yes, the upside is -- it's going to be generally upside. It's difficult to be downside because we're protecting that through a minimum -- through that -- I'm sorry, I'm missing my word. But yes, so that guaranteed subscription basically.

Okay. Great. I'd love to get into specific use cases or solutions. So like when you look at agentic AI at Moody's Analytics, could you go through maybe 2 or 3 solutions that you're prioritizing with Moody's clients today? And why did you choose these use cases to kind of be the priority first?

Yes. Yes, yes, yes. So I would say, I think there's 2 things that I would highlight here, right? And when we think about prioritization and most importantly we think about our right to win, we're going to think about 2 things. One is where do we have data that is proprietary, that it's connected, that is that connected intelligence that we refer to because we all know that, again, you cannot build decision-grade agentic workflows on poor data. So it doesn't matter who's building those agents. If it's Moody's agents, if it's third-party agents, we want to make sure that we have the right data, the right context data that it's AI ready first to make sure that we can focus on those agent workflows.

And then the other thing that we've been very deliberate about is that concept of prioritizing those places where the stakes are highest, where a wrong answer has legal, regulatory or financial consequences and where Moody's has domain expertise, right? So I'm just going to repeat that, and then I'm going to give you a couple of examples. Places we have proprietary data that is connected, that has a proper context layer. So it's basically AI ready. Second, those cases where stakes are higher because the wrong answer has a lot of consequences and third places where Moody's has domain expertise. So if you put these 3 things together, we basically, as of now, have come into 3 areas. One is credit risk, and that's where we started at the beginning, right? So it's what are the type of data and/or workflows that you need to leverage GenAI for credit risk assessment and for lending.

So examples of that is how we have automated credit memo, how we're doing automated early warning. It's all the MCPs that we have rolled out either independently or through the partnerships in terms of ratings, research, probability of default models, thermographics, financials, et cetera. Second use case, it's know your customer. That's our second priority. And those are things such as entity profiling, ownership mapping, adverse media, sanction screening. So basically, a lot of it is coming from the Moody's -- from Moody's Orbis database, right? And then the third one, which is -- we're just starting on, it's basically the insurance underwriting path. So Moody's risk models, climate analytics, ESG data that can create a differentiated foundation for underwriting workflows, right?

Okay. Yes, I wanted to get a sense of if a client, and I mean a current client that's already accessing Moody's Analytics data probably through an API. If they choose a smart API or more likely an MCP server, are they paying more to access the data in an additional way, or is that part of the existing contract? In other words, when they go from API to MCP, even if it's the same data set, same customer, is that like an upgrade where they're paying more? And if they are paying more, why would they switch?

Yes, absolutely. And this is a great question. So yes, even if they're an API customer, we are charging a premium for that, right? And the reason for that and how we justify it to our clients is the following, right? When you're thinking about an API, an API is going to deliver raw data, which means that on the customer side, a group of data scientists, developers, analysts have to take the data and build something on top of it, a model, a workflow, a dashboard. And of course, the data is valuable, but it requires a lot of investment, expertise, ongoing maintenance. right? So basically, you can think about when it's an API, they're buying kind of an ingredient, right? When you think more about what they're buying with an MCP and it's -- we are already packaging the data in a way that makes the agent -- and again, we're not talking necessarily about our agents.

We're talking about large language models, we're talking about customer agents or any third-party agents. It makes those agents -- it makes the job for that agent, I'm sorry, much easier, right? Because the agent has an easier time understanding that it has to use this data and how it has to use the data because it basically has instructions for the agent on how to use the data. So you might say, well, Cristina, that's great, but isn't that a nice to have, right? And why would a client pay more for that? And the answer has several reasons behind it. First, it's speed, right? You can -- basically, by giving the clear instructions and that clear context layer, it means that the agent can go leverage and connect with the MCP and get you an answer extremely fast. Second, there is the cost element, right?

Because you are -- if you don't find the answer, if you are working with an agent or an LLM and it doesn't find the answer, it's going to keep looking everywhere it can to not only find the answer, but also if, for example, and this -- here connected intelligence comes into play. If it needs an answer that requires several things, it might -- that looking for an answer might take more and more time as it constructs the answer, right? While if we are packaging everything in MCP and we're giving clear instructions, that means that your token use is going to go down, right? And then the third is the kind of the auditability, the knowing that the answer you're going in GenAI can -- it's backed by Moody's, right? But I would really, really emphasize the first 2. One is speed and the second time, it's cost on the client side.

Okay. That makes sense. So you're using a lot of phrases, and I just want to make sure the audience catches what you mean by each of these phrases. I'm just going to mention 3 phrases. Context layer, you say that a lot, decision-grade data, and I forgot if you said this one today, but I definitely hear Moody's talk about Knowledge Graph. And just if you can go through in the context of AI and Moody's, what each of these mean for the Moody's universe?

Yes, yes, yes. So I'm going to go through the 3 of them and actually go through the 3 of them in the way we construct them, right? So the first one, of course, is we get -- we have our raw data. And we like to talk about it as decision-grade data because we never expose to our customers or to our internal applications just the raw data, right? What we end up exposing is what we call decision-grade data, which is basically the step that we hold our data to. So what does it mean? It's sourced, it's curated, it's explainable, it's auditable, which if you think about where we are focusing our efforts is extremely importable, right? Because it's then feed for decisions that carry legal, regulatory or financial consequences, right? So if you think, for example, about data you spray from the web, that's not going to be decision grade. But if you think about data that has been collected, sourced, QA connected, that then is what we call decision grade, right?

So the section matters a lot because in regulated financial services, the provenance and the auditability of the data is as important as the data itself, right? So that's what we call decision-grade data. Data that we can stand behind that our clients can say, I can trust the data, it's coming from Moody's and that I can say that to the regulator. The second term you asked me about, and I don't think I had mentioned it in the call yet, but we're talking about it a lot, and we believe it delivers a lot of value to our clients, and it's constructed on all the years of data and different acquisitions that we've made is in Knowledge Graph. And this is basically the architecture that makes that decision-graded data interconnected rather than siloed, right? So it connects those 600 million entities that we have in the Orbis database with 2 billion ownership links.

Those 2 billion ownership links are across jurisdictions, right? It connects in those ownership links with rings with -- I'm sorry, with ratings, with other credit scores with catastrophe models, with tenants, if we think about commercial real estate in one single intelligent fabric. And of course, the other thing we're doing with the Knowledge Graph is we're doing Knowledge Graph that are specific then to use cases. right? So you have a Knowledge Graph for a sales and marketing use case. You have a Knowledge Graph for a compliance use case. You have a knowledge graph for a credit risk use case because the type of data that is relevant for you and that you want to be connected is going to defer by the use case, right? So that's the Knowledge Graph piece. And then the third piece is once we've connected all that data. So think about the processing, right?

First, I described decision-grade data, you're cleaning, standardizing, collecting, making sure you can stand by that data. Then we're connecting that decision-grade data. So you have -- you can get all the relevant insights when you're analyzing something. And you're not -- again, I'm going to go back to the previous question, you're not relying on an agent or your token cost to build all those links. And then once we have that connected data, then we're going to build a context layer. And the context layer is what sits between the Knowledge Graph and the AI reasoning engine, right? So think of it as the instruction layer for AI, a structure govern representation of what that data means, how it relates, when it should be applied, what caveats apply. And that basically, it's -- what it translates is into increased accuracy and increased efficiency, right? So it's fair to say that without a context layer, an LLM can access data but cannot reason about it in any way that it's defensible in a regulated environment. So I'll stop here to see if you have further questions on this.

No, not on those 3 terms. Maybe we'll move on to the data moat. Obviously, MA breaks up its business into 3 subsegments: data and information, research and insights, decision solutions. My question is, what is the strength of your data moat in each of those 3 subsectors? And then also, a lot of terminology goes around this word proprietary. Maybe you should just -- as you talk about the strength in your data moat, just to find what you guys mean when you say proprietary data?

Yes, yes. So the first -- I probably will say that if I think about the proprietary data moat, I think it's not necessarily in data -- in each of these places. It's kind of the foundation of each of this, right? So the 3 segments is how do we organize and deliver value, right? We deliver value by providing data and information. We deliver value by providing you research and analytics and then our decision solutions, which are KYC, lending, insurance, et cetera. But actually, when I think that when we think about the data mode, it's what makes everything defensible. It's basically the foundation, right? And let me tell you why we think this is a moat. And there's 3 important components on it. The first one is access, right? So a large portion of the data we have, it's simply -- it's not publicly available, right?

And we have over the years, have created and have developed a lot of commercial agreements, licensing arrangements, royalty relationships with over 170 sources that, again, have been -- are either exclusive or semi-exclusive. So that provides a barrier to entry. But it's -- you would have to basically reconstruct a global network of supplier relationships from scratch, right? So it's not data that you're going to go and access in one place. It's basically built over a network of relationships in different jurisdictions, different countries. The second one is kind of proprietary creation. And those are assets that Moody's originated and that exist nowhere else, right? Of course, the prime example would be the Moody's ratings, right? So no LLM can generate a Moody's rating.

No competitor can replicate the regulatory acceptance and the institutional credibility behind it, right? And then the third angle of this is the construction and curation, right? It's what I've been talking again about connecting intelligence about it's the work of linking, resolving, standardizing and continuously maintaining data across jurisdiction. And I think that the part of maintaining, it's incredibly relevant, right? Because you can do this once, but this data changes constantly, right? So all the time, we're continuously refining those links, refining that entity resolution, working on the standardization and making sure that everything is data, it's decision-grade data, right? So if you put all these things together, you put the fact that you have all those relationships with providers, right, more than 170 sources of data that is not publicly available.

You have your -- the assets that you're creating, right, the ratings being the prime example. And you put then the construction and the curation and the linking of all of this, then you have a pretty robust moat, right? So going back to your original question, then I would say data and information, it's basically more of kind of the pure data, right? And again, it's then you have -- which I've described, right? And it's all the linkages that I've described was all the curation, it's all the standardization. That's number one. When you move to research and insights, it's transforming that decision grade data into analytical output, right, into credit opinions, into sector research, into those probabilities of default that we've built out of our historical default database.

And then when you think about decision solution, it's when that intelligence becomes workflow-ready tools, right? An example of that being CreditLens or some of our catalyst solutions, et cetera, right? So the point I would like to leave is it's a combination of all of this that makes you powerful, right? It's a combination of having that connect and intelligence as a foundation. It's how we've built that through, as I described. First, the access that we've created; second, the proprietary creation; third, the curation and then the analytics we've developed on top of those and then the subject matter expertise and the relationship we have with our clients to be able to automate those workflows. Now I don't know if I answered your question about the proprietary data or -- okay, good.

Yes. Yes. Here's a question. Within your MCP protocols, what data protections do you have to prevent the LLM -- a third-party LLM from memorizing your data sets, training on your data sets and particularly in your partnership agreements with companies like Anthropic, is it specifically in your agreement that they're not allowed to train on your data?

Yes. So we are extremely deliberate and focused, both with those partnerships and with our customers that there's no training allowed in our data, right? So number one is from a contractual position, we -- there's a firm contractual position across our partner agreements, right? We have a dedicated privacy program, information security program, all are publicly documented that govern how the data is handled across all products and integrations, right? And the same standards are going to apply with, again, as I said, customers or with the partners, right? That's number one. Number two, the MCP, we're being very focused on MCP architecture as the way that we want to distribute our data for GenAI purposes because of what it means, what are the implications of an MCP, right? So it basically allows our data to be accessed through a controlled interface.

So it's not transfer. When a customer runs a workload inside Claude or another partner environment, they're querying Moody's data through the MCP. They're not receiving a copy of the underlying data set. The data remains within Moody's governed infrastructure and then the outputs are generated on demand, they're sourced, they're attributed and the underlying data is not really exposed in raw term, right? So that gives us a lot of -- and then I would say the third angle is we do monitor, right? We monitor the volume of calls that is done through an MCP or through a smart API, et cetera. So I would say between the contractual agreements, the fact that you are not receiving a full copy of our database and then the fact that we're monitoring all of this, there's a robust framework there to prevent the training of -- to protect our MCP protocols and prevent the training by LLMs.

Maybe I'll add one more thing, Andrew, which is because of the nature of the MCPs, even let's say that you pull a lot of volume at one point, it's going to be a point in time kind of data dump, right? And when you think about the nature of our data, it's very important that you have real-time data. So even if you were -- if a snapshot was theoretically possible, it would not solve the customer's problem because our data is continuously updated, curated and enriched. So the value is not in the static data set. It is in the leaving governed current intelligence that reflects what are today's entity structures, what are today's ratings, what are today's news.

Yes, that makes a lot of sense. Cristina, a term that you used just a moment ago that caught is that we could monitor the volume, like if one of our clients are trying to download an unusual amount of data, unusual relative to them. My question to you is it just because you monitor the volume. But do you have audit rights? Obviously, you have these contracts with partners and clients and do you retain the right to ensure to audit that the data is being used in the scope of the contract and not, let's say, go outside the contract?

Yes. So we do have -- we usually have audit rights within the contract and that's something that we have even before GenAI. So again, I'm going to answer -- I'm going to say yes to your specific question. But I would say, again, it's 2 things, right? In all our agreements, we're defining very clear what the data can be used for, in what context and by which users, right? And then yes, we have -- then we have the monitoring in place in terms of not only the volume, but what type of data they're using. And of course, it's not only because we want to monitor, it's because we want to make sure that we are investing in the right places. And then the third thing is, yes, we do have auditability clauses in our contracts.

Okay. And usually, when you find that you audit the data, and there's like, let's say, more users at a client, the client usually just pays for that, right?

I'm sorry? Yes, if there is -- when there's increased -- yes, when there's increased usage by a client, yes, the client will pay for it, yes.

Okay, got it. How about let's talk a little bit about cross-selling and upselling. What within AI capabilities across Moody's -- the Moody's platform will drive more cross-sell and upsell?

Yes. So I would say I'm going to point to 3 things, Andrew. One is the metrics that we see, right? And we, in general, when we look at our customers that are using GenAI solutions by Moody's, we observe 2 things. We observe higher retention in that cohort and then we observe that they tend to consume more content, right? So that's a clear indicator that when we have AI adoption, it deepens the commercial relationship rather than substituting for it. We actually see higher retention and we see higher consumption, which, of course, it's a leading indicator for us to be able to increase our revenue or our commercial relationship with that customer.

The second thing, and I touched on it earlier, is when I think about the possibilities with GenAI, we are seeing -- if I think about the data, we are seeing, especially from Tier 1 institutions, more of a drive to enterprise licenses, right, to -- we want to use our data kind of throughout the organization as opposed versus in silos, right? So of course, that drives more consumption of the data. And then when we think about the agentic solutions, then there's a possibility of automation, which also allows us to tap into a different kind of -- a different part of the wallet of our customers, right? And then the third part, when I think about cross-selling, and I think this is -- I'm extremely excited about this, is the partnerships, right? Because in that, it's not only that we're meeting the customers where they're working, right? But it also allows us to tap into new buyer personas, right?

So -- and that means customers that were not necessarily previously direct Moody's customers, but that now have -- can access our data through this new platform. So I would say there's a deepening of the relationship we have with our existing customers through more -- more retention, I'm sorry. There's increased consumptions for those organizations because of that use of more data for GenAI solutions, the need for reputable data in GenAI solutions. There's -- when we work with workflow solutions, we're tapping them into the automation budget. And lastly, there's the ability to tap into new buyer personas through our partner ecosystem.

Okay. Obviously, that all sounds credible and good. You know research analysts is supposed to have some healthy skepticism as well. And so my question is what I'm going to ask you about. When your team looks at Moody's business, what are the credible risks from AI? In other words, when the Moody's leadership team realizes that there's benefits and risks, what's like one area of risk where you like we have to get this part right?

Can I give you 2?

Yes, I think so.

Okay. Good. Great. So the first one I would say, and it's -- that's one that gets me on my toes every day, it's speed, right? I think we have to make sure that we are really, really focused on the speed of embedding our data, right? I think the risk here is not that our data becomes less valuable. It is that the customers establish agent workflows with other intelligence providers because we were not there, right? And that's why you've seen from very early on, you saw us launching in 2023, the -- I'm sorry, I cannot believe I launched this product and I just blanked on its name Moody's Research Assistant. And then we saw -- you saw us coming with Agentic Workflows. And then you saw us coming with MCPs very early on. We were the first one to launch an MCP app in the market.

So -- and you'll continue seeing this from us. And yes, sometimes they ask us, are the clients there? And I would say some of the clients are, the most sophisticated are there. Some others are not. But we want to make sure that when the clients are there, we are ready with all our data, all our analytics, all our agentic workflows ready for them to implement. So I would say it's about the speed of embedding and making sure we keep that momentum, right? I think in this market, you cannot say -- and you asked me at the beginning, Andrew, you said, well, you're going to continue all this work with Claude, AWS, Microsoft, Absolutely, right? You cannot you cannot skip a bit here because then you have the risk of not being in the play when a customer is going to finally embrace -- I'm sorry, yes, it's going to start their Gen AI journey.

And I think the second we talked about it, right? The second is we need to make sure that we're protecting our IP. And that's why we're so laser-focused in the type of engagements that we sign with our customers and with the hyperscalers because we want to make sure that, yes, we are there. We are embedding again our Connected Intelligence, but we're also very mindful of retaining our IP and retaining the customer relationships, right? So we want to do it extremely fast, but we wanted to do it safe. I would say that is the approach, right? And that's what we're -- where we are very, very focused on making sure we make this a win.

That sounds right. Okay. So last question is really, Cristina, it's a summary question. So feel free to kind of bring together things that we've already spoken about. I'm sure you realize investors are sensitive to the AI risk to Moody's business. But why should investors see AI more in total as a tailwind than a risk to Moody's business going forward?

Yes, yes, yes. And maybe I think this is probably not only the summary, but it's probably one of the most -- probably the most important question here. I think there's 2 scenarios, and we hear it every day, right? And I'm going to start by the not good scenario, what I would call the bear scenario, right? And the bear scenario goes a little bit like this. AI will commoditize the data. The LLMs will synthesize everything from public sources. The customers will no longer license proprietary data sets. We are -- all these hyperscalers are going to be able to automate all the workflows that we sell through decision solutions. So we basically are -- there's no data to sell because everything has been synthesized by LLMs, everything has been commoditized and then there's no workflows. And I think why I think this bear case does not stand is because basically, this bear case is misunderstanding what Moody's sell, right?

We do not sell data. I'm going to go back to we sell decision-grade intelligence, data that is structured, that is governed, that is continuously updated, that it's explainable, that it's auditable, again, for decisions that carry legal, regulatory and financial consequences, right? Yes, you can go and scrape all the data of the world. But if you're going to have to present -- if you're JPMorgan, and I'm going to mention JPMorgan because it's your firm, Andrew, and you have to stand in front of a regulator, you're not -- and the regulator ask you, well, how did you make this KYC decisions? How do you make this credit risk decisions? How do you make all the decisions and all the reports that you have to do in front of the regulator, you're not -- your answer is not going to want to be, well, I scrape this data from here, and I don't know if I have the necessary risk. And yes, there was an issue in linking this data, right?

You want to be able to say -- to stand and say that this was done by -- it came from a reputable source, right? So I would say that's basically -- that takes me then into kind of the good scenario, right, the bullish scenario, which is with GenAI, we not only have -- we have an amplifier for that data. The importance of good data, it's more important than ever, right? And then the data becomes more importable because you want to make sure you want to avoid the risk of hallucination. You want to have data that is sourced and auditable. But then once you start embedding that data in agents, switching that data becomes extremely painful, right? So the data is going to become more stickier, not only the -- there's an increased demand for data, but then as you embed those data in your agent workflows and as you embed your data in those automation workflows, it becomes more embedded.

So there's basically -- as more agentic workflows are adopted, Moody's becomes more deeply embedded in the decisions our customers make every day. And then there's finally, the partner ecosystem through which we are reaching buyer personas we had never reached before, right? So I would say those are incremental relationships with incremental revenue, not substitutions, right? And that's, I think, the picture, right? First, we are not playing in places where you're going to be comfortable with straight data. We play in where high-stakes decisions are made. Our data assets more used, it becomes more embedded, more secure, more intelligent. And the third part, we don't see the hyperscalers as substitutions. We see them as amplifiers of our reach. And by that, we see that as mechanisms to deliver incremental revenue. I think, Andrew...

Well said, Cristina. Go ahead, Shivani. Thank you.

I can say I think that's a great kind of note to end the call on. And I just wanted to thank you both for making the time to help us kind of educate our external stakeholders on Moody's GenAI strategy and the topics that have been top of mind for many investors and analysts out there.

Absolutely. Thank you very much.

Okay. Thank you very much.

Thank you. Bye.

Bye.

Bye-bye.

Bye.

Good afternoon, everyone, and thanks for being at this far to the last session of the day. Very, very pleased to have for our next fireside chat Moody's Corporation. Pleased to welcome back again once again, Moody's President and CEO, Rob Fauber. Rob, thank you very much for coming back to the conference. And special thank you today. I know you've been in meetings all day, so I appreciate you making it all the way here.

Christian, first of all, thanks. I've been in a windowless room in the basement all day. So it's great to be above ground. But I did get the 4:00 slot. So I know we've got to be exciting here. But I just want to say thanks. This is a really high-quality conference and some great investor discussions. So thanks for inviting us.

It's tough. No better place to start than AI strategy.

How did I know that was going to be the first question?

I would say, from my observation, your AI offering has evolved. It's gone from a stand-alone assistant tool. Now you're doing more MCP-based API models, more integrated into developer workflows like Microsoft 365. Maybe talk us through what you see as the evolution of your thinking around AI, what did you learn from what you've done so far? And then sort of what's the next step for monetizing Moody's Intelligence?

Yes. So Christian, over the last, let's call it, 8 years or so, we've assembled a massive content estate around -- really around risk. And we've been pulling a lot of that together, and it's interesting when AI kind of first came on the scene in 2023, I said, look, this can be a threat or this can be an opportunity or both. But I think we really, really believe there's going to be an opportunity for someone who has an intelligence estate like we do. And for -- I would say we've had a collection of point solutions and we offer data and models, and we offer it through, in some cases, workflow software and it's web-based delivery and all sorts of things.

And you look at this and this has to be a positive for a company that has as much valuable content as we do. And increasingly, I mean you mentioned Microsoft, increasingly we're just thinking about how do we make sure we get that intelligence into the hands of our customers whenever and wherever they need it. When they're making decisions, you don't have to come through our software. If you want to do it through Teams, you want to do it through Claude, you want to call it into your own AI environment, really, we're fine with that. Because at the end of the day, what I think we're offering to customers is access to our, what I call connected intelligence. And so I think AI is a huge unlock for us.

Okay. Let's dig into Microsoft. Clearly, it seems like compelling distribution opportunity for your work. Just talk through, I don't know, the commercial structure, economics and how ultimately you're able to protect the value of your data as you embed yourself in third-party interfaces.

Yes. What's interesting is in 2023, we announced kind of a partnership with Microsoft. We deployed Copilot to all of our employees. But we didn't quite crack the code together on being able to bring the power of Moody's content into the Microsoft ecosystem. That was the idea, but it took a little bit of time. And I think we're at a really exciting point with this announcement and so the way to think about this is that very shortly, you will be able to actually access Moody's content on the team's tool bar and be able to call Moody's content into your Copilot answers. So if you want to develop a credit memo and strength and weaknesses and do pure analysis and do it with Moody's content and your own content, of course, you can do that right there in Copilot.

Now Microsoft is -- I think, this is appealing to Microsoft because it creates greater utility for Copilot, right? And it provides a trusted intelligent source that the financial community is -- uses and trust, and you can use it right in Copilot. And for us, it exposes us to a much broader set of users. And the way it works, you asked about the commercial. For now, the way we're approaching this is a bring-your-own license model. And so already, we've got -- we've had a number of engagements. And I get a lot of questions from investors about, hey, there's all these announcements, but when are we going to see the revenue. And the cadence of this really is we make the announcement and make the capability available. We start to then engage with the customers.

We've gotten really good engagement. We announced this several weeks ago, we have in the teens number of engagements with major financial institutions, okay? And then from there, we have a handful of situations where we're already now in very active discussions about a pilot. And that's just in the span of several weeks. From there, we go to signing and that then is about -- it's a commercial opportunity at that bank where we say we're going to make a core parts of our content and intelligence system available now through your -- through AI surfaces, whether that's Teams or whether that may be Claude as well, we announced something with Anthropic or whether it's your own internal AI workflow, right?

So we're now going to make that available to you, the bank. We will have a new agreement. There'll be a new pricing opportunity. There'll be new IP protections and agreements when it's in your AI environment. Then we're going to see usage and then we're going to start to see actual revenue. And it's not -- we're not doing consumption-based pricing at this point. What we really want to do is drive embeddedness and usage of these financial institutions and have them get tremendous value out of our content. So we're -- it's early days, but already some exciting, I think, momentum. And I think what we owe the investor community is some visibility now as we move forward into the engagements and the POCs and the signed contracts resulting from these various announcements.

Okay. Maybe for just people that are newer to the story. The biggest concern is around defensibility of the data moat. And you've talked about your proprietary data being the context layer, if you like, for financial AI. Maybe describe exactly what makes the data set difficult to replicate just to give a sense of the...

Yes. So let's just -- I'm going to cover the broad components that are -- you're talking about analytics. I'm going to cover the broad components because sometimes when people say data, they're only focused on the company data, which we call Orbis. But let's start with -- we're the only place that you can get Moody's research, right? So that has -- I think there's a lot of resilience to that. In the banking franchise, we have a proprietary contributory default database we've curated for over 3 decades. And that default database allows us to calibrate our credit models, and we have public and private credit models. And those then are used in our lending suite. They're used by bank credit departments. They're really the gold standard in credit risk assessment at banks. And that is calibrated from a proprietary default database.

And it's credentialized because when your regulator comes in and looks at the loan file, and they know that you're using the Moody's scoring models, they know that, that is being calibrated against actual default history. We move to insurance. Our catastrophe models are built using the contributed claims data from the insurance industry. So the insurance industry says, "Hey, we want to get better at understanding wildfire risk or flood risk or hail risk, we're going to give you access to our claims data and you will build the model and then provide the model back to the industry. In some cases, we actually form industry working groups and the customer community, the insurance community actually invests in the tooling.

So that -- so there's a real -- between the catastrophe models and the actuarial models, these are very proprietary, hard to replicate. The last part I want to get to is the massive company database. And that is curated through a collection of hundreds of information providers that we have commercial relationships with, think of these as credit bureaus and companies houses around the world. And we have commercial contracts and IP rights and ability to create derivative. Derivative works off of that, and we pay back royalties to these information providers. Some of that information, Christian, I will acknowledge the basic address and company information. And that can be aggregated by web scraping companies today and already is. That's not where the value is.

We also get information from those companies houses and IP providers that is private that you have to have a contractual relationship with. You could have a contractual relationship with them, but it's going to be hard for your agent to do that. It's likely going to take a human to go around to these hundreds of providers around the world. And those providers have become more conscious of who's consuming the data about companies in their country. And the last part of that data is derived and transformed data where we create ownership hierarchies. That's where the value is. And the primary use case for that is financial crime compliance. We're understanding the connectedness that we have created is particularly valuable.

Cool. Let's dig into your businesses. We'll start with Moody's Analytics. And just a near-term here, as you think about sort of ARR growth in that business, it's kind of held in around 80-ish percent. As investors think about the second half of the year, are there any catalysts or which sort of specific product launches or catalysts gives you confidence in your ability to sustain that growth or potentially accelerate it?

Yes. So it's a broad portfolio. I'll probably just touch very quickly on 5 things. One, when you think of our credit, our flagship product is really the credit research, right? And we are in the process now of pulling together our credit research, our economic content, our structured finance content, that's offered through multiple platforms, and we've pulled that together into 1 offering with an agent layer over top of that. That Has -- it creates a lot of utility and the ability to see things from our content estate that we haven't -- our customers haven't been able to access. So in the second half of the year, we're going to be moving a lot of customers from simply the credit research platform to this, what we call kind of OneView platform.

That's one. Two, agent-ready data, AI-ready data. We formed a sales SWAT team at almost every major financial institution or bank. We're having dialogue about how can the bank consume more of our intelligence, our credit models, our credit research and our company knowledge graph and consume that into their own AI platform and third-party AI platforms, whether it's Rogo, Hebbia, Claude, Teams, OpenAI. And so that gives us a commercial opportunity and also an opportunity to embed our content much more deeply across the institutions. So that's two, and there's a lot of interest in that. We have a very nice pipeline. Three, in insurance, we have a set of product enhancements, high-definition models, continuing to migrate customers from on-prem to our cloud platform. That's a great pricing opportunity for us and cross-sell opportunity.

We're also leaning into casualty. That's an area that's behind the property space, and we're bringing real science and analytics to the casualty space. And then last, I would say, banking. So I know the narrative is that software is dead or dying. Our fastest-growing product at the moment is our loan origination software that we sell to kind of Tier 2 and Tier 3 banks. We had close to 20% growth in the first quarter in that. And we have a kind of an agent layer that sits on top of that. And so we're experiencing really nice growth there. And we're also taking the agentic capabilities that are in that lending suite, and we're also providing those on an à la carte basis to banks wherever they want it. So if you want to consume simply our automated credit memo agent, you can consume that into your own AI workflow. So there's a number of things that are kind of contributing to growth across the portfolio.

Okay. So you recently brought in a new head for the MA business, which was kind of an interesting choice, someone that didn't come from a traditional financial background. I'm curious what is the signal for how you want that business to evolve and are there 1 or 2 things that you think are very important for her to accomplish in the first couple of years?

Yes. If you didn't see the announcement, we have hired Cristina Kosmowski. She was employee something like 200 at Salesforce. She was one of the founding members of their customer success organization, which was a pioneer in the industry, 15 years at Salesforce culminating in running what they call customers for life, which was all of the renewal and upsell, which is extremely relevant for us because we have very broad penetration across the banking segment. The real issue is reducing buying frictions for banks to be able to consume more of our content.

She then went to Slack and was part of the team that rolled out enterprise go-to-market Chief Customer Officer, when they went from $90 million to $1 billion and then was at LogicMonitor for 5 years of Vista backed company. So what I was really looking for, Christian, was -- I know the Capital S in SaaS is a dirty word right now, but the as-a-service, that model, that business model is extremely relevant to our industry. And at Moody's at the analytics business, I think we have a fairly complex product array, and we have had predominantly field sales and we found that there's a gravity to that selling model when you're at about $4 billion in revenues, right?

And you've seen a little bit of a deceleration in revenue growth because it's hard to sell a complex product array and without a well-developed partner channel. And so Cristina is coming in to run a different playbook, to help simplify the product, the pricing and packaging to help us think about how to engage differently with our partner ecosystem and to be able to really, I think, help reposition us and to capture this opportunity that's in front of us. I wanted somebody that was different that had a different skill set. And I'm having dinner with her right after I'm done with you, and we're going to be talking all about this, and I'm very excited about it.

You sound good, for sure. A question on just MA around regulation. Historically, that's been a catalyst for incremental demand of some MA products. As we're in a "deregulatory" environment, how do you think about that as a maybe headwind for that business?

And you're right, Christian, there has been -- we have benefited from regulation. Interestingly, we just sold our regulatory reporting solutions business in banking. We didn't have a lot of cross-sell. Some of that was still on-prem and it's in a good home. I would say that one of the probably not well understood enough value props of what we offer across MA, and I think I touched on this, but there have been a lot of meetings today. So I'm losing track. But our models and our data are heavily credentialized with regulators, not necessarily endorsed by the regulator. But I mentioned earlier that when the lender comes in and looks at the loan tapes and they know that you're using the Moody's credit models or the Moody's stress testing solutions and Mark Zandi's economic forecast to do their own CCAR. Most major banks use our solution.

There is a power in that credentialization that from across the franchise definitely in the credit franchise, right? There's real strength and safety in using Moody's for credit and the same is true in insurance, as I just talked about. And I think the same is true generally in KYC. I mean how many times do you think regulators come in and done an investigation and an examination of a decision that a bank made and realized that they were using Moody's data, right? And they want to see the data. They want to see the source files. They want to see the -- right? And we are able to provide the traceability and the auditability of all of that. And so I think that's not to be underestimated how powerful that credentialization is across the franchise.

Okay. Let's talk about sort of margins in MA. You've done some decent amount of margin expansion in...

Just like typical equity analysts, decent margin expansion, that's what I'm going to get.

The context though is over the last 5 years, the business has nearly doubled in revenues. You've gone from 80% subscriptions to 95%. It is a business that should have structurally much higher margin. So what is holding back sort of get into maybe like a 40% type margin number in that business?

Yes. So you can see we're well on our way, right? We're making very steady progress. You see our guide for the year here and you see our medium-term targets. So we're getting there. and we have increasing confidence about our ability to get there because AI -- I get asked sometimes are we making enough investments? I think so for sure because we're also creating a lot of investment capacity as well, right, by getting more efficient with our product development life cycle and leveraging agentic coding and things like that. And we're able to harvest some of that to make investments and then give some of that margin back to investors. I'm going to come back, Christian, to a little bit to the complexity of the model, right?

What we have been working on has not -- I don't want to sound defensive, and I'm not looking for kudos. But we don't have 5 different divisions. I have ratings and then I have everything else. And we have been working on pulling all of that together and bringing together 13 different tech stacks and going to 1 sales force and creating a platform layer under our applications and that has taken a lot of work. There's a lot of cost in that complexity. And so we've been going after that. And as we've been -- we've been making progress on that, that has been also contributing to our ability to start to get some margin and I think Cristina, as she comes in, is going to be able to continue that.

Okay. Let's move to your ratings business believe it or not, that is your actual biggest.

Took a while to get to ratings.

That is the actual biggest business that you have. Maybe just talk about 2026, your revenue guidance is notably much more constructive than your main peer. Maybe just walk through how you're thinking about 2026 in terms of the building blocks to get there. There's clearly a lot of tailwinds. So curious also balance between tailwinds and risks.

Yes. And we didn't change our guidance in the first quarter. And obviously, we had a war break out, and we had a SaaSpocalypse and all sorts of stuff. But like last year, right, we had Liberation Day and tariffs, and we kind of lost April, we did change our guidance, and I wish we hadn't because ultimately, we came in right where we thought we were going to come in at the end of the year. And it was interesting, we had a stat that something like 80% of U.S. investment-grade issuance in March came in 6 days. And that's an extraordinary stat because what that tells you is there's a lot of financing demand but we had these risk off windows, right? We had all these headlines about the war. And so you had all this issuance supply waiting to hit the market.

And when there was a risk on day, boom, it hit the market. So I think our view is it was too early to make an adjustment. And the market is pretty constructive right now. Spreads have come back in since the start of the war. I think we've been surprised at how resilient, I think, the economy and the markets have been. We've seen really strong hyperscaler issuance in the first quarter. I don't think we're done with that. And what we haven't -- and we've seen M&A pick up, right? And we had called that last year, and we were mostly right. It just -- we lost a quarter and we saw the M&A pick up in the back half of the year. That's continued into this year. What really hasn't picked up full steam yet, and you asked about some upside.

And I always say to people, it's this private equity exit and M&A cycle hasn't really kicked into high gear, right? And when it does, it is a very virtuous commercial cycle for us. Because oftentimes, we'll get multiple commercial opportunities from this M&A and leverage finance activity and loans go into CLOs, and we rate the CLOs and all of that. So that, to me, is still an upside. The biggest risk, I'm not going to give you any great insight here. It's just it's hard to predict what's going to happen and what the headlines are going to be and whether we go into one of these risk-off periods. Our guidance doesn't really take into account a risk-off month, right? So I think that's something for us to watch. But right now, the markets are quite constructive. And so I continue to feel good about it.

Okay. Let's talk about one of the tailwinds, just AI-related issuance. Maybe just talk through how to think about the economics of this in terms of the business. How ultimately it's monetized between frequent issuers, nonfrequent issuers. And if issuance of sort of like hyperscaler debt has an impact on ratings, margins or economics over time?

Yes. So there's a number of different ways that all of this AI infrastructure build-out is being captured in ratings. And of course, that's with pure hyperscaler issuance. It's with data center issuance. So that could be project finance or CMBS or structured credit. We're also seeing it with our utility and power issuers. And so there's a variety of -- there's a lot of issuance that's going on that's related to this. There's a lot of focus on the hyperscalers in particular. And we mentioned in the first quarter that we had already seen almost as much of our full year expectation for issuance from hyperscalers in the first quarter. And we don't think that they're done. So I would say a couple of things, Christian, just as we think about the economics of that and how that rolls into the business.

In general, investment -- frequent investment-grade issuers are on a little bit different pricing construct than infrequent issuers of debt. And that's not surprising. That's the same kind of model you see in many industries where you have high volume, right, and you ultimately start to achieve discounts when you have high volumes. Same in our business. And so the hyperscalers who have been very cash-rich companies have issued a lot of debt and over time, have taken on the profile of what looks more like frequent issuers. So when we have a lot of investment-grade issuance from frequent issuers, including banks, we call that revenue mix unfriendly. It means that the issuance growth would be higher than revenue growth when that happens.

When there's a lot of spec grade issuance or issuance in things like CMBS and CLOs, complex asset classes, that's revenue mix friendly, where you would expect transaction revenue growth to be faster. We're getting both of that from AI. With the hyperscalers, we're getting a frequent issuer and with some of the data center build-out and some of the -- it's flowing in other places of ratings, where it's revenue mix friendly. But in general, it's one of -- but this is not a one-trick pony. It's one of the medium-term funding drivers that we feel very good about. I'm happy to talk about others, but it's not like if this AI CapEx bubble burst. There are a number of other major drivers of funding around the world that are supporting our business.

Okay. Perfect. Let's talk about another tailwind, which is private credit. Despite all the news, it was a big tailwind for you in the first quarter, I think, growing 80%, if I read the transcript correctly. Can you remind us again how you make money from private credits? And then given all the noise we're hearing in that ecosystem, how does that inform your outlook for that business?

So I've made some progress because Christian just described private credit as a tailwind and 3 years ago, when I would do these investor meetings, this was the #1 topic, and there was lots of investor concern that we were going to be disintermediated. The public markets were being disintermediated and in turn, Moody's was going to be disintermediated. And in fairness, we were a little slow on the draw, right? Because we -- I don't think we had a full suite of methodologies and all of the engagement with the private credit community. And so we were slow in the draw. But we understood that, that market was going to need independent credit assessment even though a lot of times I heard that was not the case, and I think there's a much broader understanding now of the benefit of third-party credit assessment in some form of transparency.

It will look different in the private markets than public markets. But there are needs for investors to have a better understanding of the credit profile of what they're investing in. And we have a very extensive relationship with the big private credit players. And when we talk about we created the language of credit risk and the benchmarks and the data and the scorecards that helped investors to be able to compare and understand credit risk, public credit risk across asset classes and geographies, and we can play the same role in private. That is our job to help investors understand credit risk, whether it's public or private. And shame on us if we were slowing the draw on private. And so what did we do?

We built out methodologies and teams and go to market. And we really see private credit rolling through the rating agency and structured finance, so this is asset-backed finance and fund finance. Fund Finance is a booming $1 trillion ecosystem, lots of demand for credit assessment there. We don't play nearly as actively in the direct lending market. Now what we have seen is loans get originated into the direct lending market and then come back into the public markets because the public markets are typically cheaper. And then we've also seen a lot more investor demand for our credit scoring and assessment capabilities.

And remember, I was talking about we have these incredible credentialized credit models. Turns out those are very valuable for understanding middle market credit risk and to be able to help investors understand that. And so we've seen more and more demand from investors who say, "Hey, I'd like to -- it may not be a rating, but I'd like for Moody's to be able to give me a probability of default, maybe mapped to a credit rating to help me understand, give me a third-party view of credit risk." So I kind of say it's a great time to have the world's best commercial credit franchise because there's a whole new segment of the market that's originating and investing in credit.

Right. How do you think about competition in ratings, particularly around products and middle market credit rating with some of the smaller agencies maybe public about just attacking that space. So maybe over the next couple of years, is that a particular area where you're monitoring share dynamics?

Yes. So after the financial crisis, the competitive landscape in structured finance ratings changed, and it -- I think it changed permanently. It was a 2.5 agency market, something like that, and it is now kind of a 6 agency market. And particularly, there's more rating agencies in the more transactional parts of the market. This is plain vanilla asset-backed finance, where the transactions tend to be the same. And you'll see rating agency rotation going on. You don't see that typically in the fundamental space. That has had very little change since the financial crisis because it's a much, much more relationship-driven part of the business, where we've rated these companies for decades, literally decades. So we do see a more active competitive environment.

That's been true in private credit as well. And I guess the 1 other thing I would say, Christian, is the coverage levels, you would think of it as market share, we call it coverage. They ebb and flow much more so than they do in the fundamental space. There are times where we or one of our competitors will make a methodological change, and that will be informed by for us will be informed by historical default experience and other things where we'll say, it's time for us to update our methodology.

And there are times where we may provide an update to the methodology and the market may move away from us. And that's where you have to have the conviction in your beliefs. And I say that there's a cost sometimes to having an opinion. And I think we came through that financial crisis and realized the #1 asset we have is trust, and we never want to violate the investor trust. And so there are times where we take a different view than others in the market and the issuance may move away, and that's the cost of having an opinion.

Let's go back to the top of the house from right here and just think through margin and investment appetite. Clearly, you've done fairly well, margins are -- have improved but as you invest in AI, I imagine platform reorganization, you brought in the new MA CEO. So she might have her investment priorities. How do you think about balancing continued margin expansion versus just investing for growth?

So 53% margin, rating agency in the high 60s. I do get asked, can it go higher, right? But we've done a pretty good job of driving operating leverage into this business. And Christian, I -- again, I continue to think about you want to make sure that you invest in this moment. But at the same time, there are so many opportunities across our company, and I'm sure many other companies to be able to drive efficiency. And we -- and AI is part of that. It's not the only part, right? They're good old-fashioned ways of becoming more efficient, but AI is definitely an accelerator and customer service was one. We don't have a huge customer service organization, but that was an early easy one. Our product development life cycle is a much bigger one.

This is how we develop product between product and engineering teams. And we're obviously not an AI-native company. So we have to transform the way that we develop products, right, from people writing code, that's how we have done it to agents writing code and humans checking code and that kind of thing. So we're well down the path of overhauling our product development life cycle across -- our engineering teams are smaller in ratings, but we've done that and then in MA. They're much bigger -- there's a much bigger efficiency opportunity. And some of that efficiency, we're going to harvest and invest where we need to invest, and some of that efficiency opportunity is going to go into the margin and go to investors.

That's one place, and we feel very confident about it because you can very clearly see the efficiency metrics and know that you can get savings, not only savings but we can get increased cycle time. This same is true in ratings. There's less headcount in ratings, but I just sat down with our ratings operations team the other day, and we were going through how many checks we have to have before we put out a rating, and we have a team that does 4 eyes. There's 2 different human teams that do the checks because we can't always get the first team to get all that right. And so we went through, we automated something like 1/4 of those checks with agents and we were immediately able to see some very significant savings in terms of time and improvement in QA and the team already said, "Hey, we're going to be able to pull out x number of people out of this process. Some we may be able to use elsewhere right? And in some places not." So there's a lot of opportunity across the enterprise, I think.

Good stuff. Let's talk about acquisitions. I would say Moody's generally seen as good acquirers, Bureau van Dijk and RMS, bringing a firm, you are embedded into the company, grow it much faster. Just curious in this AI world, the need for proprietary data, your own balance sheet capacity. How are you thinking about M&A here?

Yes. Those were 2 really important acquisitions for us in terms of the capabilities that it brought to us. And the ability to monetize those content sets across the broader customer base. So I'd say that's one thing is if you think about this massive content estate, this intelligence system, we want to be bringing content in to that intelligence system that is going to enhance the value of the system overall and be able to be consumed by multiple customer segments and serving multiple workflows, right? I want to be able to sell it many, many times. So that's one. And two, when looking at anything that looks like workflow or software, we're going to look very, very hard whether there is actually a proprietary data asset embedded into that software. In some cases, there is and it hasn't been monetized. And so those kinds of things will continue to be very attractive to us, where we might buy something not because of the software, but because of the embedded data asset inside of it that we think is uniquely valuable that we can monetize.

Okay. All right. Let's bring it all together and just think through the stock, clearly, stock has traded at a pretty healthy premium of peers for a very long time. So some of that compressed over the last year or so. What's your compelling case to investors as to sort of why Moody's should regain its premium valuation?

All right. So I'm going to start with -- we are anchored by one of the world's great businesses. And if you don't know ratings, I encourage you, I'm happy to spend more time with you and get to know it. It is an incredible business. That's why Berkshire Hathaway is our largest shareholder and has been for a long time. And it benefits from tremendous network effects and has fantastic medium-term drivers as we talked about. I mean, think about what the world has got to get done over the next 5 to 10 years. BlackRock said $68 trillion of infrastructure investment by 2040. And that's not just AI. That's bridges and roads and there's energy grids, energy transition, there's military buildups.

And there are enormous drivers for funding and fiscal -- there is very little fiscal space in sovereign balance sheets, right? So the public and private markets have got to get this done. And there's a real understanding of this. I was just in Europe last week at a forum on European capital markets. And this was what I was talking about. They said, "What do you think can happen with European capital markets?" I said, I assume they're going to have to grow substantially. You're going to have to figure out how to support capital markets growth because there's an enormous funding agenda in -- across Europe. And we are the way to play that. And we have a tremendous franchise and market position. So that's one. That is a fantastic business.

We started MA by monetizing the exhaust from the rating agency, the research and the ratings data. And as I said, we're now in a moment where it's like a renaissance in terms of a desire to understand credit risk. There's a whole new segment of the financial market that is originating and investing in credit. That is super exciting when you own a rating agency and the world's best credit modeling and data franchise. So that's the second piece. But Christian, now we're going to get to the AI piece. And in 2023, again, I said this is either going to be a threat or opportunity or maybe elements of both. But we're going to make this an opportunity.

We're going to capitalize on this because it must be an opportunity when you have a content -- proprietary credentialized content estate like we do. And so this is a fascinating time because it forces you to think about the real source of competitive advantage. My competitive advantage is not from building the best software. Our competitive advantage when it comes to the analytics side of the business is, I have the world's largest company knowledge graph. And I have this credentialized model and data estate and we're in the process of connecting as much of that as we can. It was interesting because at GTC, Jensen Huang, recently said that structured data is the ground truth of AI.

And his point was that over the last few years, we've all focused on the models, the frontier models, who have the best model this version, that version. We're now in a moment where and I wrote an op ed about this, I said, AI has a trust problem. I think people understand that, right, which really means that if you want to drive enterprise adoption, the AI has got to connect to trusted content and data. We call that decision grade intelligence. This is what financial institutions have trusted and relied on for years and decades, right? Our models, our data. And now we're pulling all of that together and I think we're in a moment where the world is realizing it's not just about the models. The models have got to connect to the data.

The first-party data sitting inside of institutions and intelligent systems like Moody's. And the other thing I'd say to this is, Christian, we're in a world where institutions want to understand the intersection of risk, right? It's not just I want to understand credit risk. That team understands the credit risk. Over here, that team will understand the operational resilience of this company. And it's a siloed view of risk across institutions. That is changing. Everywhere I go, people are talking about wanting to create a more 360-degree view of who they're doing business with, who they're making a loan to, who they're insuring, right? And that means that you have to make these connections.

And we're doing that. We are creating what I think of, ultimately, the core asset is a connected intelligence system where every model, every rating assessment, forecast, benchmark, insight is resolved to any given company and I can understand the relationship between that entity and that person and this building and that entity, right, and resolve it down to 1 company. That, I believe, is a uniquely powerful asset in an AI world. We are assembling a connected intelligence system that I believe will be an essential component of a broader AI ecosystem, right? It's the contextual intelligence layer that is going to be a required component of any AI ecosystem. And I think we're in the process of building that. The world is in the process of understanding what is needed in this AI ecosystem, right? And I believe that you put those things together, and I hope I'm making a compelling case for a premium valuation.

Good stuff. I'll let the audience to say that. So thank you very much for the time, Rob.

All right. Thank you.

Thank you for being here. For those of you who don't know me, my name is Manav Patnaik. I cover business and information services for Barclays. We're pleased to kick off day 2 for us, at least here with Moody's CFO, Noemie Heuland. Thank you for being here, Noemie.

Thank you.

Maybe, Noemie, I figured the best place to start would be, I think, last year when you came here, it was your first time in London and you just started, it's been about 2 years now. So maybe just some of your reflections and thoughts over the last 2 years. I know maybe when you first started, things were, you're in a nice stable Moody's company. Now things have completely changed, but just your thoughts.

Yes. It's always been pretty moving environment for the past 5, 6 years. So we're getting used to our first quarter being a little bit hectic. But it's been 2 years. I think we're fortunate to have joined at a very exciting time for Moody's. We have very strong momentum and deep currents in our debt capital markets across both the U.S. and Europe and Asia Pac. So Moody's has a big rule about the different dynamics between public and private markets.

A lot of very strong funding needs that underpin the demand for credit and ratings, AI-related infrastructure, maturity walls are very strong. So a lot of exciting -- and we've invested a lot in our Ratings business to support that demand. And on Moody's Analytics, it's been growing fast over the past 10, 15 years.

And we have now completed the integration of most of the acquired entities, and we're excited to join -- to have a new President joining to help us scale further and a lot of opportunities with our proprietary data sets. And I'm sure we'll talk about AI and what that means for us, but it's been definitely a very exciting time.

And on the culture side of this, as you said, I think in the recent note, Rob has been really imposing a lot of change and evolution and automation of a lot of things we do, and that's been just a great experience so far.

Got it. If I could just spend 2 minutes on the culture point. So firstly, on Rob, I mean, I think one of the things that have stood out, like you said, is the tech forward change, almost it feels like Moody's has gone through from what was traditionally a rating agency. So can you just elaborate a bit more on that on some internal anecdote perhaps and how that changes happened?

Yes. We -- I was surprised coming in 2 years ago, I spent most of my career in technology companies and Moody's was actually very advanced in the development of automation tools in both sides of our businesses, are really leveraging technology to improve what we do internally, but also how we serve customers and issuers.

We had rolled out, at the time, Copilot across the entire enterprise. And we wanted to really have everybody experiment with the tool, make sure they were familiar with it, how to get their workflow better and serve their customers better. And now we're at the phase where we're scaling a lot of those exciting projects.

So that was a pretty good surprise. Everybody was coding and using those tools, which I wasn't quite frankly expecting coming at Moody's. A lot of focus on continuous improvement. And I think that's been really interesting.

Got it. And you mentioned it here, but on your call, you introduced your new Moody's Analytics Head that you're bringing in. Maybe just a little bit more about here because I know when you first took over, you were also a little bit more focused on Analytics. So how is that going to work?

Yes, Christina Kosmowski, the new CEO for Moody's Analytics is joining in June. She has a very strong pedigree in a technology company. She is very strong in customer success and customer experience.

She is what we call customer obsessed, which I think is going to be really exciting for us as we are scaling and as we move into new territories with the monetization of AI, evolution in go-to-market, evolution in our partnerships, so that we're very excited about her joining. And we also had very stable leadership, very strong foundation, too, that she can build on. So quite exciting.

Got it. Okay, let's move to the business. Usually, with Moody's, you would think we'll start with the Ratings, but I'm going to start with the Analytics first. We'll start with yesterday's headlines around Claude putting out a bunch of new financial tools.

Initially, the whole sector, including yourself, sold off a bit, but then you guys rebounded because news broke that you guys were providing some of the data. So let's just start there specifically, if you can just give us some details on what that...

Yes. We have a partnership strategy with a lot of different providers, including Anthropic. About a couple of weeks ago, we announced that we have an MCP app that is available on the Claude desktop environment. And what an MCP app is if you think about our content, our proprietary data, our insights and models, we typically have distributed those in the past through data dumps, SaaS platform, APIs, too, for customers to be able to consume those data sets directly in their environment.

It's just a natural evolution of that where we now have enabled customers who are using Claude or OpenAI or other large language model to consume that data directly in their environment to remove some of the friction associated with having to log into a separate website and get the data dump and then replug into the Claude or OpenAI or other environment.

The MCP app with Anthropic is a step further. It's actually our -- and you can also have our own data separately but you can consume in the desktop environment, in the Claude environment, the automated credit memo agent as well as the KYC agent, which are pre-configured workflows.

And that, what this does is it really synthesize, organize the data that you're consuming in those environments and also enables you to be more efficient in your token consumption, which I think is a very strong advantage for our customers.

You will see us including more agents in this MCP app, but that's the first step, and I think that was well received by customers. We have our customers in pilot phase who are actually paying to use those tools and getting some significant efficiency gains as a result of that.

Got it. And in terms of the content that you're providing, including yesterday, like what all content is available through these MCPs or MCP apps?

So the MCP, if you think about a traditional either an API feed or an MCP, most of our content is available, if you think about just the MCP app, which is the agentic workflow that we have built over the past 2 years, the automated credit memo agent and the KYC agents are available today on the MCP app that is fed through the Claude environment, and we expect to release more of that.

Got it. And talking about efficiency, token usage, et cetera. Maybe just taking a step back, how should we think about the revenue model or the revenue sharing, whatever it might be today when you signed these agreements?

Yes. A couple of things I'd say, and it's early days. I think we are all thinking with our partners about how best to monetize the opportunity. We keep the direct relationship with the end customers. So there is no revenue share agreement yet. We're not a subcontractor of those large language model providers.

Our customers have a direct licensing agreement with Moody's. And as a matter of fact, when they call out the agents or the data, you could see the Moody's branding and interface and that directs you to our environment. So that's the first thing I'd say.

In terms of monetization, we have -- customers are paying a premium to access those MCP apps and content right now. What is likely to happen over time as we're getting the learnings from those early experimentation and early pilots is we'll likely have a flavor of a consumption pricing with our customers.

I want to be careful because our customers have told us, and we also like the recurring subscription-based revenue that is very stable and predictable. But we also want to account and benefit and make sure we monetize the peaks of data consumptions that are going to be resulting from increased usage and consumption of our content through those applications.

So you'll have likely a base fee with consumption-based pricing on top, but we're still experimenting and getting some learnings from those pilots.

Got it. And obviously, we talked about Claude and Anthropic, but are you LLM agnostic? Just can you talk about some of your other partnerships and strategies?

Yes. I talked a bit earlier about our historical distribution channels where we had either a direct API feed to our customers' environment. If you think about large banks, they've always consumed our content through their own applications.

If you go move up, down the tier a little bit, you have our customers in Tier 2 and Tier 3 banks who are consuming our content together with prepackaged workflows because they don't have the IT firepower to build their own things themselves.

So we're -- we've already had a pretty agnostic distribution channel depending on where the customer is in their journey and how they want to consume our content, and that will continue to be true with the large language models. We have partnership with Anthropic, OpenAI. We have a partnership with Microsoft and also AWS and so on.

Got it. Just to dig deeper on some of the moats that are either debated or that need some clarification. Maybe you could just help start us by setting up Moody's Analytics and the mix, the 3 different segments and what's in there?

Yes. So you have Decision Solutions, which is about 45% of ARR, so annualized recurring revenue. Now we -- 98% of Moody's Analytics revenue is recurring. So that's why I like to talk about the annualized recurring revenue as a good proxy for how we think about the business.

Decision Solutions has been growing the fastest. This is where you have the workflows for banks, insurance as well as the KYC. So for banks, the flagship product is our CreditLens offering, which has grown in the high teens in the recent past.

That is what I referred to earlier is for Tier 2 and Tier 3 banks to perform loan origination workflows all the way from underwriting to portfolio monitoring and so on. We have our insurance models, our catastrophic models that are fed on industry claims data over decades.

So it's really proprietary models based on data that we have curated over time. And then KYC workflows that leverage our Orbis data estate as well as politically exposed people database. So that's in Decision Solution.

In Research & Insights, we have -- which is about 29% of the ARR. This is where you have CreditView, well, now called Moody's View, the models, ratings, probability of default model, economic research that is used by banks to do their stress testing. And the models have been calibrated over a decade by give-to-get data consortium, so very proprietary as well.

And then Data & Information for the rest of the ARR, which is where we have the pure data feeds from the rating agency as well as the rating -- the data feeds from Orbis that we feed into our clients' environment directly.

Okay. Let's start where you ended then. On the Orbis data set, there is some debate there because a lot of the raw data is available publicly, but then there's some partnerships, some licenses. So can you just help us sort through all that nuances and why you think that's still modded?

Yes. If I think about Orbis, so Orbis is a private company database that has over 600 million records now. That's gone from 300 million when I joined. So we continue to invest and expand the coverage and the breadth of the data set.

I'll start with the first layer, which is the firmographic data, which is one could argue available more broadly on public sources. But we take that and we curate it and we make it relevant for your specific use case. And let me give you a few examples as well.

But if you want to know what is relevant for a particular entity that you're doing business with, you can use some of that firmographic data to be connected with the other data sets that are proprietary that you're using to make that assessment.

Then when you pass the firmographic. And by the way, if you think about what customers are tapping into when they go into Orbis database, we have a lot of data into that. This is not so much for the firmographic, that's a small portion of it.

The majority is for what I'm going to talk about next, which is the curated, corporate hierarchy mapping that is we spent decades curating those and we have license rights and IP agreement with registries in about 800 jurisdictions. So they have -- we have license rights, we have IP.

And then we take that raw data from those registries and we contextualize it. We -- semantic definition is also important. A dissolution doesn't mean the same thing in Germany as in other jurisdictions. So we want to make sure our customer ingests and have context around those data sets.

And some of these data licenses that you talked about, so one of the debates, obviously, is LLMs can get the data and do it. But are your license partners opening the data up more?

No. Actually, that's the interesting trends that we've observed over the past couple of years. These registries are reducing the number of partners that they're monetizing those data sets with. And again, it's not just about the raw data. It's about all the context that we have built on top of it.

The entity mapping, the corporate resolution, that's very important. And if you think about the use cases for those data sets, it's - if you, Barclays, wants to do a KYC, you don't go with good enough data that you scrape on the web, right? It has to be auditable, traceable, documented.

And then we have auditors of our customers who come in and audit our data sets. And so that's, I think, where the value is beyond just the context that it provides. It's also a trusted content that's been trusted for decades.

And the corporate hierarchy aspect that you pointed out, that's why people come to Orbis more. My understanding is right now, LLMs are not good at doing that. But is the moat there more the context that you just provided?

It's the context layer that we bring on to give you all the associated risk aspects or corporate links for a particular given entity. I think Shivani, my IR lead, has a great example that I think is very powerful.

We -- a few years ago, there was a school district in New Jersey who was using a bus company registered in California. And that company had a linkage a few layers above by a Russian oligarch. So they won't allow to do business with that particular party.

And that, the Orbis was the only way for that school district to find out. And that was actually a very strong argument for why large language models or other public sources cannot go into that level of detail.

Got it. Just one layer back that I thought about was I think whenever Claude or one of you guys put out a tool, they think, okay, they're coming after our space. But when you guys partner with them, I mean, they are partnering with you, right? So what does that discussion look like? I mean they need you to help.

Yes. They don't have -- so we don't train those large language models with our IP. That's a very important part. But they -- if you think about what a large language model does is it provides some workflow support on actual context and data. Those large language models do not have that contextualized information and data that we have. And so I think that's a natural partnership for us.

We're not also trying to compete in the UI or front office. That's not what we do. We pride ourselves in having trusted what Mike and Rob like to call decision grade data sets and insights that then get used into different applications depending on where you are in your journey. So that's where our strength is. And again, we're not trying to compete in the front office or UI space.

Got it. If we can move to Decision Solutions, when you were describing the subsegments, you mentioned workflows a lot. Nowadays, workflows is a risky word, I guess. So can you just help how moated are those workflows? Or is there something more to it than that?

So I'm going to go through the main ones. Lending in banking. We typically cater to Tier 2 and Tier 3 banks who are looking to automate their loan origination systems. We acquired a company called Numerated about 2 years ago that had some AI native embedded feature like spreading financials, automated credit memo and things along those lines.

So we've embedded now all the Numerated capabilities in our lending package, and we gave some stats about customers upgrading from the legacy package into the new one with a pretty significant price uplift. That's a product that's grown in the high teens. It has a very strong retention rate. So we feel pretty good about lending.

If you think about lending and credit underwriting, you don't want to be the one who are using a third-party large language model or an unverified source to come up with your assessment and have this come back and bite you later on. So I think we -- and again, we are audited by our customers. Our solutions go through a very rigorous regulatory and audit process, and I think that's very important.

Then I move to insurance, which we have -- the main one here is the climate risk assessment models. And again, this model or these models are -- could the AI come up with a model, sure. But the model is fed on data that comes from the industry, industry claims data that we get to train and inform our risk output.

And again, that's used by insurance to do their risk underwriting. So very core to the business of the insurance company, very core to the front office and growth of those insurance companies.

And then KYC, this is more like a pre-configured workflow to perform KYC checks, leveraging our Orbis database, leveraging our politically exposed people database as well. And again, if you operate in a regulated industry, you want to make sure you have the right tools and workflows and auditability, traceability.

How did you come up with the decision? Where is it recorded? What is your justification for making that decision? And the regulator comes in and audits that. So I think that's also another area where we feel quite comfortable.

Got it. On the KYC, we get a lot of questions, too. So maybe first on the data side. You already talked about Orbis, but can you talk about the politically exposed PEP data set, like how important that is, how differentiated that is?

Yes. This comes from an acquisition we did a few years ago. We've continuously enriched that politically exposed database. I gave an example earlier about how powerful that was in identifying sanctions and -- sanctioned individuals.

After the Russia invasion of Ukraine, we had a lot of interest and demand for that politically exposed people database because again, if you operate in a regulated business or even you're looking at supply chain or vendor risk management, especially with DORA and things like that, you want to make sure you have a clear understanding of who you're doing business with from a third-party risk standpoint.

Got it. And then in KYC as well, and maybe it's a broader question, right? But the view is AI can scour the web, find out who's exposed, whatever it might be. But those tools that can be more efficient, are you guys using those tools to make yourself better disruptive...

Yes, we are actually using it in our procurement department now. So for our own customer and front office, we're using it. But we're starting using it now also in vendor risk management. As you know, we operate in Europe. We are regulated by DORA, so we have to comply with those regulations. And our tools actually help us do that more effectively.

And just to round up the segment then, the Research & Insights part of it, I don't think there's any debate, it's your ratings, research proprietary, but anything else you would...

Yes, credit research. The other thing I would say, we hear a lot about economic research, which is a part of it, but hey, economic data, you can find this on the web and other publicly available sources.

The one thing to note though is those economic forecasts and research are used by banks to do stress testing. So if you listen to Mark Zandi, who's our Economist at Moody's Analytics, he's very careful about -- when he talks about recession odds and other risks from an economic standpoint because he knows that the minute he passes a certain threshold, this is going to be used by banks to adjust their stress test. So it's pretty serious, again, things that we think is very valuable.

Got it. Before we leave the segment, since you are a CFO, I got to ask about margins. Can you just help us with -- since you've come, of course, the trajectory has improved. And just remind us of your goals and how you get there and some of the moving pieces.

Yes. So Moody's Analytics margin, we have a medium-term target that's by the end of 2027 to be in the mid- to high 30s. We're well underway. We have made some significant improvements again in the first quarter.

We started at about 30-ish percent when I joined. That was after a lot of the acquisitions that we had made, investments to be ready for AI and make sure we had the right, again, context layer in our data.

We've improved significantly. We're now in the 33% range, and we're again aiming to be in the mid- to high 30s by '27. We've about 150 basis points improvement again this year. And we're doing that by -- there's a few things that are going on in MA, and not a lot of it yet has to do with deploying AI at scale in that segment.

So there's a significant opportunity beyond that. It's really about resource allocation. We came to the realization, we had acquired -- ingested and integrated most of the entities we acquired. We simplified the operating model. We looked at having one product organization, a go-to-market and make sure we have the thoughtful allocation of resources to drive areas of growth in lending, KYC and data.

And so that's really what's been driving the growth. We also have deploy AI and customer support, as you would expect, a pretty obvious use case at first that has allowed us to get some efficiencies. And we're looking at product development life cycle, all the engineering and product development with AI, and that's very promising.

Got it. Maybe let's use margins and shift into Ratings. By any measure, Ratings has very impressive margins. But it sounds like AI could help improve that even. Can you just talk about Ratings?

Yes. Ratings is operating right now at about 65% margin. I mean, we -- what we say, like to say is being volume agnostic. We have a medium-term target in that ballpark. But we, obviously, if you have a year like 2022, where revenue went down 33%, you're not going to make it up through the efficiencies and the automation.

But we're trying to be volume agnostic within a certain band of issuance, and we do that by -- and they started way before I joined, actually, we have automated a lot of their workflow that an analyst go through before the actual human rating committee and assessment happens, things about like spreading financial statements, getting data from different sources, putting those into the methodology template, running all those workflows has been really automated such that the analysts can spend a lot more time talking with issuers around what's happening in the sector.

And last year during around Liberation Day, we had a peak of demand for our analysts to really make sense of the noise beyond the headline. So that's really what's been driving a lot of the margin expansion. We are continuing to invest, though, in Ratings. There's -- I talked about all the funding needs and the currents in the market.

We want to make sure we have the analytical capacity and skill set to address those demands. And as you can imagine, it's a long-term workflow -- workforce planning. You don't switch on and off and adjust the analytical skill set overnight, but we've been able to increase the load of our analysts by automating a lot of the processes that precede the time where they sit down together and think about the rating.

Got it. If you can just touch on issuance and trends and so forth, maybe first on a high level before we touch on a few specifics. But if you could just help us appreciate what happened last quarter and what the current trends look like?

Yes. We had a very strong quarter in Moody's Ratings for -- and I'm not going to repeat, the data from the first quarter. But hyperscaler issuance was very strong. The 5 hyperscalers have issued as much debt as they did in 2025, and we expect this trend to continue. So that was a strong driver for investment-grade issuance in the first quarter.

We had, interestingly, in terms of if you think about the macro environment and the geopolitical disruption, in March alone, 80% of the activity was concentrated in 6 days. So what this tells you is when the markets are open and when it's a risk on day, there's demand and transactions happen and there is no constraint.

We'll have to see how that evolves, but that was a very strong driver of growth. In the first quarter, M&A activity was also very sustained in bank loan. We talked to our banking partners again recently, and they see a very strong pipeline of M&A transaction. So that's -- we're pretty pleased with the growth in our Ratings business in the first quarter.

Got it. And on M&A, I know in the prior years as well, there's always been fits and starts, clearly. But how have you -- what have your assumptions for M&A been for the year? It clearly seems like AI, there's upside, but on M&A, how do we think about it?

Yes. We've guided to about 40% -- we've considered about 40% increase in announced M&A. So that's our assumption. Before we came to the market in April, we looked at -- we talked to our banking advisers, and they haven't seen a slowdown in the pipeline.

So we've hold on to that, and we saw a very strong first quarter in that regard. I think the -- we always talk about pent-up demand in M&A. We've talked about this for a while. Our Rating Assessment Services, which is a leading indicator for M&A.

So an issuer comes to us ahead of a transaction and says, if I do these types of financing or if I structure the deal that way, what would that impact be on my ratings? And that business has been performing very strongly in the second half of '25 and again, first quarter. So that's again a good leading indicator.

Got it. Private credit, obviously, another big topic out there. Maybe just a high level from all your insights at the rating agency. Is this just a headline issue? Is this a potential systemic risk, structural risk? How do you guys look at that?

So we -- you're referring to a few idiosyncratic events that have a lot to do with fraud or other types of considerations. We -- private credit has been a strong growth driver for us of a very small base. We rate about $80 trillion of stock of public debt. So private credit is much lower than that. As you can imagine, it's grown 80% in the first quarter.

And I think what those headlines bring is a flight to quality, requests for transparency, signposts, indicators and benchmarks, which we are very well positioned to provide. We have a lot of interaction with the private credit players.

As a matter of fact, we had 2 credit conferences in the past 2 weeks, 1 in New York and 1 in London, where we had prominent leaders in private credit speak and interact with Marc Pinto, our Head of Private Credit for the Ratings franchise.

And you could see really, there is demand. We start to see insurance companies for those guys disclosing how much of their portfolio is actually rated. So there's a demand from investors about signposts and quality, which I think we're well positioned to serve.

Got it. And I know you've talked about as a company focusing on private credit across the company. On the Ratings side, it's pretty obvious. It's the different categories. How do we think about private credit and the opportunity on the Moody's Analytics side?

Yes. We provide credit. I talked about the credit assessments and the credit models that we provide. So we provide that as well if a joint investor who want to know the quality of the loans you're invested in or the fund you're invested in, we provide that for Moody's Analytics as well. And that gives us the opportunity as those players scale to come and potentially rate those transactions down the road if there's a need for a rating.

Got it. And I think one of the initiatives, and there has been a partnership with MSCI. Can you talk about overall, what that entails and how that's going?

Yes. The partnership with MSCI that we concluded last year, we come in with our probability of default models, our credit estimates and then they have the best, the most comprehensive database of loans. So we combine those 2 to provide a probability of defaults and credit assessments on those portfolios. And it's a revenue share agreement, and that's going pretty well.

Got it. And is there another leg where they could do private indexation on the Orbis data set?

That could be -- we're exploring different avenues on the partnership, and that could be one.

Okay. Got it. Maybe in the last 5 minutes or so, just let's talk about capital allocation. Actually, one step back, on the Ratings, just to wrap that up, there's always a lot of different moving pieces. There's a lot of focus on the forest versus the trees. Maybe you can just remind everyone of the long-term model for Ratings to wrap it up?

Yes. So it's a business that if you look over the cycles, that's grown in the high single digit -- mid- to high single-digit over time. Obviously, there is years like last year where it was significantly higher and this year as well.

But the algorithm, first and foremost, GDP is the first pillar of that -- first block of that algorithm. It fuels asset formation. So you take GDP growth, then you have the value that we provide to issuers, and we've recently updated our study to show the savings on the coupon for an issuer that has a ratings versus a bond that doesn't have a rating.

So that's 2 or 3 percentage points. And then the last 1 to 2 percentage points of emerging market trends. So here you have a contribution of private credit, domestic market.

We have investments in Latin America, Asia Pac and affiliates to serve those domestic markets that are going to be very important in the next decade. And then digital finance as well and other emerging trends to get to the high single digit.

Got it. Okay, moving to cap allocation, I don't think you've changed a whole lot, but just your approach and how you think about how capital allocation priority is set up?

Yes. First and foremost, growth. There's a lot of opportunities to grow both businesses, and I've talked about what those underlying demand drivers are, funding needs, the maturity walls are very healthy, understanding who you're doing business with, understanding the risk of climate-related events on your businesses. So we want to make sure we have investments for that, and we've been investing in acquiring companies in those different spaces.

In terms of M&A, obviously, very thoughtful. We have a pretty good record of strong return on those transactions. We'll continue to be very focused on that. I think the bar is raised. Obviously, if you have asked me a few month ago, whether we would be contemplating a very specific workflow for one area, I would have said probably yes.

Now it's maybe a bit of a different answer, focus on data assets and data coverage. And then the rest is capital return to our shareholders, and we just did $1.5 billion of buybacks this quarter in Q1.

Got it. Maybe just on the buyback. Obviously, you did a big number in Q1. Therefore, you upped the amount for the year. Just the thought process around there, opportunistic...

Yes, so we were very pleased with what we did in the first quarter to take advantage of the price to increase our buyback. We just divested our regulatory business, and we just closed that transaction on April 30.

So we'll use the proceeds to continue on our buyback program, and we'll continue to be opportunistic. I think the good news is we have a lot of flexibility in our capital allocation program because of our operating leverage and our profile. So first and foremost, growth, and then making sure we return capital to our shareholders as well.

Got it. I got one more. We do have a few minutes. If anybody has any questions, you can put your hands up. But just on M&A, I want to touch real quickly. You did mention while we were going to Moody's Analytics, a lot of what you built up has been through M&A. And so in the next, call it, 5 years, should we be expecting a lot more even if the bar is higher?

I think, again, we'll be very thoughtful. We have high hurdle rates in our M&A. There's a whole debate right now on whether software workflow makes sense. I would argue if it's deeply embedded in customer workflows, if it's a vertical that has a lot of value and efficiency gains for the customer with a lot of proprietary data associated with it, I think it's something that definitely should be looked at.

Data coverage, we just acquired a year ago, 1.5 years ago, CAPE Analytics, which is a geospatial data to be used by insurance companies to underwrite their risk on properties. And insurance actually isn't -- visiting an insurance company in the Midwest last year, and they love it. They really said that was something we were really expecting you to do.

So we'll listen to our customers. Some of those ideas come directly from customers in terms of data integration or tuck-ins. And so you would expect us to continue to do that.

Got it. I think you had a question. Just wait for the mic, if you don't mind.

I'd love to hear a bit more, so you get a lot of questions on MA and the moats there. But on MIS, I guess you get a lot fewer questions. I guess when we hear about you putting a lot of financial data and then the credit guys sit in a room, the obvious question is why can't Anthropic hire 300 credit analysts and do that? Can you just make sure we understand, is it the NRSRO certification? How do you think about the moats in MIS and why those are so impenetrable?

Yes, you're right to say it rarely comes up as a concern or question. I think people understand and appreciate the value of having the benchmark and the signpost for appreciating the -- assessing the credit quality of underlying loan.

I think we have experts who are called in and have a dialogue. So you talk about large language model and having the analyst crunching data. I mean, that's the, I would say, the relatively easy part of the job.

Where it gets really interesting and where the secret sauce comes in and what our issuers are telling us, and I was an issuer myself, so I interacted with our Moody's analysts as well, is really the depth of understanding of the historical trends of the sector. We have access to MNPI and things that, obviously, customers share with us. We do -- our analysts go on site visits.

You think about all those infrastructure projects, AI, data center construction, they actually go on site and look at the construction site and talk to the engineers, they have a really deep understanding of the business and not only what's happening in a given quarter or a given trend, but like long term, like what does that mean in the long term and the ratings, obviously, are not expected to move from one quarter to the other, it's really that long-term view, and I think that's what our issuers value today.

We got time for one more. Otherwise, we can wrap it up, too. All right. Let's just leave it there then. Thank you, Noemie.

Thank you. Thanks a lot.

Appreciate everybody being here.

Good day, everyone, and welcome to the Moody's Corporation First Quarter 2026 Earnings Call. At this time, I would like to inform you that this conference is being recorded [Operator Instructions] The call is scheduled to last approximately 1 hour.

I will now turn the call over to Shivani Kak, Head of Investor Relations. Please go ahead.

Hello, and thank you for joining us today. I'm Shivani Kak, Head of Investor Relations at Moody's. This morning, we reported our first quarter 2026 results. The press release and today's presentation are posted at ir.moodys.com. We'll reference non-GAAP or adjusted measures, please see the tables in our earnings release for reconciliations to U.S. GAAP. Today's remarks may include forward-looking statements under the Private Securities Litigation Reform Act of 1995, please see the safe harbor language in our earnings release and the risk factors and the MD&A in our most recent Form 10-K and other SEC filings available on our website and the SEC's website. These factors could cause actual results to differ materially from those expressed or implied. Members of the media may be listening in a listen-only mode.

With that, I'll turn it over to Rob.

Hey everybody, and thanks for joining us. Q1 was a strong start to the year despite a volatile geopolitical backdrop. And Moody's again delivered sustained revenue growth across both businesses and powerful operating leverage as we continue to capitalize on the deep currents driving demand for our ratings and solutions. Now there are 3 takeaways for the first quarter. First, we delivered strong financial performance. Both MIS and MA grew revenues by 8% and disciplined cost management drove 150 basis points of adjusted operating margin to 53.2%. Together, this contributed to adjusted diluted EPS of $4.33 and that was up 13%. We returned $1.7 billion through buybacks and dividends in the quarter, and we increased full year buyback guidance by $500 million to approximately $2.5 billion.

Second, demand remains healthy across both businesses. And ratings issuance continues to reflect long-term funding needs tied to infrastructure, technology, private credit and energy transition even as volatility may affect timing. In analytics, engagement is strongest and our largest, most strategic relationships, which continue to grow materially faster in a broader MA base, and we have a growing pipeline of some of the world's largest financial institutions to consume our agent ready intelligence, and that's supported by further expansion with our hyperscaler and AI partners.

Third, we're executing on our strategic priorities. And when our intelligence is embedded directly into customer decision-making, we see tangible outcomes, higher retention, expanding relationships and more durable recurring revenue. And like last quarter, we'll share some specific examples of meaningful customer wins.

So now let me turn to what's driving performance. In Ratings, as I said, issuance remains anchored in long-term funding needs tied to AI-driven infrastructure, private credit, energy transition in emerging markets. And these are multiyear funding needs. They're not short-term cycles. And as I said, volatility may affect timing, but the underlying demand is structural. And that showed up clearly in Q1. In fact, in the first quarter, rated issuance surpassed $2 trillion for the first time, and that was led by near record investment-grade volumes, including several jumbo AI-related financings totaling more than $100 billion.

Private credit activity remained durable this quarter despite increasing credit concerns. As private market scale and come under greater scrutiny, demand for our independent credit assessment continues to increase, and that dynamic contributed to private credit related revenue in Ratings growing more than 80% year-over-year.

In Moody's Analytics, we're embedding our intelligence into mission-critical workflows, particularly lending, underwriting and compliance where accuracy and auditability and trust are essential. And to support that shift or expand how and where our customers access Moody's Intelligence. In fact, over the last several weeks, we announced a set of partnerships that significantly extend our distribution without compromising governance or independence, and through model context protocol integrations, Moody's license intelligence can now be accessed directly within enterprise AI environments such as ChatGPT Enterprise and Claude. And this allows customers to bring trusted Moody's content into their own AI workflows rather than relying on generic or unverified data.

With Anthropic for licensed users, our agentic credit and compliance workflows are now available natively inside the cloud interface through something called an MCT application. And that's the first of its kind as far as we're aware, and it enables users to access Moody's agents to perform analysis, generate outputs and trade sources without leaving the [ Claude ] environment. And by making our agentic solutions available through the AWS marketplace, we're meeting customers inside their existing cloud and procurement ecosystems, reducing friction by allowing customers to burn down their AWS commit when consuming Moody's agents and intelligence. And Moody's scaling workflow embedded distribution by launching a dedicated Moody's agent in Microsoft 365 CoPilot and making Moody's intelligence available as a grounding data source across CoPilot experiences. That's CoPilot Chat, Researcher, Copilot and Excel. And this brings trusted decision grade context directly into everyday Microsoft tools, extending access beyond specialist teams and enabling faster, more consistent, explainable and auditable decisions.

And importantly, these are bring-your-own license models. They expand reach and usage but preserve our direct relationship with our customer. And all of this sets up what I'm going to turn to next, which is how customers are using these capabilities today and how that's translating into growth and differentiation across analytics and ratings. So I'll start with lending and credit decisioning. And our AI-enabled lending suite continues to gain traction as banks modernize end-to-end credit workflows.

ARR for our lending suite grew 18% year-over-year, was driven by customers upgrading to an integrated platform that spans origination, decisioning and monitoring. And what's driving adoption is workflow integration and AI enablement. So the faster decisions, greater consistency, clear auditability. We're also seeing demand for credit assessment and workflow beyond banks with asset managers and even corporates. In the first quarter, we expanded relationships with 2 of the world's 5 largest asset managers, representing nearly $20 trillion of assets under management, the first signed an approximately $6 million multiyear deal to bring our decision grade intelligence to both public and private credit workflows, supporting risk investment decision-making at a global scale.

And the second asset manager signed a multiyear contract of over $2.5 million and adopted multiple Moody's modules to support front, middle and back ops credit and compliance workflows. It also represented our first structured finance software win with a trustee, which provides a strong reference for future opportunities. And in the corporate space, a global athleisure brand tripled its relationship with us and signed a multiyear contract for an automated credit decisioning solution that accelerates decisions from days to minutes. And these are all ways that customers are accessing what we believe are the best set of commercial credit scoring capabilities in the world.

In insurance, growth was sustained from continued demand for digitization via our intelligent risk platform. That included adoption by 1 of the top 3 reinsurers in the world in the first quarter as well adoption of our high-definition models. In fact, IRP cross-selling and upselling accounted for almost half of our insurance net growth in the first quarter. And that growth was also supported by our trailing 12-month retention rate of 97% which reflects how embedded we are in customers' workflows as what they call their primary view of risk.

In KYC and compliance, growth continues to be driven by scale, complexity and regulatory expectations. And I've talked before how these needs go beyond regulated financial institutions. And a good example is our first Moody's for compliance customer. In the first quarter, a global real estate firm spanning approximately 275,000 sites operating in more than 80 countries selected our enterprise-wide solution for counterparty screening and monitoring covering millions of entities handily. And we replaced a fragmented region-specific approach, with a single governed platform integrating ownership, sanctions, politically exposed people and adverse media representing both a competitive displacement and a meaningful expansion of our relationship.

And finally, let me turn to Ratings and digital finance. And as capital markets evolve, we're extending the same rigor and governance and independence that define our ratings franchise into new asset classes and new forms of market infrastructure. In fact, during the first quarter, we were the first rating agency to publish a methodology for stable coins, and that's an asset class that's expected to reach north of $2 trillion by 2030. And I'm excited to share that we already have a number of deals in the pipeline. We were also the first rating agency with blockchain agnostic capabilities to ingest data and publish ratings directly on chain. We're now live on The Canton Network, making Moody's the first rating agency operating a node in the privacy-enabled blockchain ecosystem.

And during the quarter, we were the first rating agency to rate an innovative inaugural bitcoin backed bond where repayment is secured by bitcoin collateral. So these are not pilots or proof of concept, they represent and reflect real customer demand for trusted comparable risk assessment as finance evolves, whether assets are traditional or digital. And taken together, this is what differentiates Moody's across analytics and ratings. We're embedding decision grade intelligence directly into the workflows and decisions that matter most, driving durable growth today and reinforcing the long-term strength of the franchise.

Now finally, before I close, I want to highlight an important leadership milestone, and I am absolutely thrilled that Christina Kosmowski will become Moody's Analytics CEO in June. And she brings a blue-chip Silicon Valley pedigree. She's been a pioneer in customer success and brings a track record of delivering high growth at scale, and her leadership materially strengthens our ability to accelerate execution in an increasingly AI-driven world, and I'm very excited about having her join us in June.

I also want to thank Andy Frepp for stepping up to serve as the Interim President and for his steady and effective leadership. And Andy has had a fantastic career with us for almost 15 years. He is deeply respected across Moody's. And in a brief period of time, he provided some real focus and business direction and has ensured continuity and momentum during a critical period. And we are tremendously grateful for his leadership and continued support through the transition.

And with that, I'll turn it over to Noemie to walk through the financials in more detail.

Thanks, Rob, and hello, everyone. Q1 represents a solid start to the year. And echoing Rob, our performance reflects disciplined execution across both of our businesses.

Let me start with Moody's Analytics. Our Q1 results -- [ so we're ] delivering against the framework we've discussed over the last several quarters, durable recurring growth, strong retention and margin expansion, while we reshape the portfolio. MA revenue increased 8% in the first quarter as reported or 6% on an organic constant currency basis, reflecting healthy underlying demand across our core franchises. Recurring revenue grew 11% as reported or 7% on an organic constant currency basis and represented 98% of total MA revenue underscoring the shift towards renewable subscription-based solutions.

As expected, transactional revenue declined materially, down 54% year-over-year, reflecting both the learning divestiture and our deliberate focus on scalable recurring revenue streams. This is fully consistent with the portfolio actions we've taken over the last several years to prioritize durable, high-quality revenue. ARR remains the clearest indicator of underlying demand and of the health of our future revenue base while reported revenue can move quarter-to-quarter due to timing effects and portfolio actions. ARR ended Q1 at $3.6 billion, up 8% year-over-year.

Decision Solutions continues to be a key growth engine for MA, representing approximately 44% of total MA ARR and delivering 10% ARR growth. KYC grew 13%, driven by deeper penetration within existing banking customers and expansion beyond financial services. Our new Moody's for compliance offering officially launched in April, and we have already seen success in prelaunch activity, as Rob highlighted earlier. We are building pipeline, with April renewals as the first cohort of upgrades, and we expect this revenue to build progressively through the year.

Banking ARR grew 10%, supported by strong adoption of our lending solutions, which grew in the high teens. We continue to see good customer uptake of our new package. Strength in lending was partially offset by more modest growth in the RAG product portfolio. Insurance ARR grew 7% reflecting sustained demand for higher definition models and cloud-based delivery via the intelligent risk platform, which is enabling the cross sell and upsell motion that is central to our strategy in this business.

Research and Insights ARR grew 7% year-over-year, driven by our flagship CreditView suite, now Moody's View and EDF-X with broader adoption across banking customers and deeper integration into customer workflows. Data and Information ARR grew 6% year-over-year and we closed several high-value agreements that illustrate 2 distinct, but reinforcing demand patterns for Moody's decision grade intelligence. The first is mission-critical workflows where precision and auditability are nonnegotiable. 2 government tax authorities, one, supporting national scale fraud detection and tax compliance across thousands of users and the other powering AI-driven tax risk assessment and transfer pricing enforcement, selected Moody's as their long-term data partner. In these environments, the consequence of error is too high for good enough. Moody's curated, auditable data, we believe, is the best viable choice.

The same dynamic plays out in financial services. A leading specialty insurer embedded our private company data and proprietary risk signals directly into its real-time surety underwriting workflows, replacing manual processes with automated point of decision analytics. The second pattern is front office and investment intelligence, where our data drives commercial advantage. First, as Rob shared, a major asset manager embedded our private and public credit risk data sets directly into its core portfolio platform to enhance credit modeling and surveillance across public and private markets. Second, a leading global professional services firm expanded access to our real-time information and research intelligence across thousands of consultants to sharpen customer advisory and business development workflows. Together, these wins reinforce that Moody's decision grade intelligence is becoming foundational infrastructure across both the risk and growth agenda of our customers. And across public institutions, financial services and global enterprises.

Quarterly retention improved to 96%. That's up 200 basis points year-over-year as the outsized government and ESG-related churn we saw in Q1 2025 has no left. On a trailing 12-month basis, retention was 95%, improving 1 percentage point versus Q4 '25 and within our historical range, evidence that our solutions remain mission-critical as customers modernize their workflows, including with AI.

Turning to profitability. MA adjusted operating margin was 32.5% and that's up 250 basis points year-over-year. We are well on track for full year margin of 34% to 35% and our mid- to high 30s target by the end of 2027. This expansion reflects the impact of prior restructuring actions, disciplined cost management as well as a thoughtful reallocation of resources, which enables us to fund priorities without increasing costs.

As we look ahead, margins are expected to continue improving as efficiency initiatives scale, including usage of AI-enabled tools that lower unit costs in product development and tighter alignment of sales capacity to our highest growth opportunity with full benefit building into 2027. These structural changes underpin confidence in our medium-term margin trajectory.

Turning to MIS. We delivered the strongest quarter on record. Rated issuance surpassed $2 trillion in Q1 for the first time, supported by strong primary market activity, relatively tight breads, increased M&A and solid investor demand. While investment grade and high yield spreads widened in March by roughly 15% and 30%, respectively, they remained well below the level seen around Liberation Day and the market stayed open and functional.

Transactional revenue grew 8% year-over-year, outpacing the 6% increase in rated issuance. Recurring revenue grew 9%, supported by growth in our portfolio of monitored credit, new mandates and pricing. First-time mandates increased 20% year-over-year, an important leading indicator of future recurring revenue. Here is how transactional revenue performed across the major categories. Investment grade was the largest contributor with revenue up 33% year-over-year. Investment grade revenue within Corporate Finance was driven by a record first quarter and the second highest quarter ever for issuance, including several jumbo transactions from hyperscalers and other technology issuers.

Issuance from the top 5 hyperscalers year-to-date has already exceeded full year 2025 levels. Specialty grade revenue grew 31%, with investor appetite holding up well for most of the quarter despite geopolitical volatility. Now we're watching this closely as sub-investment-grade issuers tend to be more sensitive to issuance windows.

Bank loan revenue declined as activity moderated in March following a strong start to the year. M&A-related issuance in Q1 was the highest in a number of years, which we view as an encouraging indicator for the balance of 2026. Public, Project and Infrastructure finance grew 8% driven by infrastructure finance, which delivered its second strongest quarter of the past decade. Funding needs tied to the energy transition, transportation and AI-related infrastructure remain key demand drivers.

Financial institutions revenue was modestly higher year-over-year. Funds and asset management remained strong, supported by private credit activity, partially offset by lower opportunistic issuance from infrequent issuers in banking and insurance. Structured Finance revenue was slightly lower year-over-year as large AMBS and RMBS reductions in EMEA were offset by softer CMBS and CLO activity in the U.S., especially refinancing.

On profitability, MIS delivered an adjusted operating margin of 66.7%, reflecting strong operating leverage, disciplined cost management and technology investments that are improving analytical productivity. We're streamlining credit workflows, so analysts can spend more time on credit analysis and less time gathering and formatting information, while maintaining the controls and human judgment regulators and the market expects. Those investments supported our ability to handle record issuance volumes while expanding margins.

Looking ahead, our full year guidance remains unchanged across revenue, adjusted operating margin and adjusted diluted EPS. Our base case assumes the current market turbulence is largely contained to April with issuance recovering through Q2 and Q3 on the back of ongoing refinancing needs, a healthy M&A pipeline and sustained demand for high-quality investment-grade issuance, including AI-related financing.

For the second quarter, we expect MIS revenue growth in the low to mid-teens with adjusted diluted EPS of approximately $4.15 to $4.30. If volatility persists beyond April, we'd have less confidence in a full recovery in Q2 and Q3 and would expect full year MIS revenue growth to moderate to the mid-single-digit range with adjusted diluted EPS trending towards the low end of our guidance range.

For MA, we expect to close the sale of our Regulatory Solutions business on April 30. We have, therefore, excluded its contribution from our reported revenue outlook, which moves us towards the lower end of our mid-single-digit MA revenue guidance range. Importantly, this does not change our expectations for ARR or organic constant currency recurring revenue growth, which both remain anchored in the high single-digit percent growth range.

On MA margins, we expect a modest step up in Q2 and a more meaningful ramp in the second half, consistent with our typical revenue seasonality. Pulling this together, in terms of MCO revenue guidance, as I shared, we expect to be within the high single-digit percent growth range we previously provided. For modeling purposes, taking into account the impact from the MA divestiture, we anticipate growth to be towards the lower end of high single-digit percent range for MCO for the full year.

Finally, a few housekeeping items to help with your modeling assumptions. Excluding restructuring and other charges, we anticipate Q2 expenses to be broadly in line with Q1 with increases in the second half, reflecting typical seasonality. This includes ongoing investments and annual salary increases, partially offset with our continued cost containment initiatives. We expect MCO adjusted operating margins to be above the midpoint of our full year guidance range for Q2 and Q3 before taking down in Q4, consistent with MIS revenue seasonality and historical patterns. There is no change to our tax rate guidance for the full year, and we expect Q2 to be in the high end of the full year range of 23% to 25%. And please note that our revised nonoperating income and GAAP EPS guidance reflects the expected gain on the sale of our Regulatory Solutions business in April, but it doesn't impact adjusted diluted EPS guidance.

We again delivered strong cash flow this quarter with free cash flow of $844 million, up 26% year-over-year. And given price levels and market dynamics, we were active in the market repurchasing shares in Q1. We returned approximately $1.7 billion to shareholders through a combination of share repurchases and dividends. Given the nearly $1.5 billion of buybacks executed in Q1, we have increased our full year repurchase guidance by $500 million and now expect approximately $2.5 billion of share buybacks in 2026. We remain on track to return approximately 110% of free cash flow to shareholders by year-end. Importantly, our balance sheet remains strong, providing us with the flexibility to continue investing growth while maintaining a disciplined and consistent capital return framework.

In summary, we delivered another quarter of strong growth and profitability expansion and remain confident in the trajectory of the business. We believe we are well positioned to deliver sustainable growth, margin expansion and long-term shareholder value.

And with that, operator, we'd like to take questions.

[Operator Instructions] Our first question will come from the line of George Tong with Goldman Sachs.

You talked about your MCP strategy allowing Moody's data to be accessed through LLM. Can you discuss how many customers are accessing Moody's data through these channels and what your plans are to monetize MCP distribution?

George, good to have you on the call. So yes, I talked a little bit about these different partnerships. And so that's enabling integration of our intelligence through MCPs through those surfaces. And then we have -- we have customers who are also looking to take the data directly into their own AI, internal AI workflow orchestration platforms at their institution. We have, I would say, a number of large financial institutions who are trialing, I'm going to call this our agent ready data through either the MCPs directly into the institution or through one of these channels. And what that does is it allows us the opportunity to up-level the commercial model that we have with these institutions, right? Because if they want to bring our intelligence into the corporate and investment bank, we need to make sure that there's an arrangement and a license that allows them to access that content across that entire division as opposed to in the past, we may have had been serving different use cases in different parts of the bank.

So I would say it's in early days. Lots of really good engagement of number now of trials, and we'll be looking to convert those to obviously, the sales through the balance of the year. The one other thing I'd say is -- sometimes it will also depend on the kind of institution or what the use case is for some of this. So we may see some of this show up in different segments across MA.

Our next question will come from the line of Scott Wurtzel with Wolfe Research.

Wondering if you guys can help maybe contextualize how much of the operating leverage in MIS is being driven by the technology innovations and AI efficiencies, I think just in the context of maybe some softer-than-expected MIS revenue growth in the quarter, it was still encouraging to see the 70 basis points of margin expansion. So wondering if you can talk about how much of that is being driven by AI efficiencies?

Yes. So you're right to say that we've been able to deliver on $2 trillion of issuance this quarter and still expand our margins. We've talked a lot about the investments we've made over the past few years on technology and now so technology, workflow automation, for all the works and steps that precede the ratings committee, where the analysts actually gather and discuss and make decisions and the work that preceded that was automated over the past few years. We've enabled them to be more efficient, avoiding repetition in different tasks. As you can imagine, Moody's being a 120 years company. We had some technology infrastructure that needs to be updated. So we've done that over the past few years. And now we're adding AI to those workflows in large parts of our analyst groups to help allow them in areas like financial statement spreading, data gathering, all the information, again, that precedes the the Ratings Committee moment where it's a lot of human in loops discussing and talking about different industry sectors and what they're observing. So that's -- I would say that's what behind our margin expansion. I'm pretty pleased with that.

Yes. And Scott, I would -- just to double click, I mean I think that the AI enablement really picked up in the back half of last year. As Noemie said, there was a lot of foundational work that we had done that put us in a very good position. We also had to work through our risk teams and make sure that we're going to deploy that in the appropriate way across ratings. And then it's not only about efficiency, and I appreciate you acknowledging that. But it's also going to be about inside as well. I mean, as Noemie said, we're capturing more and more structured and unstructured information across our entire ecosystem. And we're already seeing that that's going to give us new insights for our analysts that are going to support ratings quality as well as new research insights.

Our next question will come from the line of Jeff Silber with BMO.

I wanted to shift back to MIS. Rob, I think you had mentioned that volatility may impact timing and I was just curious, do you think there was any pull forward in the first quarter or conversely -- have we seen any recent delays? And if so, when do you think that debt might be issued?

Jeff, good to hear from you. We were looking at the pull forward. And I would say there was no more pull forward than what we would consider to be within typical ranges. And we've talked about it on prior calls that -- and typically, there's less pull forward with investment-grade issuers because they typically have market access all the time, and spec grade issuers is a little bit more pull forward. But nothing out of the ordinary, I would say, first of all. And I would say, Jeff, that in general, yes, things have been choppier, but spreads have come back in from the highs in late March and so is the 10-year as well.

So I would say from an investment grade perspective, markets open. And in fact, last week was a big week for financials. You had 4 of the 6 largest banks hitting the market, almost $40 billion in issuance. There is a backlog of Q1 deals that we have heard this from the bank. Some of these deals have been deferred into the second quarter. And I think there's some optimism that we're going to see some of that come back in May and June. But overall, the funding costs are pretty attractive. You think very tight spreads by historical standards, and looking at default rates, if anything, continuing to modestly decline based on depending on what plays out. It's that great, I'd say there's a little bit more selectivity as you'd expect with a preference towards credits at the higher end of the credit spectrum. But last week was pretty strong from a high-yield issuance perspective, pretty good from a loans perspective as well. So I'd say the market is open, constructive, and I think there are some risk windows, risk on and off windows that we're going to continue to see for some time as we've got some of the headlines playing out.

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

I wanted to follow up on the AI efficiency gains topic. And maybe asked a different way on the regulatory side. It seems like you guys have been first mover on a lot of these items, a lot of progress already to date. Is there any gating factor on adoption internally tied to regulatory pushback or what the regulators are comfortable with you kind of leveraging or ratings or even within MA. Just trying to get a sense for the puts and takes on that side.

Yes, Andrew. Good question. So I'll take it in 2 parts here. One with ratings. As you'd expect, we have a very active dialogue with our regulators, and they want to understand how we are thinking about deploying and using AI and they want to make sure that they are a very strong control environment around all of that. There's I'd say, heightened sensitivity for sure around the use of AI to actually be making decisions. And I think you see that across a number of industries, actually. So a lot of what we're doing is around the rating process and tools to give our analysts more new insights like I talked about. But we have a very good engagement with our regulators, and I would say they understand and expect that we will be deploying these AI tools and providing them transparency and having a strong control environment.

Now on the analytics side of the business, I would say that if you think about who we serve, these are -- we have several thousand bank customers, something like 1,000 insurance customers, they expect a strong control environment. They expect for us to have strong AI governance and other things as part of our products. And in fact, some of our customers come in and actually audit our products and solutions and what we're doing.

And so when we talk about decision grade intelligence, we always say it's got to be decision grade and that means you have to have strong control environment and auditability and all of those things that are regulated customers expect of us. So that does I think that -- we've seen that it takes a little bit longer for adoption with these big regulated institutions because they've got to satisfy not only their internal environment, but make sure that the third parties that they're working with have the same kind of controls and governance that their regulators are going to expect of them.

Our next question will come from the line of Peter Christiansen with Citi.

Congrats Rob. Best luck on next chapter here and also great to see first-mover strategy on digital assets. I had a question about private credit. It seems like sentiment here has been kind of going back and forth the last couple of months, and you called out 80% year-over-year growth, which is pretty impressive. Should we think that there's been a bit of a build and in the pipeline there? I mean you did talk about some deals that potentially are creeping in from 1Q to 2Q, but specifically on private credit, whether you're seeing that that dynamic occur and, if possible, is there any way you could size that portion of the growth for us?

Peter, thanks. So there's a few kind of cross currents I'm going to try to address on private credit. I think fundamentally, though, when -- obviously, we've been reading about increased credit stress in private credit throughout the quarter. That -- we've been talking about this now for -- I mean, for a couple of years about the importance of transparency in the context of private markets and having benchmarks and data and other things that can support a consistent understanding of credit risk across that market. And that is very important for that market to be able to continue to grow and scale.

And so I think one of the things that you're seeing as there's -- and this happens in the public markets as well. When there's more credit stress in the market, there is more interest and demand in our ratings and in our solutions. And that is exactly what we are seeing right now. It's exactly what you'd expect that we are seeing aspects of what I call investor demand pull or the investors in private credit are starting to say, we'd like to have a third-party independent credit assessment on these loans that are in the fund that I'm invested in. You're starting to see alternative asset managers make disclosures about how much of their portfolio is rated or the insurers are doing that and by whom. So -- and that's because the underlying investors are asking questions and wanting to have a third-party assessment of credit risk.

Now I'll say this, though, that -- so we've seen a number of deals shift from private into public market this past quarter. That's not surprising. The public markets are typically a cheaper source of funding. We've seen a lot of that, but there are massive funding needs. We've talked about these deep currents, they're not going away. And we've talked about sovereign balance sheets being really stretched. And so that means you've got both the public and private markets are going to have to be very important sources of funding going forward.

So all of that is playing into what you're seeing, I think, with our growth in private credit. And obviously, we've got very strong growth in ratings. But a couple of the things I mentioned in my prepared remarks, we're actually us supporting credit assessment out of our MA business with our credit scoring tools and other things. So I mentioned, we believe we have the world's best commercial credit franchise. So we're very well positioned to serve these needs across the entire company and across the entire ecosystem.

Our next question will come from the line of Jason Haas with Wells Fargo.

I'm curious what caused ARR to come in a little better than expected since I think a few weeks ago, you're talking about it maybe coming in towards the lower end of high single digits. And then I think the expectation then was that we would see an improvement through the year, maybe just due to some timing of new products getting pushed out. So I'm curious if that timing cadence still holds.

Jason, I'll start and see if Noemie has anything she wants to add. You're right, at that BofA conference, I did mention that there was a chance that we might have a little bit of a downdraft in ARR from the fourth quarter, just given that the way we had kind of sequenced our sales kickoffs and product launches and other things. We -- so I think the short answer is we had good sales execution through the balance of March coming out of those sales kickoffs and we ended up making up a little bit of that ground that I was kind of noting might be at that BofA conference. So change to how we're kind of thinking about the full year. I don't...

No, you're right, we had some pretty good execution in March. We had some swing deals that we were able to close, and we're pretty confident with the new product release that pipeline is building. We talked about what we're doing in KYC and we're confident about the high single-digit victory for ARR for the full year.

Our next question will come from the line of Sean Kennedy with Mizuho.

So I wanted to see if you could discuss a bit more about KYC and some of the trends that you're seeing there and the longer-term opportunity? And if some of the slowdown was due to macro later in the quarter?

Yes. Thanks, Sean. So for KYC, 13% ARR growth, we had a little bit of a tough comp for new business versus the first quarter last year. We had a couple of outsized deals last quarter. Retention improved pretty notably as we lapse those cancellations that we had last year, most of that was related to DOGE.

I would say, Sean, that we think growth is going to pick back up into the mid-teens through the balance of the year. We've got some new use cases and new product launches. Probably the most important of those is the one that I just mentioned briefly in my prepared remarks, which is what we call Moody's for compliance. Think of that as a kind of a platform solution that serves nonregulated institutions, corporates and so on. So we've been building pipeline on that. We expect that to continue through the balance of the year.

Most of our growth so far has been from cross-selling to existing banking customers, and we're starting to see that corporate growth pick up. So I think the key message here is that we expect ARR growth to pick up through the balance of the year into that kind of mid-teens number.

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

Rob, I was hoping you could just give us an update on how you're thinking about the hyperscalers and if you've seen a number of them move to the frequent issuer program and whether the economics there are sort of similar to other IG issues? And I guess, has that created sort of a price dilution or a mix dilution between sort of when we look at the issuance numbers and ratings revenue, is that one of the factors that would drive sort of a delta there? And should we expect that to continue as we see this sort of massive hyperscaler issuance over the next few years?

Toni, good question. I'm glad you asked it because I mentioned kind of $100 billion-ish hyperscaler issuance through the first quarter. That's a big number, and that's getting close to what we were thinking of for the full year for 2026. So it is possible there's some upside to that through the balance of the year. But I'm glad you asked the question because I would say hyperscalers are, in many ways, no different than any other what you would think of as frequent investment-grade issuer. And we always talk about some of our serial investment-grade issuers are on frequent issuer pricing programs, which is why there's a little bit different revenue mix on investment grade versus spec grade, and that's true here. So when you see these big numbers around hyperscaler issuance, just think of that as frequent investment-grade issuer kind of issuance.

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

Noemie, I just wanted to queue in on something you said in your prepared remarks about MA and you specifically said you're reshaping the portfolio. I was just wondering if that's sort of the past like the learning divestiture? Or is that also kind of a reminder something that's ongoing and MA portfolio changes ahead in terms of divestitures or product sunsetting?

Yes. We -- so you're rightly pointing to the couple of divestitures. We -- one we've closed last year and what we're about to close in April. So that's part of it, really focusing on high-growth areas product suites where we have cross-selling opportunities with the rest of our customer ecosystem. That was an important driver for the decision around regulatory solution divestiture, for example.

And beyond that, we're looking at within Moody's Analytics, really reallocating our resources, both in the product development as well as sales and go-to-market to higher-growth areas. There's a product where the growth rate, and you see that, for example, in the Banking and Decision Solutions, some of them are very mature products, very much in demand from our customers, but at scale. And I would say we're investing less and putting them more in maintenance mode and making sure we continue to serve the customers who have those solutions before they migrate into the new package. So that's kind of the decisions we're making in terms of resource allocation. And that's what allows us to continue to fund investments in really strategic areas like lending, decision grade data, insurance underwriting, while at the same time not increasing the amount of developers resources new product and go-to-market.

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

Yes. Staying on MA, and this is also Noemie, just a little bit more of a numbers question here, but obviously, the transactional side of that business, I think, is the lowest quarter on record, I think $17 million. So obviously, done a lot I know you deemphasizing. So just the question is, is this kind of it now? Is this kind of a good run rate to use for the rest of the year? And does that mean that as we think about 2027, you're finally getting to the point where like ARR and recurring revenue growth and overall growth kind of start converging? Or is there still more to go? And can there still be more lumpiness on the transactional side here. I'm just trying to understand like really what's happening on that side?

Yes. Recurring revenue on an organic basis is actually very trending really close to ARR. So I would continue. That's why we were disclosing those numbers separately. When it comes to transaction revenue, you have the effect of the learning solution divestiture in Q1 number. That's why you have the down dip in that number in Q1, which was expected. So you'll continue to see that carrying through the rest of the year. We had a double-digit decline in transaction revenue, which we continue to expect as we move services, integration work to our partners. We don't want those on our paper. We're obviously here to support our customers as they go through migration and implementation, but those revenues are now being recorded outside of our books. So you'll continue to see that carrying through '26 and '27.

However, if you look at, again, organic constant currency growth for recurring revenue, that's really much aligned now with ARR, you can have a few lumpiness in a given quarter if we have on-premise revenue recognition for long-term software arrangement that could create a little bit of variation. But on a trailing 12-month basis, that's pretty close.

Our next question will come from the line of Owen Lau with Clear Street.

I do want to go back to the organic revenue growth and ARR bridge because the organic growth was 6% in the first quarter, ARR was 8%, but you still guide to high single-digit percentage range for organic revenue growth. Can you please talk about the bridge to go there from 6% to high single digits? Because -- would that come from like Moody's for compliance, AI and some other stuff. More color would be helpful.

So the guidance for organic constant revenue in the high single-digit range is at the low end of that range. We have, as I said, about a percentage point of headwind from transaction revenue decline. It was down 56%, for example, in Q1. So that's one thing.

In terms of the underlying organic recurring revenue growth, that typically accelerates throughout the year, consistent with our sales cadence. As you know, the second half is usually stronger when it comes to sales execution and pipeline build. So that's gradually building back up to high single digit. About organic recurring constant currency growth and ARR guidance is really consistent with what we've said before in the high single-digit range. So if you look at the organic revenue growth, that transaction revenue is really the delta here and the drag.

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

Great. Just a quick asking question on ratings issuance just assuming we stay at that current guide of singles rate for revenue. Rob, last time you had spoken to at least the relative mix of the weighting to be about mid-50s for the first half of the year. Is that still roughly right or just anything we should think about or any changes that's baked into the current forecast?

Yes, Curtis, good question, because obviously, we held the guidance but the issuance has been a little softer than we had expected. So I can give you kind of an update on how we're thinking about the calendarization of both issuance and then maybe I'm sure it will be helpful. I'll translate that quickly into ratings revenue.

So we're expecting issuance to grow in the, call it, high single-digit percent range for the first half of '26 versus the first half of last year. And then we're expecting it to decline mid-single-digit percent in the second half of '26 versus '25. And remember, we have bank loan repricings in those numbers.

So from a sequential standpoint, we think that issuance is going to decline from the first quarter to the second quarter in kind of call it the mid-teens range, flat issuance from the second quarter to the third quarter and then then kind of mid-20s decline from third quarter to the fourth quarter.

From a revenue perspective, we're expecting first of all, year-over-year revenue growth in every quarter in 2026, stronger in the first half versus the second half. So in the first half, something like low double-digit percent revenue growth in the first half. And then for the second half, we're expecting something like mid-single-digit percent revenue growth. And again, the delta is just because of bank loan repricings being in there. So hopefully, that gives you a sense.

Our next question comes from the line of Craig Huber with Huber Research Partners.

Rob, I thought one of the most important things you said earlier was a partial response to a question was concerning that the regulators were very apprehensive have an issue with AI making decisions out there talking about parts of your portfolio. Can you elaborate on that? It's obviously a major, major issue AI concerns and some hope with the AI tools can come in and duplicate some of the services that information service companies have in general. Just talk about a little bit further, please. It's a big point.

Yes, Craig, and just take this for what it is from my seat. Obviously, I'm not an expert, for instance, in insurance and all of that. But I would say, just in general, you can imagine, and this is true with our regulators as well, thinking about the opportunity to accelerate your process and the time to get to a decision and all of those things, those are pretty straightforward conversations with regulators.

When it comes to, hey, I've got an AI model that's actually going to make a decision about who's going to get a loan, who's going to get an insurance policy at what price, what a credit rating might be, there's a lot more sensitivity around that, as you'd expect, because there's questions about the model -- does the model have bias, how is the model being governed, what kind of data is going into the model? Is there a human in the loop? All of those things, right? And that's true with us, and that's true with a number of our customers.

So obviously, there are decisions across financial services that do get made by models. I get that. There's quantitative trading platforms. There's credit score things that go on for consumers, all of that. But I would just say that, that's generally where there's more scrutiny from the regulators and wanting to understand it. If a decision being made by a model, well, there's a lot of questions about that. Hopefully, that gives you a sense.

Our final question will come from the line of Shlomo Rosenbaum with Stifel.

A little bit more of a broader question in terms of the guidance. And I know it's a fluid situation geopolitically, but I'm just wondering how did you incorporate the war in Iran, what's going on and the potential impact to inflation and anything else in terms of spreads going up and down into the guidance? I know you mentioned the guidance talked a little bit about volatility. But like when you think about it through the year, and your decision to keep the guidance there. How are you thinking about it as it goes through both MIS and MA?

Yes. I'll focus probably mostly on ratings just because I think that's where more -- there's more variability given the geopolitical backdrop. But obviously, the Iran war is the most important variable is interesting actually because we were thinking back at the first quarter call this time last year. And if you remember, there were the liberation day tariffs. And it was very -- it created a lot of volatility and uncertainty in the market. And what we saw through the balance of the year was that, that volatility resulted in considerably lower issuance levels in April last year. But then we saw that get made up for the back half of the year, right? And we ultimately ended up essentially right in line with our original full year guidance.

So I think we're -- we feel like we're in a little bit of the same situation. It's April 22. There's still a long way to go in the year. There's actually an interesting stat, Shlomo, that in March, 80% of investment-grade issuance was in 6 days. That's pretty remarkable. And that tells you a couple of things. I mean one, it just shows you kind of the risk on, risk off windows that were going on in March. But two, it also shows you how much demand there is that was just waiting until there's a risk on window and that demand hits the market.

So it goes back to all these things about the underlying funding drivers, the demand drivers for raising capital, those are still there. And so Noemie talked a little bit about in her prepared remarks that if we see heightened volatility that goes on into May, and we see real softness in the month of May, I think at that point, we're probably going to -- Noemie gave you a sense of what that would mean for our guidance. But right from where we sit right now, given the conditions that I talked about, given the underlying drivers and given the fact we're still in April, we think it's most prudent to hold to our current guidance. And when we talk to the banks, that's the same thing we hear from them as well.

This concludes our question-and-answer session, and I will hand the call back over to Rob for any closing comments.

Okay. With that, thank you very much for joining, and we look forward to taking -- talking with you on our next earnings call. Goodbye. .

This concludes Moody's Corporation First Quarter 2026 Earnings Call. As a reminder, immediately following this call, the company will post the MIS revenue breakdown under the Investor Resources section of the Moody's IR homepage. Additionally, a replay will be made available after the call on the Moody's IR website. Thank you. You may now disconnect.

We're happy to have all you here. I'm Curt Nagle. I'm the new senior analyst for the sector. Really excited to be covering the sector. Really excited to be working with you all. We have a really terrific lineup today, full gamut of the -- basically the entire sector, covering what we think will be the most pertinent themes and then, of course, headline with all things AI.

Opening the conference today, really pleased to be welcoming Rob Fauber. He's the President and CEO of Moody's. 20-year veteran of Moody's, started at BofA his career.

Yes, that's right.

And under his tenure as CEO for the past 5 years, led the company to record profitability both in ratings and in analytics. And is embedding -- I think turned it off a second. No, okay. Sorry. Embedding AI across every facet of the business. That's a huge focus for him, driving internal efficiencies, new product development, solutions, and revenue streams based on the proprietary and as you put it, Rob, their decision-grade data. So again, with that, welcome, Rob, and why don't we jump into the questions?

Yes, thanks for having me, and it's great to have you covering Moody's.

Yes. Great to be here. So yes, in terms of the first question we're starting with, at least for the info service companies, is unsurprisingly on AI and moats, right? We'll get into some of the -- what we are -- or could be the biggest opportunities, how you're harnessing the technology. But yes, sticking with moats, I think it's generally understood that anything around credit is pretty walled off, right, defensible.

But if we think about some of your other data assets, the stuff that comes through licensing, commercial agreements, IP agreements, stuff that isn't outright owned by Moody's. What are the moats around there? And I guess in terms of -- maybe moats that people don't recognize or don't appreciate as much, whether it's regulation or switching costs. How would you address that?

Yes. So I knew the first question would be AI. I'm sure we'll have a lot of discussion throughout the day on AI. And you're right, the Ratings business is a benchmark business, and we'll probably touch on that. I hope at some point, about how we're thinking about the Ratings business and an AI future. But in general, there's more demand for understanding credit and risk than I can remember in a long, long time.

As you think about basically, our content state, I'm going to move now over to analytics. I would say a few things. One, and I'm going to zoom in, you talked about our company database, so I'll zoom in on that in a second. But in general, we have deeply contextualized content, right? So there's a whole context layer on top of our data that provides -- it's a structured representation of the data with governance and auditability and all those things that are super important to banks like Bank of America, who come in and send in their internal audit teams to audit our processes. So that's one.

Two, a lot of what we do is underpinned by very proprietary data sets. Orbis is a little different. I'll talk about that in a second. But if you think on the credit side, we, for 3 decades, have curated the world's largest proprietary give-get default database. And then that's what we use to calibrate our credit models. So it makes them unique.

Similarly, with -- you go over to insurance, like our catastrophe models, those are calibrated, but we get access to the entire industry's claims data. And so we use that to calibrate the models. I've been asked before, can't AI build the models? AI can build a model, but it can't be calibrated on actual loss data. So that's the second thing, I would say.

And third, you have to think about why institutions are using us. You use the word decision grade. We use that all the time. Banks and financial institutions want to credentialize what they're doing. So our credit models, our stress testing, our cat models, our customers' use of those models and those data sets is being reviewed by their regulators, right? They're going in and looking at credit files and reviewing their processes. So there's a very strong indirect regulatory support for all the things we're doing. So imagine that everybody in the industry is using our stress testing and economic scenarios and forecasts except you and then there's an error in yours, and you can't figure out why there's an error. That's a very, very bad day in the office.

The last thing I'd say is I'm just going to go to the Orbis data. So this is the world's largest database on companies. And think of it as really 3 layers of content within that. First is what I'd call basic firmographic information. Can that be collected, some of that be collected by AI and scraped off the Internet? Yes, and it happens today, and we compete against those companies and have been.

Then we have information that we get from these bureaus that is private. And we get that because we have paid access and IP rights that we negotiate and then the IP rights are about how can we create derived data and distribute that data. And then we transform some of that data and create proprietary ownership structures and trees. That is transformed proprietary data, it's where most of the value is in the Orbis database. I'll pause there.

Okay. Maybe a good segue in terms of thinking about adoption, right, for some of these AI-enabled products, agentic workflows, stuff like that, AI-enabled databases. I think on the last call, you talked about your large customers, right, consuming at much higher rates, I think twice the rate for the rest of the business or your other customers, in part due to, as you talked about, more sophisticated AI tools. Where specifically are you seeing the adoption curves really start to ramp? And then I guess thinking about growth rates for the rest of your customers, the smaller ones maybe less sophisticated. How do we think about that ramp?

Yes. So I'm going to focus on banks. It's our largest customer segment. And there is a tale of 2 customers. So you're right, at the big end of town, the Bank of Americas, they're all about building out their own AI workflow platforms, maybe across the corporate and investment bank or the commercial bank. And it's not about consuming software from us. It's about consuming I'm going to use the phrase our connected intelligence, right?

This is our contextualized data, our models, our insights, our ratings. And they want to consume that in their platforms, right? And increasingly that they're building those platforms, and that means it's either -- historically, we've -- people have consumed our content from our workflow software, maybe through our website, and a data feed, a good old-fashioned data feed. And today, it's about, hey, now can I take it through a smart API or an MCP server into my AI workflow platform.

And every big financial institution I talk to is talking to me and I'm sure others in the industry about how can I access actually more of your content because I'm building this layer across the corporate bank. And I know that I've got the data siloed in all these different parts of the bank, and I want to have my own internal bank data and my very important third-party information providers, feeding into my AI system. That's a conversation we're having at almost every single bank. That's a great conversation for us to have. That's why we're seeing the highest growth actually from the strategic -- the largest banks, and that's very encouraging to us.

If they wanted -- if they thought it was commoditized, we'd be having a very different conversation. But then when you go down to Tier 2 and Tier 3 banks, the regional banks, the credit unions, it's a very different story. We serve a lot of them. There, one of our fastest-growing products, and we talked about in the earnings call is lending workflow software. And what those banks are saying to us is, "Hey, look, I don't have an army of AI experts. I want you, Moody's, to bring to me AI enablement on the workflow platform that I'm going to implement and tell me what other banks are doing".

And so we've got an AI layer that sits on top of the workflow that does things like spreading financials into your chart of accounts, creating automated credit memos, covenant monitoring, all those kinds of things. Both of those are driving very nice growth for us.

Understood. I guess another good segue. I think maybe a little long term here. And considering all the things you said, how does this -- how do we think about the evolution, I guess, of pricing models, right, over the next few years particularly, again, not to belabor the point, but companies like yourselves that have mission-critical proprietary data. Do you foresee, I guess, a shift to more consumption, more value-based, which you've talked about a little bit right away from these strict enterprise models. And I guess how does that impact I guess the arc of revenue growth going forward, let's just say, over the next 1 to 3 years?

Yes. I think that's the right time line, by the way, the right way to think about it. We are piloting consumption pricing in one small part of our solution set. This is with the smaller customers where it's more of like a product-led growth kind of model. I would say a couple of things.

So first of all, a lot of the conversations we're having now are about, hey, how can I think about changing the labor leverage model within my institution, whether it's KYC and anti-financial crime or whether it's my credit process, right? So that's a great discussion for us to be having. It is a different discussion.

And then it's all about business case and ROI and all those kinds of things. And you start to say, well, the data is going to be the data and models and contextualized intelligence is going to be very valuable, right? And there's going to be a huge return on that. How do we think about the pricing? I think you're going to see us move over that time horizon to implement elements of consumption into the model. And I say that because a few things -- you have to think there's a few things that have to happen.

One, we have to have the revenue operations and the technological capability to meter all of the usage and to be able to charge for that usage. So I mentioned these good old-fashioned data feeds. We don't know all of the usage in a traditional data feed environment. We have -- there are IP restrictions and usage restrictions. We audit our -- we don't know right? So there's a case where it's not as easy as just saying, "Hey, I'm going to charge you based on consumption". So there's a RevOps piece. And then there's a customer piece.

A lot of times, people lose sight of this because you think aren't you just going to get uncapped upside for usage of the data. That sounds great, but the customers -- think about what the customers are dealing with uncapped cloud cost and want -- many of the customers want budgeting certainty. And so I think you're going to see hybrid models, right, where we have access to the content, some set amount of consumption and then perhaps thresholds and kickers for additional usage.

And I think back to the conversation we're having about hey, take more of our data, more of our content into your AI workflow platforms. That means there's going to be more usage across more of the institution. We'll see you in a couple of years, and we'll have a different discussion at renewal when you have a chance to really understand how you're using and getting value out of our contextualized intelligence.

Yes. And I guess maybe as a byproduct before maybe pricing consideration stickiness, I would imagine would be a good consequence of that, I would think.

Right. The more embedded we are, the stickier we are, and we're deploying our customer success teams to say, "Hey, great news, you've got access to the content here at the institution. Now we're going to deploy our customer success teams to make sure you get as much value as you possibly can out of it".

Understood. Okay. Switching gears maybe a little bit. So again, we've talked about AI customer relationships, revenue opportunities, value of the data. How should we think about AI within Moody's internally in terms of asset and labor efficiencies, again, kind of, let's call it, the 1- to 3-year time horizon. Just looking at your K, right, headcount does seem to be going down, at least if I look at AI, I don't know if that's a consequence of just good old-fashioned expense management or whatever but -- yes, just basic question of kind of how to think about internal utilization and asset efficiency.

Yes. There -- you talk about 1 to 3 years, and this is coming out as fast. So I'm a real bull on the efficiency opportunity across our organization. So we, like many other companies went after customer -- customer service and some other things. That was low-hanging fruit early on.

Now we're going after product development life cycle. And what that is, is if you think about a company like us, we have product people and we have engineers. Product people engage with our customers, create specifications for products, work with the engineering teams who then have historically written code. We know all that is changing.

So we have literally -- we have redesigned our PDLC to be AI first. We have AI coding tools that we are deploying into that PDLC. We have changed job descriptions, and we're moving towards a world where I think instead of product people and engineers, we're going to have what you think of as builders, right? I'm a builder. I was telling you, I built a website at 3:30 in the morning the other day, I mean -- so that is a real opportunity, both in terms of efficiency. We already see the data on how much more efficient it is making, especially our best product and engineering people but also product velocity.

And even the selling motion is going to change, right? Because we can do rapid prototyping now and we can create specialized agents in -- literally in days, right, and prototype that with a customer as a way just to access more of our intelligence. It's just another vehicle to consume our content. So I can't change the -- I'm not going to change the medium-term targets, but I can tell you we're going after this aggressively, and it starts with me, and I provide coding and everybody at the company knows that. And -- so I think there's a real opportunity here.

Okay. And maybe just to put, I guess, a final point on that. Can't change the long target, right, or the medium-term target, high 30s, but I guess in terms of -- not to sort of again a belabor a point, but in terms of the arc of potentially reading -- getting out there, maybe even at some point, thinking about maybe you get to 40, I don't know, but yes, the general margin implications.

Yes. So I guess there, I would say I'm bullish on the opportunity. As you can see, I'm not ready to build that into changing the medium-term targets, but I see this as a real opportunity for us going forward.

Okay. Talked a lot about analytics business, AI and ratings, right? Your highest margin business by a pretty good margin. I think your guidance for this year is above your targets and that is obviously on things like the volume leverage and you're lapping some investments. But yes, how does -- just very broadly, how does AI change your ratings business?

I would say 2 ways. And I know a lot of people focus on, hey, with these AI tools, can't you just be much more efficient, right? And the answer to that is, yes, of course. We will be able to. The interesting thing I think about what's going with AI, it forces you to ask questions about your source of sustainable competitive advantage.

And of course, spreading financial statements and making adjustments and stuff is not where the value is in the rating agency, so that means those things are going to get automated, and they are being automated and leveraging AI as fast as we possibly can. That's all happening.

And you've seen already the operating leverage that's continued to come into the business even last year, right, as we have issuance growth because we've been working hard on what I'd say is traditional workflow automation. And in the second half of last year, we deployed AI capabilities that really accelerated our ability to automate and enable our analytical teams.

The other thing is we're going to capture as much data from across the organization and the ecosystem as we possibly can, right, and feed that into our models to continue to provide us with unique insights that the rest of the market doesn't have.

Okay. Fair enough. Sticking on -- so well, I guess, put a bookend on AI. Sticking on the Ratings business. I guess a question -- and I know there are a lot of moving pieces here. Just generally, I guess, assessing the puts and takes, the risk opportunities for the guidance you gave, low single for issuance for the market, whether it's uncertainty on pulling forward refi walls, geopolitical risk, obviously, a huge question right now or just general data center CapEx, that's been a big driver. What specifically is in the model? And again, how should we think about the puts and takes?

Yes. Take this for who it's coming from. But it feels like just about every year around this time, there's something that happens. It's COVID. It's [ Ukraine ], it's liberation days, right? And here we are. And so the questions every year have been gosh, the market is feeling fragile. And what does that mean for your full year guidance and so on.

Well, guess what, last year, in Liberation Day, we basically lost the month of April, right? The markets went to a risk-off mode and look where we came right on top of our guidance, our original guidance for the year.

And what I would say here is what it's hard for us to build into our annual guidance is geopolitical risk and the inevitable then market volatility and kind of risk off mode that happens. So you end up losing a week or -- but what I would focus on is -- so while that is certainly the environment at the moment, heightened geopolitical risk, questions about oil prices, Fed easing, spread widening, all those things.

From where I sit, I just think, gosh, all of those funding drivers that we have been talking about for years, which you have seen come through the business over the last 2 years, they're all still firmly intact. What kinds of things are they? So economic growth certainly has been one, but BlackRock put out a $68 trillion of infrastructure funding needs by 2040, that hasn't gone anywhere.

You put AI and data center and not just data center, but all of the related energy production, transmission grids, renewables, transition finance, all of that, that's all still there. Heightened geopolitical risk has meant military buildups. Massive investment is going to go on in militarization and defense. And guess what, sovereign balance sheets are pretty stretched, right?

So the governments are going to have to rely on the public and private funding markets to do a lot of this. And by the way, we also have a huge amount of debt has been issued over the last 5, 6 years. That's got to get refinanced. The 2028 refi walls in particular, are quite substantial. And then there's all of the private equity exits that have to happen, we know they have to happen and all of the money that's got to get deployed, that's got to drive M&A, still all there. So we're going to have some risk on and risk off weeks, heightened geopolitical risk, that stuff, those medium-term funding, it's all there.

Structurally, so no change. Okay. And yes, March is always tough...

It's early in the year. That's what we have to keep in mind.

Okay. Maybe just a segue here, private credit, right? [ Small ] has been a high-growth business for you. I guess how should we think about a, if you're willing to say just the revenue contribution for this year and then going up maybe a few?

And then just kind of thinking about it like, you've got certainly some puts and takes, right, things you talked about, impact private credit. We've got concerns about outflows and credit quality, which would technically be a negative. On the other hand, right, that theoretically drive more demand for a deeper analysis of portfolios and specific companies. So how does that all balance out? How are you feeling about private credit?

So I feel much better just where our franchise is now than several years ago. It's interesting the discussion with investors and analysts several years ago was isn't private credit a big negative to the rating agency because it's the disintermediation of the public markets. And that was a huge negative. We geared up. We found ways to serve that market. There's still lots of that market that are unrated. We have seen very strong growth in parts of the rating agency serving parts of the private credit market.

And now questions are, hey, is this now a headwind because there may be, as you said, heightened defaults and fund outflows. And well, that means the public markets are going to take up this lack. And I have said before that a lot of the direct lending is like a deferred mature -- it's like another maturity wall for us, right? And we've already seen this year some pretty robust refinancing out of the private credit deals into the public markets. Why? Because they're cheaper, right?

And -- so I think we're going to -- to some extent, I'm relatively agnostic, right? I mean, I'd rather rate the direct credit now, and I'd rather be able to express an opinion on it for the market, but we're seeing some of that come back into the public markets. So that's one.

And just in terms of what do we assume, we had very robust growth last year off of a smaller base relative to the overall size of the Ratings business. We've assumed that growth is a little bit slower this year, but still quite healthy. But if that slows down more than we expected, my guess would be we're seeing that come into the leverage loan part of our business.

And the second thing, just to your point is, I've been saying this for a couple of years now, and I feel like I've been speaking into the wind about this market will benefit from rigorous third-party credit assessment. And that will provide confidence to the investing -- to the investors and allow this market to scale. And I would hear all the reasons that didn't need to happen.

But I think now there's a much, much greater understanding of the benefit that third-party -- rigorous third-party credit assessment can provide this market in helping understand the credit profile of what people are investing in, so they can invest with confidence. We're seeing that demand then materialize in our analytics business because remember what we have in analytics. At the core is the world's best commercial credit franchise, right, the proprietary default databases, the gold standard credit models and guess what they're ideal for assessing private credit. And so we're addressing that market opportunity.

So I guess in the context of -- I mean, just judge it by the headlines we're seeing, in terms of rate -- I mean, is that rate of adoption accelerating in a fairly linear path of relationships?

I would say, it's very small. So the investor use of credit models, not surprisingly, has been small. The biggest customer base for all of our credit models are bank credit apartments. But now you have a new customer segment who's saying, first of all, we have to educate them. I didn't know that you had those capabilities, right? And now talk to me about what they are and can you actually -- do you actually have the ability to create a -- give me a probability of default mapped to a rating level with the confidence that you can put the Moody's name behind it.

And the answer is -- if you give me the data, the answer is yes, and we've been doing it for several decades for banks. So it's small. But in part, what we did with MSCI was about saying to the market, we have this capability, and we and MSCI are working together to bring this capability to the investors in private credit.

Setting the table, I guess.

Yes.

Okay. Fair enough. Switching just quickly back to MA. So I guess, kind of breaking it down by subsegment, right? Your KYC business is doing really well. One, in terms of how I'm thinking about the rate of growth, roughly 20%, is that a sustainable rate? Insurance, you're calling out -- and we've talked about this a little bit more demand for sophisticated products. So how should we think about that, again, as a rate of growth this year?

And then I guess, what is -- what needs to happen within your banking business to get that to reaccelerate? I know there were some purposeful I guess, pullbacks like transaction revenues. But how do we think about that segment?

Yes. So you kind of talked about the big 3, if you will, sitting inside Ratings, our Analytics business. And I mean you can see from our guidance, we're generally expecting the portfolio to produce roughly the same rate of growth. But let me break down kind of where that growth is coming from.

So in banking, I talked about both what we're doing with the large banks who are accessing, Think of it as our contextualized intelligence and the Tier 2 banks who are actually buying the software. And we talked about the growth rates of that lending workflow software are very robust growth rates.

The drag in terms of revenue. So when you look at ARR growth, the ARR growth in our lending suite is faster than MA overall. That's very encouraging. But when you look at revenues, we historically have had transactions implementation services. We've been deemphasizing that for years now. And so that's just a drag on reported revenues. That's low margin revenue anyways. We want to move away from that. We've moved to a partner model.

With insurance, the drivers there -- we -- not only do we have the cloud-based platform adoption of our core catastrophe models, but we've now moved into -- we acquired a company a couple of years ago that provides AI geospatial intelligence to support insurance companies in underwriting, property underwriting and then that feeds into our catastrophe models, and we've expanded into casualty.

And casualty is actually one of the biggest sources of insurance claims. You think about things like asbestos -- mass torts and litigations and asbestos and things like that. And that is a huge need for the insurance industry to understand how to get a more data-driven approach to assessing that kind of risk. And so we're building that out. That's going to support the growth in insurance.

And then, of course, we talked about KYC, the demand for that continues at pace. And the only other thing I would say is that what we've done this year in terms of just how we go to market is we've tried to kind of cluster our product launches into the first quarter of this year so that we can have a really concerted go-to-market. Historically, we kind of spread them out throughout the year. And that included the second half -- so what we did is we kind of took the things from the second half of the year, held them, put them into product launches this year.

What that means -- the only reason I mentioned this is just there's going to be a little different cadence of ARR growth. So I would expect in the first quarter, we probably have a little bit of a downdraft towards the lower end of our high single-digit ARR guidance. And then that will pick back up through the balance of the year because I think it's really about just the calendarization and the selling.

Okay. Understood. Maybe quickly touch on capital allocation. One, just in terms of -- I don't think it's a huge focus, but bolt-on M&A, what assets would look attractive? And then I guess, just thinking about buybacks considering current valuation and just -- yes, how are you thinking about that framework?

Yes. So we -- we always like to invest back in the business first whenever we can. And I always say, like, if I can invest in Ratings, I'm going to do that. That's the -- one of the best businesses in the world. You've seen us make. There aren't many opportunities to do that inorganically. We bought the largest domestic rating business in Africa a year or so ago. It's a great generational investment for us.

And then from an analytics perspective, I mean, gosh, we have had to change how we think about what makes the most sense from an M&A standpoint. I think you would expect us to do that, right? So when you look at -- do you want to bring more workflow into our solution suite. It's got to be something that has a real proprietary data asset and data rights inside of it. And not all workflow is created equal, not all of the rights to the data that sit inside these systems that is a real focus for us as we think about that. I think it would be very unlikely we would buy workflow for the sake of workflow at this point.

So -- and then obviously, everyone is thinking about, can they get access to proprietary data. But for us, if you think about what we have as a connected intelligence system, that's really what underpins all of our solutions, right? It's the world's largest database on companies, and a knowledge graph that we are building out that connects all of the companies to all of the different data sets and models and insights and ratings that we have, right?

And so wherever we can find uniquely valuable data sets that we can put into that connected intelligence system, make this system itself more valuable, make that data more valuable and monetize that through multiple customer segments, that's attractive for us.

Then I think Noemie, the last thing I would say on the earnings call, she talked about share buybacks. So obviously, we have a lot of dry powder if we decide that there's an attractive acquisition opportunity. Absent that, Noemie talked about a $2 billion share buyback this year. That's up, I think, something like 25% from last year. And Noemie did signal that we're aggressively buying back stock here in the first half of the year.

Yes. Okay. Maybe one quick -- very quick lightning around word association. So first, refi well.

Very strong.

Very strong. Okay. Private credit?

Needs independent credit assessment.

Margins?

Very robust.

Very robust. Okay. Rates?

TBD.

TBD. Fair. And M&A?

It's coming.

It's coming. Okay. All right.

By that, I mean the market.

The market, right. Clarification. All right. Well, I think that wraps up time. Rob, really appreciate the conversation. Than you so much for joining.

Thank you.

Moody's Investor Service. And we have Kiera Bridges, SVP of Investor Relations. Format for this is going to be a fireside chat, and with that, welcome. Thanks for joining us.

So Mike, despite massive volatility in pockets of the equities market. Credit conditions remain quite benign with spreads near historically tight levels. And maybe the events of the last few days have widened them a little bit, but still relative to where they've been historically, it's a very tight market. When you were here last year, your expectation at the time was for spreads to normalize in 2025, back towards their historical 400 basis points spread relative to the reference rate. So today, I'm wondering whether it's going to take a legitimate credit recession to cause that normalization? Or kind of what are your current thoughts on that topic?

Okay. Well, first of all, thank you for inviting me and thank you for everyone joining. When it comes to credit spreads as many of you know, very complex inputs going into it, whether it's economic market, liquidity or others. When I was here last year, our default study was expecting that we will go back to about 400. In fact, I looked and it tipped over about 300, but then came back. It is still our assumption that it will still gravitate towards that number, the 450 even up to 500. I did just take a look at this moment, and spreads are still hovering around about 300 despite what's happening out there in the world today.

So I think your response segues well into my next question, which are what are the puts and the takes in the form you recently issued or recently announced issuance expectations in 2026, including your spread expectations then?

So first of all, I just want to do a quick clarification on the earnings call, Rob Fauber, our CEO, outlined that revenue would be on a calendarized basis, about 25% for the first quarter, not to be interpreted that revenues would grow by 25%. So I just wanted to clarify that because there was some uncertainty out there in the market. When it comes to the upside this year, obviously, keeping a very, very close eye on spreads in the short term and in fact, how that is feeding into current issuance so far this year. They've still been relatively tight. And what that allows for is this opportunistic financing coming into the market. We have substantial numbers in the refinancing, but the opportunistic refinancing comes over and above that.

This year, we're also expecting about a 25% increase in M&A activity that's announced M&A. A portion of that will be debt. It's been relatively subdued over the last years, particularly in the private equity space. We've also factored in more specifically an increase in debt associated with the investments going into data centers, power generation and supply. Again, the overall sentiment around the economy, notwithstanding what's happening out there today. And also, particularly for the U.S. issuance that is supported by the pro-growth agenda by the current administration and deregulation, particularly as it relates to the banking sector.

On the flip side, when you think about the downside scenario, one would be a prolonged geopolitical conflict that would reduce investor confidence. I think that's been tested at this moment. And ultimately, depending on what happens to energy prices with a prolonged expectation of inflation particularly as it relates to oil and gas, and that may pause authorities around the world with regard to easing of rates that were still expected for this year. On top of that, you may see in any one of the sectors credit events that may throw the market to a risk-off environment if that risk off is a few days that is materially different from if there's something that's prolonged going into a matter of weeks that would increase volatility, increase spreads on that. And that would again feed in to concerns about the health of the broader economy and potential deteriorating trade and other dynamics.

So you touched on inflation and the implications on the long end of the yield curve. If rates were to move meaningfully lower from here, could that be a positive catalyst? And I guess another side, if inflation appears to pick back up, like how significant of a headwind could that be?

Yes. So when we look at the duration of rates, and at the moment, what you have is an elevated rate scenario towards the longer dated. If that starts to come back in and if I recall back in COVID times, at the back end of the curve started to come in substantially. What that allows for is longer data paper being issued into the market and allows for certain assets to be funded at a longer duration. And when you think about infrastructure, you think about energy, you think about real estate, and importantly, at the moment about data centers that there's an opportunity to tap that longer-dated paper. It will also depend on the nature of the assets that need to be financed, often certain assets just need short term, whether it's securitization, you just need to back that until it's paid off. So it really is a matter of what assets are out there and the pool of assets that need to be financed.

And that's why it's important when we look at our first-time mandates, we're expecting around about 750 to 800 new mandates this year and the nature of those, whether they're long dated and whether there's access, we did see that during COVID and normal corporates like Moody's issued a 40-year bond during that period. So it doesn't always have to be those long-dated assets.

So I promise I'm going to touch on AI. But before I do that, question on your pricing power and just the broader competitive dynamics. How do you view the durability of your pricing power? And do you ever get pushed back from clients?

Yes. I mean, first of all, we are constantly in discussion with our customers with regard to the value that we bring. And I don't know if people are familiar with this slide. This is a perennial in the Investor Relations deck, but we've just updated this.

Posted on the IR website.

Yes, this is on the IR website. It's just gone up there. And when we think about the value of a Moody's rating, it is really saying to the market, do you get a better pricing with a Moody's rating than a bond that goes to market without a Moody's rating. And that could be with other agencies or no rating at all. What we are indicating here, and this has been done by an independent firm is that on an adjusted -- option-adjusted spread basis that with a Moody's rating, you are saving about 22% in terms of your overall coupon. And if you actually translate that into dollars, and this is a $1.5 billion a 5-year term, you can see the difference on what that translates into, which is a substantial amount of dollar savings for the issuer so as long as those dynamics remain, then the pricing power of Moody's rating and the basis points that we charge falls into that. That makes sense?

So artificial intelligence, obviously, a big topic at the conference this year. What are the implications of AI for Moody's Investor Service starting with the revenue opportunities?

Yes. I mean, first of all, when we think about the revenue opportunity, what do we do? We rate bonds. We rate bonds of an instruments of major players that are issuing in the market. We have estimated in a recent paper that there will be approximately $3 trillion of investment going into data centers and to the related power associated with that and a good portion of that amount will be debt and rated. And when you think about the sizable requirements of that sector. That does not include the amount of debt that is being now issued by the hyperscalers. And in a number of cases, we're seeing CapEx at multiples of historical levels. And again, those are rated entities and those are issuing debt to support that CapEx. That all feeds into that revenue and that upside that I talked about on one of the earlier questions.

And then to the topic of data center build-outs and hyperscaler build-outs. A lot of times, I think these are big chunky bond issuances. How do we think about how those issuances scale from Moody's in terms of the revenue? Is issuance volume going to grow faster than issuance revenue? And even if it were to happen, I suppose it's a good problem to have.

Yes. So when you think about the nature of a frequent issuer. And as we are seeing a number of these hyperscalers are starting to issue very large sums on a frequent basis. What we will do is engage with the finance teams at these companies to understand their profile of debt issuance over the next 3 to 5 years. And if that profile moves that they will become a substantial and frequent issuer, then we may shift our pricing scenario to accommodate that. However, if there's a short-term boost in the next 1 to 2 years and then they are not issuing the same amount in the outer years, then it may make more sense to stay on more transactional pricing. So we will follow these individual companies. We'll talk to them on an individual basis and we will make sure that, that pricing arrangement meets their needs going forward.

And then how is MIS using AI to drive operational efficiencies?

Yes. One of the key things to -- first of all, think about is that -- and I think I said this last year that we have been on a multiyear investment in our technology stack and our data stack. We sit on substantial amount of data. And when AI and particular Agentic is available, which has happened in the last 12 to 18 months. It gives us a significant boost to the efficiency of what we do because when you think about what do we do, we process first and foremost a substantial amount of debt ratings. We rate approximately $6.6 trillion a year. And that is processed through regulatory requirements, and therefore, you can use AI and Agentic in particular, to help you with all that processing that helps you streamline the teams and the focus of the teams.

When it comes to the analytical teams that we are bringing in vast amounts of data and the use of the agentic tools to gather to pass and to put into these data sets, both on a -- again, on a structured data, whether that's spreads or unstructured data that you're pulling that you can use these tools to our advantage to extend the opinions and insights that we have and what that allows our analytical teams is to get to that credit analysis point much earlier and therefore, time save with regard to the focus and the prep. So both operationally and analytically, we are benefiting from AI.

And I think building on that, your MIS segment had incremental margins that were north of 100% last year. I think some of that was due to bonus accrual timing, but has AI structurally changed the incremental margin profile of the business?

I would say that where we are at the moment is that it's probably too early to state that we've got a structural change. But what we are gaining is incremental leverage, being able to accommodate more volume through the business. And if you even think about the refinancing study prior to the pandemic, the refinancing amounts were about $2.8 trillion, $2.9 trillion. Now when you look at the study, that's north of $5 trillion and we are able to process much of this on a more moderated increase in our resources because of the efficiencies and the way that we operate inside the company. So it's very early to call is it a structural change. But what we're seeing is that we're increasingly able to beat volume -- what I like to call volume agnostic as the volumes go up, that we're able to hold much more steady on our cost base.

Are there any regulatory constraints on how you deploy AI within MIS?

When you -- I mean, first of all, we are a heavily regulated business around the world and many jurisdictions have particular requirements of what you can and cannot do in the ratings process. So we try to level that out in order to provide a global service. What we do is constantly talk to each of our regulators to keep them updated as we are implementing our AI and agentic strategy. A number of the jurisdictions require that there is human judgment in the decision-making inside the company. And more importantly, that we are often dealing with significantly complex transactions, private transactions with heavy documentation that does still require a very human involvement.

But going back to my earlier comment, that what we also talk to our regulators about is that we can get to the starting point of our analysis much faster and in a controlled manner by using agentic tools and broader AI and that is something that is seen as acceptable as we invest further, and we will keep them on that journey with us as we continue to implement and get those efficiencies, but also the controls. And that's what many of our regulators are focused on. Are we safely playing in the broader financial ecosystem? And are we controlled in the manner that which we produce ratings and we believe we can prove that, too.

Structured finance question for you. Last year at a different conference, your CEO, Rob Fauber, mentioned that sometimes Moody's methodology and structured finance can lead to issuance moving away from you. And obviously, one of the big outcomes of the financial crisis was a clear separation between the business side of things and the rating side of things. So what sort of levers can you pull running that business to try to grow market share in structured finance, but while still also kind of remaining true to your guiding principles?

Yes. I mean the backbone of running a rating agency is front and center, you must get the rating right because this is all about the trust that people have in the market. And the challenge that you have in terms of the business versus the analytics is that you are driving to get the rating right and the cost of that opinion may be that the issuer of that transaction does not like that opinion and will decline to publish that in the market. That is something that we have to live with because at the backbone of what we need to do, we need to get that rating right. We have methodologies that cover all of the asset classes. It all depends on the structure of a particular transaction and the layering in that, whether, in fact, they want to go with a Moody's rating.

The other thing about our structured finance business is that we are continually investing in the innovation. And many of you may have seen that Moody's was the only rating agency on the inaugural CLO from the World Bank, and that CLO was backed by emerging market loans, a very first of its kind. Similarly, when it comes into new asset classes, whether it's ABS for data centers that we recently just published the first AAA rating on a structure for that. So you have to distinguish between certain run and flow transactions where we may have a different opinion to others. And then the innovation and the front end of that innovation where we play very heavily.

And then staying on the theme of competition and turning to the private credit space. Obviously, there's multiple components to private credit. It's not just one single thing. But broadly speaking, how would you evaluate Moody's competitive positioning in the private credit markets as opposed to the public credit space.

Yes. I got lots of questions on this one. I mean, first and foremost, credit is credit. Whether it's in the public market, whether it's in the bank market or whether it's in the private space. And when it comes to methodological rigor, we use the same methodologies, whether it's in the private space or in the public space. And we continue, again, to compete on the standards in that market. And as the private credit market continues to mature, then the need for even greater transparency, the need for even greater rigor lends itself to coming to a player like Moody's that can offer a full service across fund finance, across asset-backed, across infrastructure, and into the insurance and the large players that are buying that.

So we feel we're in a very good position. And as this market gets increased scrutiny and if there is any market turmoil that raises that scrutiny, then that's where we can offer our services as a major player in this space.

And then following up on that, a comment was made on your last earnings call that you guys have seen about 70% year-over-year growth in the number of MIS private credit-related deals. Can you give us some color on the sorts of mandates that Moody's is winning? And are these wins a function of Moody's gaining market share within private credit? Or just there's more ratings in general in the private credit space?

Yes. Well, first of all, the private credit market continues to grow. And it also continues to grow not only volume but also in complexity. And again, this is why many of the players as they continue to mature, in their role, and they want greater transparency that they want to come back and deal with someone like Moody's. So when you think about the nature of transactions, there is fund finance, which is often at the very front end and you're dealing with transactions like subscription lines where pooling of funds to be deployed to transactions. So there's ratings at the front end.

There is also money that is coming from insurers, and we often have a relationship with the insurers. And then that money gets applied and that can get applied into structured finance, it can get applied into infrastructure finance, broader asset-backed finance, and that's where additional transactional ratings are required because if some of those transactions need to go back onto a balance sheet of an insurer, then there's a requirement to gain capital relief that you need a rating from an NRSRO and as there again, is greater review and transparency required that many of those insurers are wanting to evidence that they have a rating from a very credible player like Moody's.

So we're seeing the front end, we're seeing the insurance end, and we're seeing all the transactions that come through on the deployment of funds and that could be short-end investment-grade structured type transactions or it could be very long dated infrastructure paper, whether it's in data centers or others. So we're seeing it across the board.

Very helpful. So I certainly wanted to take advantage of Mike's presence here today to ask a lot of questions about the rating side of things, but I think we'd be remiss if I didn't ask any questions about the AI threat opportunity as it pertains to Moody's Analytics. So Kiera, there's so much fear of the unknown as it pertains to AI right now. Can you speak to what gives Moody's confidence in the competitive moat around Moody's Analytics and why LLMs won't be the drawbridge for competitors to cross that moat?

Sure. Thank you so much for the question. I think as AI becomes the interface for decision-making, it's not just that we're supplying data to these AI models. We're embedding the trusted context in the analytics, in the data and in the judgment where customers are actually making these decisions. And broadly, we service very regulated customers where we've heard from them that good enough is just really not good enough. So maybe a few things just to think about as you're thinking about our competitive moat around the data, the context layer that Rob talked about and where we -- how where work gets done. So first, as you all know, we have a very massive proprietary data set that we've been building over quite a number of years.

And it's not just the data, but it's the process of taking all of that underlying data models, the ratings, the research, the credit assessments and putting that around a single normalized record for each entity. And what this enables is that we can have a comprehensive interconnected view of that entity, which supports agentic and automation. When it comes to the context layer that we talked about on our most recent earnings call, this is the layer that sits between the raw data and the AI reasoning agent.

And this is what makes the data usable for reasoning. It has to be structured. It has to be governed. It's what the data actually needs. So when you think about how that relates to entities, time, different scenarios, is when and how this data should be used in those particular scenarios. So if you take Orbis, for example, it's not just the company data. It's the years of the entity resolution that we have there. It's the ownership mapping, it's the expert judge that's been applied to that. And then, of course, we have a very complex network and ecosystem of the IP rights and the licenses to be able to use that data. And this is the context that goes into our analytics and our methodologies. And as Rob called it makes this data decision grade.

Lastly, as we've talked about a bit more on the most recent calls, we're embedding ourselves into where the work gets done. And so whether that's into a customer's own internal system, their workflows, they're increasingly internal different AI environments that they may use or third-party interfaces. As AI accelerates, we actually think that Moody's is needed more, not less.

And then maybe to follow up on that point. So Moody's is embedding AI within your products and your services and starting to monetize those efforts. What are a couple of highlights that you guys are pretty excited about right now?

Yes. I think the 2 that I would sort of point you to is when you look at the growth that we had in Q4, the strongest growth that we had actually came from our most strategic customers. And then when you look at that over the year, those customers actually grew at twice the rate of the MA customer base overall and have increasingly become very sticky and durable customers for us and recurring revenue streams. The second thing is we've talked about a cohort of AI customers at big institutions. And that's actually what's driving the growth. We've seen those customers grow, again, that have upgraded -- upgraded to standalone or upgraded to an AI version of our product. Those customers have also grown at twice the rate. So we see that as a very good proof point and a leading indicator of what's to come.

Perfect. And then maybe a good place to end the conversation. What are some of the key messages that you want to make sure people walk away with today.

I'll leave with 2 punchy final comments, which first of all, we believe that Moody's is a durable compounding business with very solid positions, both in the ratings side and on the analytics side. And then secondly, as AI becomes more central on how financial decisions are made, our differentiated position is with regard to what Kiera just mentioned, this decision grade data and where we play in the financial ecosystem and what our customers need from a player like Moody's. And as those capabilities are embedded in everything that we do, then we continue to compound and be an AI winner in this space.

Terrific. Well, I think that's a great place to wrap up. Thank you, everybody, for joining us.

Yes. Thank you, everybody. Thank you for your interest. Thank you.

Good day, everyone, and welcome to the Moody's Corporation Fourth Quarter and Full Year 2025 Earnings Call. At this time, I would like to inform you that this conference is being recorded. [Operator Instructions]

I will now turn the call over to Shivani Kak, Head of Investor Relations. Please go ahead.

Thank you. Good morning, and thank you for joining us today. I'm Shivani Kak, Head of Investor Relations. This morning, Moody's released its results for the fourth quarter and full year of 2025 as well as our guidance for 2026. The earnings press release and the presentation to accompany this teleconference are both available on our website at ir.moodys.com.

During this call, we will also be presenting non-GAAP or adjusted figures. Please refer to the tables at the end of our earnings press release filed this morning for reconciliations between all adjusted measures referenced during this call in U.S. GAAP.

I call your attention to the safe harbor language, which can be found towards the end of our earnings release. Today's remarks may contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. In accordance with the act, I also direct your attention to the Management's Discussion and Analysis section and the risk factors discussed in our annual report on Form 10-K for the year ended December 31, 2024, and in other SEC filings made by the company, which are available on our website and on the SEC's website. These, together with the safe harbor statement, set forth important factors that could cause actual results to differ materially from those contained in any such forward-looking statements.

I'd also like to point out that members of the media may be on the call this morning in a listen-only mode. Over to you, Rob.

Thanks, Shivani, and thanks, everybody, for joining today's call.

I'm going to start with the highlights. And 2025 was a record year for Moody's. It was driven by consistent execution against the long-term demand trends that we've discussed over the last several years. And we finished the year with strong fourth quarter performance across both ratings and analytics and delivered robust growth and meaningful capital returns to shareholders. Now we're scaling decision-grade contextual intelligence embedded directly into customer workflows across our platforms, third-party systems and AI-enabled interfaces so that we're present where critical decisions get made. And as technology and the ways of working continue to evolve, we enter 2026 well positioned and confident in the opportunities ahead.

Now we had strong top line performance across the company in 2025. Total revenue exceeded $7.7 billion. That was up 9% year-over-year and 9% in both Ratings and Analytics. We expanded adjusted operating margin to 51.1%. That was up 300 basis points as we drive further operating leverage into the business. And these results are being driven by sustained customer demand for our decision grade data analytics and insights amidst very large funding needs, greater market complexity, heightened risk and resilience needs and compliance requirements.

Now adjusted EPS -- sorry, adjusted diluted EPS reached a record $14.94, that was up 20% year-over-year. And that represents a earnings growth over the past 3 years. So it's something like a 20% CAGR since 2022.

Now let me turn to Ratings. And issuance and investment cycles came together very powerfully in the fourth quarter, resulted in the busiest fourth quarter in our history. And the investments that we've made over several years have really positioned us to capitalize on this activity and that drove record revenue this past year. In 2025, we rated $6.6 trillion of debt. That was an all-time high, supporting investment across infrastructure, AI-driven data centers, energy finance, energy transition finance and private credit. And in the fourth quarter alone, we rated more than $70 billion of issuance for companies, including Alphabet, Amazon and Meta, in part related to their AI investment programs.

Moody's was named Best Credit Rating Agency in the U.S. by Extel again. That's for the 14th consecutive year, and that really reflects our role at the forefront of global debt markets. In December, we issued a request for comment on a cross-sector stablecoin rating methodology. And as the use of tokenized cash continues to accelerate, the total value of issued stablecoins is forecasted to reach $400 billion by the end of 2026 and $2 trillion by 2028. And our methodology, which is the first such framework from a credit rating agency, will position Moody's to play an important role in the digital finance ecosystem.

Now in private credit, demand for ratings continues to accelerate. Private credit revenue in MIS grew by nearly 60% in 2025, reflecting both market growth and our expanding role in the sector. And we developed new methodologies and deepened our analytical and commercial engagement to capture rising demand for transparent, independent credit assessment. And that momentum is translating into tangible wins. Last year, we were the sole rating agency on the largest private credit CLO of the year, a $1.5 billion issuance by Blackstone.

Now pivoting to Moody's Analytics. We finished 2025 on a strong note there as well. We delivered net growth that outpaced the fourth quarter of 2024. And this performance included meaningful contributions from our highest priority growth areas. That includes our lending and credit decisioning solutions as well as decision-grade KYC data. We also closed the year with strong momentum in AI-related sales, ranging from specialized workflow agents to AI-ready data sets, and I'm going to talk about that in just a few minutes.

Importantly, our strongest growth came from our largest strategic customers. These customers contributed over 30% of the total MA net growth in the fourth quarter and for the full year, grew at twice the rate of the rest of the MA customer base. So this is durable high-quality growth with clear evidence of customer adoption. And I want to emphasize durable because the nature of MA's revenue growth is increasingly recurring and scalable, so recurring revenue grew 11% and represented 97% of fourth quarter revenue. So this, combined with some real execution discipline, enabled us to deliver 190 basis points of margin expansion and an adjusted margin of almost 36% in the fourth quarter.

We set our focus on scaling MA's recurring revenue base a few years ago. And now we're making further proactive adjustments to our portfolio to reinforce that strategy. So in December, we closed on the sale of our Learning Solutions business, that was primarily reported as transactional revenue, and it really was no longer core to our strategy. We also announced the sale of our regulatory reporting business which serve customers with relatively limited cross-sell opportunities across other banking offerings.

And underpinning all of this is our commitment to delivering best-in-class solutions. And that commitment was reinforced by our recognition as the #1 provider in the Chartis RiskTech100 for the fourth consecutive year, and that reflects the trust that customers place in Moody's to support workflows and decisions that matter most. And we see that market recognition reflecting a broader truth that as AI becomes a new interface for decision-making, the need for trusted context increases, not decreases. AI systems require verifiable permission, domain-specific data and analytics to produce outputs that are accurate, explainable and defensible that's exactly what Moody's provides, and it gives us the opportunity to become even more deeply embedded in customer workflows.

So we see this clearly in recent customer behavior. Customers who have purchased or upgraded into at least one stand-alone Gen AI or agentic solution are retained at a rate of 97% and are growing at roughly twice the rate of the rest of the customer base. So this is an experimental usage. AI adoption is driving greater consumption of our proprietary data, expanding our share of wallet and reinforcing long-term customer economics, particularly amongst our largest strategic accounts. And a key reason for adoption that it's accelerating is how customers consume our intelligence.

So Moody's solutions are delivered through our own applications. And increasingly, they're embedded directly into customers' existing technology stacks and third-party workflow platforms. That includes systems like Salesforce, ServiceNow, Coupa, [ NTAP ], Databricks. And we've made our content available through smart APIs and MCPs and specialized agents for consumption through our customers' own AI platforms and going forward through AI portals like Claude and OpenAI. And this is enabling us to serve our customers on a different level and in different ways than ever before.

So for our banking customers, AI-enabled workflows such as automated credit memos and early warning systems are delivering some material efficiency gains, reducing cycle times while improving consistency and regulatory compliance. And our flagship lending solution that we call CreditLens remains the fastest-growing product in the banking portfolio. with growth approaching 20% in 2025. And I have to tell you, our new packaging is working. Roughly 2/3 of eligible renewals converted to our AI-enabled lending suite in 2025 with an average uplift of about 67%.

In the fourth quarter, we also sold a large globally systemic important bank, our Gen AI-ready data and smart APIs to embed into their digital credit platform in order to automate financial analysis and accelerate wholesale lending decisions. A Tier 1 U.S. bank has deployed Moody's agentic solutions to automate credit memo creation. They've told us that it can generate roughly 35% to 40% of each memo and saves analyst hundreds and hundreds and thousands of hours of time equating in some cases, the millions of dollars saved. And that work is expanding into enabling real-time commercial real estate risk monitoring, API-based screening and KYC where we displaced a competitor in the fourth quarter.

And the same holds true around the world. In the fourth quarter, we signed banks in APAC and the Middle East to embed our AI-enabled spreading and memo generation solutions into their loan origination platforms. And we heard back from them. They're reducing decision times in some cases by as much as 80% and cutting loan processing cycles, in some cases, by as much as 15x. So some real efficiency.

And KYC continues to deliver mid-teens growth driven by customers' trust in the quality of the governance and the global coverage of our data. So a great example is our partnership with one of the world's largest e-commerce and technology companies, where we've grown that relationship more than tenfold over the last 3 years. And today, our data is integrated across KYC, supplier risk, credit risk, transfer pricing and sales workflows and covers more than 15,000 suppliers across automated entity resolution, screening and early warning signals.

Similarly, in the fourth quarter, and you -- there's a pattern here, one of the world's largest global payment platform, signed a multiyear, multimillion dollar agreement to embed Orbis via API into their new customer onboarding processes. And they're treading 2 critical requirements. They're creating a smooth customer experience through prepopulated applications while addressing enhanced KYC due diligence requirements from their regulators.

And just to bring it up another notch. Moody's data is being used at the highest levels of the intelligence spectrum. In the fourth quarter, Interpol announced they're leveraging our ownership in firmographic data to support their operations targeting illicit finance, with the recent operation resulting in 83 arrests across 6 countries. And it's in environments like this, our accuracy, providence and the auditability are nonnegotiable.

Now our data can't be synthesized from public sources. It reflects how ownership and control actually work in the real world, cutting through complex multilayered structures across jurisdictions, and reflecting years of proprietary data curation, entity resolution and relationship mapping. And it's that breadth and depth that makes our data both AI-enabling and AI resilient. And we see some similar dynamics in insurance as well, where rising climate-related losses are driving demand for more data-intensive, model-driven solutions. In December, we launched our high-definition severe convective storm model. That was calibrated on more than $55 billion of granular claims data, and that was contributed by the industry and available nowhere else. And then we deliver that SCS model through our cloud-based intelligent risk platform, and early adoption has been strong, reflecting the demand for more precise underwriting as these secondary perils as they're called, increasingly behave like primary risk.

So we believe the common thread here is clear. As AI proliferates, value accrues to providers of trusted context, decision grade data and analytics that are embedded, auditable and difficult to replicate, and that is exactly where Moody's sits.

So stepping back, our confidence heading into 2026 is grounded in the durability of the business model that we've built and the discipline with which we allocate capital. And we operate businesses with structurally attractive economics complementary revenue streams and deeply embedded customer relationships. And it's these powerful business dynamics that allow us to generate strong cash flow and invest confidently in the areas with the highest long-term returns while continuing to expand margins.

So in Ratings, we continue to broaden our methodologies and deepen expertise in areas aligned with the huge global funding needs and market innovation. And that includes infrastructure and AI investment, public and private market dynamics, energy transition and digital finance. At the same time, we're further investing in our global footprint to ensure that we are supporting the markets and issuers that will define the next phase of growth.

In Analytics, we're advancing a very deliberate strategy to position Moody's data as a trusted context layer for AI. We're accelerating efforts to link our massive data estate, expand network-based insights and make our content more actionable within customer workflows. And given the traction we're seeing, we've established a dedicated sales team focused on agent-ready data in 2026, and that reflects both customer demand and our conviction in this opportunity.

Now from a product standpoint, our innovation engine is highly active with the majority of 2026 growth expected to come from 3 primary areas. First, in lending and credit decisioning we're upgrading customers onto a more integrated AI-enabled platforms. This includes moving CreditView users to what we call Moody's view, expanding CreditLens into a broader lending suite. And delivering a genetic capabilities such as automated credit memos and early warning tools. And we're also expanding and packaging our credit tools specifically for private credit origination and underwriting where demand continues to grow.

Second, in KYC and compliance, we're focused on driving efficiency and scale. For financial institutions, we're delivering productivity gains through workflow partnerships and piloting screening and diligence agents. For corporates, we're rolling out a simplified modular compliance suite that scales in data and functionality based on the company's size, exposure and sophistication. All of that will be delivered through the Moody's [ risk compliance ] platform.

And third, in insurance, we continue to invest across catastrophe modeling, underwriting and risk transfer. This includes ongoing migrations to our cloud-based intelligent risk platform, new high-definition model offerings and enhanced data management capabilities with our new Risk Data lake. We're leveraging our geospatial artificial intelligence alongside Moody's hazard and risk scores to deliver a holistic property intelligence solution that supports underwriting decisions. We're also expanding into casualty and financial lines by combining Praedicat's capabilities with Moody's data where we've demonstrated strong signal value and customer interest. And in the capital markets, we see an opportunity in catastrophe bonds as climate risk increasingly migrates into structured finance, an area where Moody's is uniquely positioned at the intersection of models, ratings and market infrastructure with the recent launch of our cat bond rating methodology and revamped cat bond modeling platform.

Across both Analytics and Ratings, a critical enabler of this growth is the continued build-out of our AI context layer and knowledge graph. And we're capturing large new structured and unstructured data sets and leveraging our global connectivity to enrich how our AI systems and our analysts understand risk, relationships and exposure. It's not a point solution. It is a foundational capability that compounds the value of everything that we do. And taken together, this is a portfolio designed to perform across market environments. It strengthens our competitive advantages, extends our growth runway where we have a clear right to win and supports durable value creation for shareholders.

And before I hand it over to Noemie, I want to thank our teams for their exceptional work in 2025. Noemie, over to you.

Thanks, Rob, and hello, everyone. The fourth quarter capped off an outstanding year across the board. While we experienced tariff-driven uncertainty that resulted in a market-driven air pocket early in 2025, conditions recovered as the year progressed, and we finished very close to our initial internal expectations.

Let me start with Moody's Analytics. In 2025, we sharpened our focus on our highest conviction growth opportunities, while continuing to actively optimize our product portfolio and manage costs with discipline. For the full year, MA revenue grew 9% and adjusted operating margin improved by 240 basis points to 33.1%. This performance builds on our already strong financial profile, delivering consistent growth at scale with a very high concentration in recurring revenue and retention in the low to mid-90s. ARR reached $3.5 billion, up 8% and which is in line with organic constant currency recurring revenue growth also at 8%.

Now before turning to the drivers of ARR growth, I want to do a quick reminder on the MA revenue disclosures. Reported revenue reflects period results and that includes FX and M&A. Organic constant currency recurring revenue measures renewable software licenses decision grade data and world-class content and analytics, which collectively represents an incredibly durable core business, and that removes FX and M&A. However, the growth rate can still vary quarter-to-quarter due to upfront revenue recognition timing, especially for on-premise licenses. Now ARR is forward-looking. It's normalized for FX and M&A. And it reflects the current position of recurring contracts. As a result, this gives, in our view, the clearest perspective of customer demand and the future revenue base.

Using that lens, let me walk through a few highlights. Starting with Decision Solutions, which includes KYC, insurance and banking and continues to be a key growth engine for MA. These businesses delivered double-digit ARR growth and represent approximately 45% of total MA ARR, underscoring both their scale and strategic importance.

KYC remains the fastest-growing component, with growth consistently in the mid- to high teens over the past 2 years and 15% ARR growth at the end of 2025. Growth in KYC continues to be driven by both deeper penetration with existing banking customers, especially Tier 1 institutions as well as expansion beyond our traditional financial services customer profile. We are increasingly seeing demand from nonfinancial customers for unique solutions to address complex, high-stakes compliance challenges, as you heard Rob talk about with the Interpol example. We delivered very strong net growth in the quarter, supported by both new customer wins and continued cross-selling and expansion with existing relationships.

Now a few recent deals illustrate the power of our solutions here and our ability to deliver trusted outcomes for customers. As Rob referenced earlier, we secured a competitive KYC displacement win as a tier bank that also leverages a broader set of Moody's solutions. And what this example illustrates is our ability to build and more broadly scale relationships over time. In fact, the relationship grew by more than 20% in '25 and continues to present meaningful expansion opportunities in '26.

Beyond the payments company customer example, Rob mentioned earlier, we won new business with 2 manufacturing corporates including a leading global aerospace and defense company facing new U.S. export control requirements. In this case, the customer needed a solution capable of identifying ownership and control structures across complex global entities to comply with the BIS 50% role and the evolving export restrictions. We are uniquely positioned to address this kind of customer challenge because of our ability to link together billions of ownership structures through our extensive network of local registry relationships.

Turning to banking. Our focus on customer mix here differ quite a bit from KYC. While KYC is anchored in deep relationships with Tier 1 banks and corporate customers, our banking offerings in decision solutions are much more significantly concentrated with Tier 2 and Tier 3 institutions, where demand is centered on scalable, configurable end-to on workflow solutions that are ready to deploy. Banking delivered ARR growth of 8%. That's up from 7% in the third quarter. And this business includes our lending suite as well as risk regulatory and finance solutions. We are actively investing in expanding our end-to-end offering for lending, including with AI capabilities from the Numerated and [ AAI ] acquisitions, strengthening decisioning, automation and customer experience.

In this line of business, we have been deliberately reducing transactional revenue over the last several years, primarily by expanding our partner network to serve the lower-margin implementation services for our solutions. And you'll see in 2025, this trend continued and was compounded by the recently completed divestiture of the Learning Solutions business, which is a further sharpening of our focus within the banking portfolio towards the highest demand and quality revenue.

Now turning to insurance. demand from our -- for our most sophisticated high-definition models and cloud-based intelligent risk platform drove 7% ARR growth for the year-end and that's an increase of 21% over the last 2 years. And looking at this 2-year view is important because 2024 was particularly strong, reflecting record levels of customer migrations on to the IRP combined with large model upgrades and new product adoption.

Stepping back, our recent performance underscores the successful integration and execution of growth strategies we laid out for the RMS business following the acquisition. In fact, we completed and slightly exceeded the financial target associated with that transaction, adding $150 million run rate revenue by 2025. Now achieving that milestone required shifting RMS from flattish growth in 2021 to a high single-digit CAGR, including synergies over a 4-year period. That's a transition that was supported by sustained customer demand and meaningful platform-led upsell activity.

Next, turning to Research & Insights. We achieved 8% ARR growth in this more mature business, underscoring the durability of demand, continued innovation and improved customer retention. As Rob shared, we are enhancing CreditView with an expanding set of Moody's content and agentic solutions that improve productivity, insight generation and workflow integration. This reinforces its role as a core decision support platform and driving continued option.

Finally, Data & Information delivered 7% ARR growth, supported by strong pricing power and sustained customer demand across 2 distinct but complementary areas. Ratings data fees are the primary growth driver within the segment, with ARR growth well above the overall line of business. And that underscores their decision great nature and central role in customers' credit risk and investment workflows. In parallel, our decision grade data estate, which includes company ownership, people and news, is increasingly embedded in customer workflows across a wide range of third-party risk use cases.

Now growth in this area can vary year-to-year based on deal mix, including the timing of closure of renewals of large enterprise-wide data agreements versus sales to smaller institutions. And as we shared, 2025 was impacted by those related cancellations across several U.S. government agencies. Excluding these items, underlying demand and customer engagement remains solid. We've had several notable Orbis wins in the fourth quarter, including one with a large global bank for enterprise-wide access and a new partnership with one of the world's largest asset managers underscoring the breadth, relevance and durability of our data estate.

Turning to margin. As I mentioned earlier, Moody's Analytics delivered ahead of the target we originally set for 2025. And that's even as we absorbed acquisition-related headwinds and continue to invest in future growth. What differentiates Moody's Analytics is our ability to invest in growth while expanding margins. We expect to be able to sustain this balance for the years to come. Because beyond near-term cost actions, we're making structural changes to how roles are set up in our core processes.

Let me give you an example. We're building out a single standard Gen AI-led product development life cycle process across MA, which we expect will drive higher productivity, improved quality and faster delivery for customers. In parallel, we are embedding advanced analytics and Gen AI into other core workflows, such as sales account planning, which allows us to scale impact and customer value without proportional increases in headcount.

Turning to MIS. Fourth quarter revenue was up 17% year-over-year and the performance here was driven by activity that was very strong, particularly in the investment-grade asset class within Corporate Finance, where tight spreads, strong investor demand and several large jumbo deals from hyperscalers supported record issuance. Project & Infrastructure Finance also had near record issuance in the quarter. Private credit across all asset classes grew 40% in Q4 from particularly strong activity from finance and securitization. Transactional revenue increased 22% in Q4, supported by 10% issuance growth and a more favorable mix as lower yield bank loan repricing activity declined versus the prior year quarter. MIS recurring revenue was particularly strong, up 9% year-over-year in Q4.

Turning to margins. MIS delivered a full year adjusted operating margin of 63.6%, representing 350 basis points of year-over-year expansion. And that reflects strong operating leverage in the Ratings business, driven by continued technology investments and disciplined capital allocation. Looking forward, we expect investment needs will continue to increase, and that remains an attractive funding source. Accumulative monetary conditions, declining default rates and healthy investor demand for yield should support access to capital across sectors.

For the full year 2026, we expect total issuance to increase at a low single-digit percent pace, followed by ongoing refinancing needs and 40% to 45% increase in debt-funded M&A issuance. We also expect ongoing growth from private credit as well as issuance from hyperscalers and AI-driven data centers. Based on our issuance outlook, we expect MIS revenue for 2026 to grow at a high single-digit percent pace. Our forecast project year-over-year growth across all 4 quarters, strongest in the first half and moderating in the second. We're projecting a full year operating margin of approximately 65%, that's up 150 basis points versus 2025.

For Moody's Analytics, reported revenue guidance is at the high end of mid-single-digit growth, [ including ] a 180 basis point headwind to year-to-year growth from the divestiture of our Learning Solutions business. Adjusting for the effect of this divestiture and uneven foreign exchange rates across the 2 years, we expect organic constant currency recurring revenue growth to be aligned with ARR in the high single-digit percent range. From a margin perspective, our 34% to 35% adjusted operating margin outlook reflect approximately 150 basis points of improvement at the midpoint.

Putting this all together, we expect MCO revenue growth in the high single-digit percent range and MCO adjusted operating margin, likewise expanding by 150 bps to the [ 53% -- 63% ] range for 2026. Our 2026 adjusted diluted EPS guidance is $16.40 to $17, implying approximately 12% growth at the midpoint. We expect the effective tax rate to be in the range of 23% to 25% in 2026, a more normalized overall rate after we realized a sizable M&A-related onetime benefit in 2025. We've also added a new appendix slide with additional detail to provide further insights into the key drivers of our results and 2026 outlook assumptions.

Lastly, we're expecting free cash flow to be in the range of $2.8 billion to $3 billion, 13% growth at the midpoint. Now this guide is impacted by a notable $100 million increase in CapEx for the build-out of our New York headquarters and London office space. We expect to repurchase approximately $2 billion in shares during the year and announced a 10% increase to our quarterly dividend.

Overall, our capital plan calls for a return of at least 90% of our free cash flow to shareholders in 2026. Given the recent market activity in [ the sector ] and our strong fundamentals and durable growth outlook, you can expect us to be aggressively buying back shares at these levels.

In short, both our 2025 results and our outlook for 2026 demonstrate the strength and differentiation of our financial profile and confidence in our ability to continue to deliver long-term value for shareholders.

And with that, operator, we're now happy to take questions.

[Operator Instructions] Our first question comes from Curtis Nagle with Bank of America.

Terrific. Maybe Rob, just a quick one from you. Just from a portfolio perspective for MA, it seems like it's in a pretty good place. But I guess, do you feel like, at this point, you have the right assets, the highest growth, the ones you think are most confident in terms of investment? Or should we expect more paring this year?

Curtis, first of all, welcome to the call. It's great to have you on today. I would say we feel very good about the assets and the capabilities that we have. And you heard me talking about this, Curtis, a bit in my prepared remarks. I mean, I think we all understand that data and trusted data is going to be the fuel for AI and especially for the big regulated institutions that are big customers of ours. And so we feel very good about having built out this massive data estate.

And then now, as you heard me talk about, it's about linking that and it's about the ability to draw insights across that network of data. So I think -- and again, I think we also understand that proprietary data sets will be at premiums going forward. And wherever we have an opportunity to add uniquely valuable data into this giant data estate, putting it into our context layer, helping to build out our network graph. I think you're going to see us do that.

In terms of the trimming, I think this just -- you hear us talking about where we're making the more concentrated bets. And I talked about lending and credit decisioning, KYC and compliance and insurance. And those are the places where we think we bring the strongest set of capabilities, the deepest customer relationships that give us the strongest right to win. And so we felt there was just an opportunity to look across the portfolio at things that weren't as central to that and had an opportunity to, as you said, kind of prune the portfolio and allow us to focus even more on the areas of the greatest scalable growth opportunities.

Our next question comes from Alex Kramm with UBS Financial.

I want to stay on MA. Thanks to both of you for all the AI detail, a lot of impressive stats. On the flip side though, it doesn't sound like it's really translating into ARR revenue yet, maybe it is. But obviously, if we look at the guidance and the results, relative to your medium-term outlook, those have kind of softened a bit. So I guess the question is, when is AI really going to contribute? And if it's already contributing, are there some other issues elsewhere in the business. So maybe an open question there.

Alex, thanks. And I think in a way, there's kind of 2 parts that I want to unpack in that question. The first is kind of your observation around the trajectory of MA. And I would say that our fourth quarter ARR was in line with the third quarter. And as you'd expect, when you've got I'm going to say, kind of a portfolio, we're selling into very different customer bases. There's some puts and takes in terms of what's growing faster and what's growing not as fast.

If you look at kind of the ARR trend across the portfolio I think you'd see that actually banking, research and data actually picked up a little bit and we had some headwinds with insurance and KYC. And as you heard Noemie mention, we've talked about before in the call, some of that with KYC was impacted by [ those ]. And you see our guide. That's consistent with these growth rates. I talked about the new products and the cross-sell and upgrade pathways that are going to drive that growth.

But I think maybe one other point I want to just double-click on. Everybody wants to understand how much revenue is being generated by AI. And there were 2 stats that again, I want to come back to because I do think they are leading indicators for us. One, is the fact that those largest accounts for us are growing at about twice as fast as the rest of the portfolio. That's really important because that's where we have the deepest engagement with the most sophisticated institutions on the planet, and that's where they all want to be able to consume our content and bring it into their own AI workflow orchestration platforms and consume it through AI portals. So there is a lot of AI-oriented engagement with those big institutions. That's what's driving and importantly, driving that growth.

And then second, we have that stat about the cohort of customers who have bought at least one stand-alone or [ packet ] or upgraded into an AI solution, that's growing twice as fast, again, because of the level of engagement. So I think, Alex, I feel good that the most sophisticated institutions are where we've got the most growth and the most engagement around AI. And our view is that that's going to then trickle through the rest of the customer base over time.

Our next question comes from Manav Patnaik with Barclays.

I was just hoping on the rating side, if could just help us with the cadence for the year in terms of how you assume the issuance trajectory there?

Yes. Manav, great to have you on the call. So I'm going to start with issuance and then maybe I'll just -- I'll go into revenue real quickly for you. because I know that will be helpful.

So we're expecting issuance activity like we typically do, to be more heavily weighted towards the first half of the year. We have very attractive market conditions. And there's, I would say, a relatively strong start to the year as well. And that's also in line with what we've been hearing from the banks, who we've been talking to, who think that the issuance, again, it will be a little bit front-loaded in the first half of the year.

To give you a sense, that's probably, mid-50s percent of total issuance is going to be in the first half of the year, at least that's what we're modeling. That was pretty consistent with '23 and '24. '25 was a little more back-end loaded, I think, as you know. And that's also a pretty consistent pattern that we see with frequent issuers. So to put a finer point on it, Manav, we're expecting issuance to grow in the first half of '26 in the kind of high single-digit range versus the first half of last year and to decline mid-single digit in the second half. And in the first quarter, in particular, we think we're going to see kind of high 20s percent of issuance in terms of -- as a percent of the full year.

Now when we go to revenue, it's a little less pronounced in terms of the being front-end loaded. So I would say from a revenue perspective, we expect it to be somewhere in the low to mid-50s percent of revenue in the first half of the year. I think importantly, we do expect revenue growth in each quarter of the year. We think that we're going to be somewhere in the mid-teens for revenue growth in the first half of the year and somewhere in kind of the low single-digit range for the second half of the year. And for the first quarter, probably somewhere in the mid-20s percent.

Our next question comes from Toni Kaplan with Morgan Stanley.

I've been getting an increasing number of questions recently around how much of your data is proprietary, the sources of your data, and which parts and how much of MA is based on proprietary data. I was just hoping that you could dimensionalize this in a way that you think is most helpful for investors.

Yes. Toni, rather than me sitting here and trying to convince you of some statistic. Let me help you think about it in slightly a different way. And this is about why we think we are well positioned in an AI world. And first, as you said, like we all understand we have a massive proprietary data estate. And you heard me talk about we're in the process of unifying all of that, all the data, the models, the ratings, the research, the risk assessments into really a single normalized record for each entity. And that is going to be able to give us the ability to create a very, very powerful knowledge graph, right? And then we're going to keep adding to that. And that is going to enable the agents to be able to access a comprehensive interconnected view of any entity. And as I said, give unique insights and allow for richer decision-making.

But the second thing, I think this is important is we're assembling all of that into what we call -- and you might have heard me use this term a trusted context layer. So that context layer sits between the raw data assets and the reasoning engines. So it makes the data usable for reasoning. And what that is, is a structured governed representation of what the data means how it relates across entities and time and scenarios, when and why the data should be applied and much, much more, right? [ Is it ] a deep contextual understanding of the data.

Orbis, obviously, a very important part of this massive data state is a great example. It's not just company data. It's years of entity resolution, ownership mapping, expert judgment and of course, a complex ecosystem of licenses and IP rights. And we've built all of that context directly into our analytics, our methodologies and our models so that then the outputs are accurate, they're explainable and they're defensible. And as you've heard me say, and I love this term, they're decision grade. So hopefully, that gives you a sense. It's all of that together that makes our data, I think, uniquely valuable.

Our next question comes from Ashish Sabadra with RBC.

I wanted to ask a follow-up question on AI. Thanks for highlighting the AI resilience and strong demand for the agentic solution. One of the investor concerns lately have focused on the adoption of white coding and verticalized LLM offerings such as Claude for Financial Services and those potentially impacting vertical software or workflow solution. Can you talk about the moat around the software or vertical solutions within MA?

Yes, Ashish. Great to have you on the call. Again, I think the way to think about this, and it's interesting if you think about -- you heard me talk about CreditLens and our lending solution, and that has an AI-enabled layer to all of it from the ingestion of financials to credit decisioning and covenant monitoring and much more. You've got different adoption curves with different customer segments.

So you heard me say at the high end, almost all of the banks, the big Tier 1 sophisticated banks want to be able to consume our content in a variety of different ways, and it's typically not through software, right? But what they want is we had a bank that's working on agentic. I mentioned it in my remarks. They're building an agenetic workflow for lending. So while they don't need to adopt CreditLens, what they do want is they want our specialized agents around credit memo generation and early warning that are populated with all of our data. and access to our model. So they're consuming it through either through smart APIs and MCPs or specialized agents that are going right into the workflow that they're building.

So for me, again, it comes back -- we talk about we're going to be wherever our customers want us to be. If you are a Tier 3 bank and you want a lending software platform that's enabled with AI and has access to a lot of our -- we're going to sell that to you. If you want our content through, as I said, different ways to consume the data or specialized agents, we'll do that. If you want to consume it in a enterprise software system, we'll do that.

So in a way, Ashish, I'm actually less worried about it because at the end of the day, and we've always talked about this. The software that we have built is simply a delivery chassis for the content. It's not just some business logic that we've sold to a customer. It's a delivery channel for the content. We'll deliver it through software. We'll deliver it into your AI platform. It doesn't matter.

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

I have a simple one. I just wanted to know how much revenue these 2 MA divestitures affect the MA revenue guide for '26. And then let me just add on to that. I also want to understand how they affect the MA ARR figure, are divestitures included or excluded when you report MA's ARR.

Yes, Andrew. So let me start with the first part of your question in terms of how those affect our guide. Learning Solution was actually divested in December. So obviously, for 2025, there's a very immaterial impact. In terms of our outlook, we expect about 1 percentage point of headwind to the MCO revenue growth, and that's reflected in our reported in our outlook for total revenue. We expect a little under 2 percentage point headwind to the revenue growth -- sorry, 1 percentage point headwind to MCO revenue growth and 2% headwind to MA revenue growth, which is embedded in our guide. And there's -- most of it is onetime. That's about 90%.

Going forward, it should modestly improve the total revenue growth on a pro forma basis that the training revenue was a slower flattish growth. And when it rolls off, that should improve the profile going forward. This is broadly neutral to MA, about 30 basis points MA margin dilution and very minimum for the MCO adjusted operating margin guide.

Now for the regulatory business, this is not yet reflected in our guide. We expect the transition to close around midyear of 2026. We'll update our guidance to reflect that impact at the time. Just to give you a sense of the impact when it closes, we expect about 2 percentage points of headwind to MA reported revenue growth, and that's mostly recurring. We expect 100 basis points tailwind of MCO adjusted expense growth and about 10 basis points dilution on MCO margin. This will also have a minor $0.05 to $0.10 adjusted EPS impact. It depends on when the timing of the transaction closes as we anticipate to redeploy some of the sales proceeds to additional share buybacks.

Just on your last question about ARR and constant currency organic recurring revenue. This is what ARR is adjusted to eliminate the effects of divestitures and acquisitions, and we expect both of those to grow high single digit in 2026.

Our next question comes from Owen Lau with Clear Street.

I want to go back to your MIS margin guide, which is better than expected. And I think it's even higher than your medium-term guidance, which is around low 60%. Could you please talk about the driver of the strength? And how should we think about your medium-term guide from here?

Yes. So we're guiding adjusted operating margins for Moody's Ratings of about 65%. I think those 2 components, obviously, revenue and transaction revenue growth. But we've also made significant investments, if you recall, over the past couple of years or 3, 4 years on technology enablement. And around our data, and Rob talked a lot about the value of the ratings data feeds and all the data that our analysts produce, all the insights. So we've done a lot of work around that.

We've also equipped our ratings analysts with pockets of automation tools to be more efficient and spend more time on actually -- on ratings committee, spending time with issuers and less so on more administrative tasks. And that's really driving increased operating leverage. We're still investing in the ratings while at the same time, improving and getting those margins level. We're investing in analytical staff to support, obviously, the volume but also areas like private credit. We are looking to also on our commercial efforts as well as methodology groups and technology more broadly. So we're still investing in Moody's Ratings and at the same time, expanding margin through those investments in technology.

Our next question comes from Craig Huber with Huber Research Partners.

Rob, I thought you did a really good job talking about your AI moats that you have. But just a little further on that. Within Moody's Analytics, there's obviously concern out there with investors, [ again, seeing your ] stock price and your peers as well, that AI firms or firms that pop up or exist that have AI tools over time could replicate what you guys do when parts of your MA operation. Can you just talk a little bit further about the moats or where do you think -- just to talk on the other side of this, where do you think maybe you are vulnerable to a third-party AI initiative that takes some share away from there on a meaningful basis.

And then on the second way to look at this is there's a lot of concern out there, people talking about that AI is going to ravage the white collar workforces out there in the U.S., around the world. Talk to us, if you would, about MA, how you price your product here. It's not really on a per seat basis, but if white collar headcount out there goes down 25% plus, just say, hypothetically, at a lot of your institutions, how will that impact how you get paid, how much you get paid when contracts come up for renewal, not existing contracts, but when they come up for renewal, how may that impact your discussions there.

Yes, Craig, some good stuff there. Thanks for the questions. Let me just talk a little bit -- I'm going to go back to Orbis for a moment because it's one of our biggest parts of our data estate. And we get questions about this. And I would say a few things in terms of that -- make it very hard to replicate that I do not think are understood.

First of all, a lot of the data just simply isn't available to the public. We have a complex ecosystem of commercial agreements and IP rights. I mean that has taken us decades to build and we're constantly curating that. Second, there's legal and regulatory issues, privacy laws and export controls and all sorts of things that our customers need to know that we're abiding by, right, if they're going to use the data. There's semantic complexity. This gets into things in different jurisdictions mean different things. And models have a lot of challenges with semantic drift. So that's where we've been curating all this and our local experts over decades, understand what different things mean in different locations. And then they're cleansing and normalizing that data to make it valuable.

There's entity resolution and ownership inference. And by the way, the models are not simply doing entity resolution. That is a really important thing to be able to resolve against the right entity. And we've combined probabilistic models, human-in-the-loop validation and proprietary logic, and we've been doing this over years and years and years. And then we've got all this historical depth, right? So we have a lot of historical depth and in some cases, the data has either been archived or it doesn't exist in digital forms. It's not easy to get some of that history.

And then finally, governance. And I got to tell you, Craig, every bank I talk to tells me good enough is not good enough for our institution. What they want from us, they want to move, in many cases, to fewer trusted providers. So they want us to be able to meet their needs. And look, I'll acknowledge, Craig, that things like automated data ingestion and things like that will be done by AI. But it's those things that I talked about. And it's not just Orbis. You could go across a number of other data sets that we have, and the same is true. So hopefully, that gives you a sense.

Now let me talk about how do we price the product. And we've never had seat-based licenses. That's not the way we've operated. We've always tried to kind of think about value in our pricing schedules. But look, we are starting to trial in parts of the business, different pricing models, right? And thinking about elements, bringing in elements of consumption-based pricing that I think will be more closely aligned to outcomes, right? Because at the end of the day, Craig, what you're talking about, if there is a substantial labor replacement, somebody, and some companies are going to capture some of that opportunity. Maybe not all of it, but they're going to capture, right? And that is going to be, in my opinion, a combination of the model providers and the data providers who are making that efficiency possible. And so we are going -- we are thinking -- as we speak, and trialing different pricing models to be able to capture some of that, frankly, some of that upside.

That concludes our question-and-answer session. I will now turn the call back over to Rob for closing remarks.

Hey, thanks, everybody, for joining today. And for my colleagues at Moody's, let's go. Talk to you next time. Bye.

This concludes Moody's Corporation Fourth Quarter and Full Year 2025 Earnings Call. As a reminder, Immediately following this call, the company will post the MIS revenue breakdown under the Investor Resources section of the Moody's IR homepage. Additionally, a replay will be made available after the call on the Moody's IR website. Thank you.

Hi, everybody. I'm Andrew Steinerman. Welcome to the info services track of the Ultimate Services Investor Conference. If you get a chance, pull up an information services data book, which is our quarterly claimer on the sector since 2013. This is Rob Fauber, the CEO of Moody's. We appreciate you coming back every year.

Thanks for having me.

It's always a really good discussion. And don't worry, everybody, we will get to discussions about AI. I just thought we'd ask some questions beforehand.

So when you look at just this year in terms of issuance and ratings revenues, your expectations were more modest at the beginning of the year and have been more robust as the year has gone forward. What's driven that kind of upside to issuance relative to initial expectations just this year?

We adjusted downward after liberation days, as you remember, and then we've come back since then. I would say that -- a few things. We, originally, at the beginning of the year, had a view about kind of M&A in the Trump administration. I think there's a little bit of a fall start again with Liberation Day. But as we've seen in the second half of the year, M&A has really picked up and a lot of strategic M&A. And we're also looking at sponsor-backed M&A because there's a real flywheel effect that goes on in our business when we see sponsor-backed M&A. But you've got M&A volumes picking up. You've got economic growth that, while has slowed a bit, not as much as people thought. So it's actually been better than market had thought. You've got default rates, which are slightly above long-term averages, but have generally been coming down, maybe a little slower than we thought, but spreads are really tight. They're at near multiyear lows. And all of that's pretty conducive for issuance. And so the strongest issuance that we've seen this year has been in the corporate segment, both opportunistic investment grade, we see a lot of big infrastructure financing getting done, some of that getting done through corporates, and then leverage finance, both high yield and leveraged loans.

And when you say M&A, usually the ratings and the issuance happens closer to the close, right? So like M&A announcements this year should even help issuance even more so next year, right?

Yes. That's right. As we look into next year, we have a service called Rating Assessment Service. So we have companies that come to us, and we'll understand what their rating profile may be in an M&A transaction. That pipeline is very strong at the moment. That's the same thing that we're hearing from bankers that the M&A pipelines look quite good. And now as we're going to round into -- from Thanksgiving and into the end of the year, some of that deal flow is actually going to get -- also get announced in the beginning of the year, and as you say, then get financed subsequent to that.

Okay. Talk about the 4 deep currents. These are something you've been talking about for a while. Are they coming to fruition in terms of revenue growth the way you would expect them?

Yes. So it's interesting. During COVID, or right after COVID, and we were a beneficiary of COVID. We were a COVID stock, right, with ultra-low interest rates. There was a lot of fretting from investors who said, "Oh, my gosh, interest rates aren't close to 0. It's going to be terrible for your business." Obviously, there was an adjustment period in 2022. We ripped the band-aid off and rates moved up. But I would argue that we're in a much better environment for debt issuance over the medium term than we were then, right? Then it was a monetary bubble. And now we look at what is going to drive financing volumes. The first one is there's just a massive amount of debt that's been issued over the last 5 years. And that debt has got to get refinanced. We've published these. We call them our refinancing walls. Those look quite good, especially for speculative grade debt. So that kind of underpins issuance. And then the deep currents that we talk about, private credit and banks coming off -- assets coming off of bank balance sheets and going into investor markets, capital markets, that's securitization. That's a positive for us because we're providing credit assessment in many cases.

The -- both infrastructure -- I've seen a BlackRock report that says something like $68 billion of infrastructure financing needed by 2040. But of course, AI, it's all in the news, these massive AI data center and infrastructure investments also driving that, and we're seeing that.

And then I'd say in the earlier days. So that's rolling through the ratings business now, Andrew. And then I would say earlier in its maturity is digital finance. We do feel that, that is an inexorable trend and transition finance. I think maybe a little bit of that slowed down a little bit, but when you look at companies that are going to be decarbonizing and evolving their business models, they're still -- and what we're going to do with energy grids and all of that, there's still a lot of financing that's going to get done for transition finance. So that's still out in front of us.

Okay. That's great. Okay. Well, so when you look at the categories, you just mentioned a moment ago that spec-grade looks good. But when I look over the Moody's categories of issuance projections, both structured finance and the public category was actually tapered in terms of MIS rating issuance outlook. Why is that? And is this an important thing to watch? Obviously, leveraged loans and high-yield bonds are more important. But should I be watching these other tails?

Look, there are always ebbs and flows within the different asset classes. That's one of the great things about the business is sometimes when we see -- we'll see issuance slowdown in 1 area and we'll see it pickup in another, whether it's a region or an asset class. In this case, Andrew, you're right, corporate has been very strong for the reasons I talked about. In a couple place -- parts of structured finance, primarily around consumer finance, we have seen a little bit slower growth than we had thought in the beginning of the year. That's not particularly surprising because I think there are elements of a 2-speed economy in the United States. There's the AI economy and then there is kind of everybody else, and we've seen a little bit of stress in fact as we move down the socioeconomic spectrum, right, with subprime autos and undocumented populations.

And so you see a little bit of that in the -- in parts of our structured business. As it relates to project and infrastructure finance, it's an interesting question, right, "Hey, if there's all this infrastructure funding, why did you, again, modestly trim our outlook for the year?" But yes, all -- that stuff is -- it's interesting. Just take data centers for a moment. They're coming to us through all of the different lines of business within ratings. So you've got data center financing that's getting done in our corporate rating segment. I'd call that infrastructure, but that's in corporate. We see it in CMBS. We see it in REITs.

So it's rolling through different parts of the rating business. So there's a little bit of a, I'd say, a quarterly downtick just in that particular line. But infrastructure is much broader than that across our rating lines.

Okay. That's fine. When looking at the MA organic revenue growth targets, the medium-term targets that you set earlier high single digits to low double digits, you kind of left that kind of low double digits there as kind of an ambition. What would it take to get there? Like is that really a stretch? Or is that kind of a key part of the range?

So we're not bringing forward any of our guidance estimates today. That's still the -- certainly the medium-term targets in this particular case. I'd say a couple of things. One, this year, we've talked a little bit about a few of the, I have to be careful about this, the idiosyncratic things that we've experienced in terms of whether it was canceling a distribution agreement, whether it was [ Doge ], a little bit of the ESG runoff from when we did the MSCI partnership. I only caution that because I -- every -- we're in a very dynamic world, and there're always things that are happening, but those things did provide a headwind to growth. We had a little bit higher attrition in those particular areas for those reasons.

And I would just go back to kind of what is it going to take? It's a -- in particular, we're going to be investing where we see where we have the strongest right to win and the strongest growth tailwinds. And those are going to be in our banking segment. It's around lending. Right now, we feel very good about our lending suite. In fact, that's growing faster than the rest of Moody's Analytics. Underwriting, and particularly building out an insurance and expanding from property into casualty and financial lines and that's another opportunity for us, cyber. KYC continues to be an important opportunity. Certainly now with AI, there's a really interesting opportunity between our data and agents and thinking about providing huge amounts of value to our customers that have very manual, people-based workflows.

And then the last thing I'd say, Andrew, is kind of an agentic layer over top of our content estate. In general, I think of AI as a great opportunity for us. It must be a tremendous unlock when you have a massive mostly proprietary data and analytics estate. And I think this offers us at this moment in time so many more ways and channels for us to monetize that content.

Okay. Maybe we should jump into AI since it just seems like the conversation is naturally migrating that way. I have this figure that I put together, really was kind of worked from the research we did over the summer of who's most at risk, who's least at risk. The rating agencies are actually, in our opinion, kind of least at risk, but just -- let's just start out with a big picture question about info services. There's been a sell off broadly of info services stocks. It's not just Verisk and Moody's, it's everybody. We've sold off and there's a worry about AI. And of course, I've come to the conclusion there is companies more at risk and least at risk. Just start with the big picture point, do you think this is a group, the whole group that's going to net benefit from AI on average, or be dislocated by AI, the whole group?

So take it with a grain of salt to who it's coming from, right?

I know.

I firmly believe that this must -- for the reason I just touched on, this has got to be a big opportunity for the owners of, I'm going to say, proprietary or heavily derived data and analytics. And I'm happy to kind of dig into that, but...

Please do.

Okay. So why is that? And we've talked about this a lot today. First of all, I think there are many more opportunities for us to monetize that content across new customer segments, new customer personas and new use cases. And in some ways, I think about a utility curve of our content, I'm going to give an example of our catastrophe models, okay? So we have these really sophisticated catastrophe models that the insurance industry uses to assess risk of extreme events. We've done an amazing job of monetizing those models at the very high end of the utility curve with catastrophe modelers through our catastrophe modeling software. But guess what, that IP is very, very valuable to personas and customers well beyond insurance companies.

So you're a bank and you want to understand the risk of a piece of real estate that you're taking as collateral, we have an opportunity to leverage that IP and to be able to provide that to a bank during their lending process. I can embed that into my software, I can pull that into an agent. So in general, I just look at this and think, gosh, there's so many more ways to access our content and for me to think about who I'm serving, what use cases and how I price along that utility curve, many ways, I think I'm just getting started.

And then the other thing I would say to this is, and this might sound a little trite, but more and more -- we know there's enormous value to the data, right? All of a sudden, we've -- not all of a sudden. We know that our data is valuable in supply chain and supplier risk, for example, right? So now I've got -- I know that I want to have my data and my content and my models where our customers are making decisions, whether that's in SAP or Salesforce or Coupa, any of those third-party platforms, whether it's in a bank's internal AI workflow orchestration layer, take my content with AI rights to it, take my specialized agent, or whether it's in our software and our web platforms with an AI interface or agentic layer over top. I don't care. There's many more ways for me to monetize that content for broader uses and also thinking about, over time, different commercial models for that content.

And if a financial customer discovered Moody's data on a third-party LLM and wanted to subscribe to the data, would you charge them the same as an existing customer? They might not have the broad use cases that existing customer has.

I mean it really depends. We're going to have a variety of different pricing models. I'll tell you, so you -- in that case, I think you're talking about a situational access to our content. So what I'd like to do is I think of that example, Andrew, is somewhere lower on this utility curve, right? So there, I've got to have the capability to be able to do essentially digital fulfillment, right, and enablement for that content at that moment of time. Historically, our company and many companies like us, we have products and we have field sales, right? And so what would happen in that particular scenario is, in theory, up to now, it would kick off -- you have to call a salesperson. That's not a scalable model. So we've built a platform layer underneath of all of our application estate, starting with single sign-on and moving to metering and fulfillment to be able to understand what are our customers doing across our applications, and how can we then start to think about a digital fulfillment model that will allow us to sell the content and monetize somewhere different on that utility curve.

The one other thing I'd say about, you gave a bank example. Our content with the big banks is being consumed all over these institutions in different departments in different parts of the world. We'll have many different contracts. There's a really interesting opportunity at this moment to up level the way that our content is consumed at these institutions. In many cases, like at JPMorgan and others, they're building out these AI workflow orchestration platforms. They might be at the enterprise level or more likely at the corporate and investment bank level, the commercial bank, and to have us be able to get core parts of our risk operating system, as I like to call it, make that available to the AI and then be able to have that content consumed much more broadly across the institution to serve many more use cases and then I'm going to price behind that.

Right. I just want to make sure that Moody's is going to lose its pricing power as it does more digital fulfillment for new customers.

Yes. Again, when you're talking about pricing power, we're going to price for the utility and the use case. I think that's going to be very important.

So you saw my risk continuum a little bit here. And I put the ratings as rating agencies least at risk. If you were going to talk about MA, where on the risk continuum for AI do you feel like MA is? And I know, obviously, MA is a mix of businesses.

It is. And if you think about our content estate, the largest part of the content in Moody's Analytics is the exhaust from the rating agency. It's the research and the data. It's all proprietary. We're creating it. On average, we're issuing a rating every 20 minutes, 24 hours a day, 7 days a week. It's all proprietary. You can only get it from Moody's.

We then have built out a -- what I think of as one of the world's -- I think it's the world's best commercial credit franchise. So we have credit models and we have a giant contributory proprietary credit default database contributed by banks that helps us to calibrate models for public companies and private companies. And then we've gone all the way down to credit workflow, right? We have loan origination, a lending suite. We have asset liability management software, portfolio analytics, all because we have such deep domain expertise and proprietary content in credit, right? So that anchors our research business, for the most part, anchors a lot of the banking business.

I'm now going to move to insurance, and I get asked questions about, well, you sell software. Our software -- we're only in the software business as a delivery chassis for the content. Yes, we have something called the Intelligent Risk Platform, which has I think industrial strength cloud compute to run models for the insurance industry, but really what the insurance industry is buying are the cat models. And I got asked earlier about, well, could AI just recreate the cat models? It's much more than that. Our cat models, first of all, are the currency of risk across the global insurance industry. It's how they manage and price risk. And our cat models are then calibrated with claims data from the insurers. The insurers want and need these models to be accurate. So they work with us to help us with the calibration of the models. An interesting example, the insurance industry wants to grow cyber insurance underwriting. So we work together with the industry, biggest broker, biggest reinsurer, biggest insurers of cyber to form a cyber industry working group where they contribute claims data and content to us to help build models and solutions for the industry to help the industry grow and write more cyber policies.

So that's how to maybe think about insurance. And the last part because I get asked this question a lot, and I think this is important, is around our massive company database, right? And this powers a whole range of use cases across banks and insurers and corporations. So we have the world's largest database on companies, 600 million, 2 billion ownership links. We have really rich data on politically exposed people and adverse news and all of that, we link it all together. The biggest use case for that is KYC. But that is assembled through a relatively complex ecosystem of information providers. So we have to have the rights to use the content. We have commercial arrangements with them. We then normalize and cleanse the data and make the data available. So it's not as easy as you can just go out and scrape all this data. Is there data available on private companies that can be scraped? Yes, there is, but not what we're doing through these company bureaus where we curate an ecosystem of information providers where we have the rights to use the data.

You're not going to believe that I don't know the answer to this question. My question is, you already have an incredible database of private companies in your credit research, like could you combine your BvD database with your credit research database? Or do you have to keep those separate?

So if you were to go on to moodys.com today, you can type in any company that you want. And Andrew, you're going to find rich information on companies, whether it's public or private. You may find model-derived ratings on private companies, right, where we're leveraging our credit models, where we have financial statements on private companies, and we say that the financial profile of this private company not rated is a BA1 model implied, right? And guess what, that gives us -- that's also what we're bringing to the private credit opportunity.

If I could just touch on that for just a second. Private credit is a super interesting opportunity when you have arguably the world's best commercial credit scoring franchise, right? It starts with ratings on public companies, but we have the ability to put a model-derived score with high fidelity and high confidence on virtually any company on the planet. Now as it goes to smaller and smaller and less information, the range of confidence around that is wider, but, gosh, you want to have -- understand the credit profile of a private company, we can do that. And we've been doing it.

I think what our answer was, if it's model-derived ratings, yes, we can combine it with our other database. But if it's a ratings that is by an issuer, you can't combine it?

The one thing we're going to do is make sure that if you're using our rating, you will know if it came from the rating agency or it was model derived.

That's a fact.

Other than that, it's all going to be available to the same investor group because, guess what, our investors tell us all the time, "Hey, look, in my portfolio, I've got 90% public and 10% private. I need to help on the private." We now -- we offer that. So what do we do? When we layered in all of those hundreds of thousands of private companies, we went back to our CreditView customers and said, "Hey, are you interested in the private company package, right?" There's an upsell.

Just to make sure I got the question right. There are some pieces that you can't combine together, right?

We're not sharing information that we get from the rating agency with any other part of the institution. Yes.

Okay great. Let's open it up for questions for Rob.

Maybe if you could expand on that MSCI partnership. I guess where is that market at in terms of is this being demanded by kind of the investor groups and the LPs? Or is this something that build it and they will come? And maybe if you could just also expand on what exactly you guys are doing together as well?

Yes. So it was interesting. I was on the road for most of the last 2 months. And at the beginning of that trip, when I would sit down with various folks in the investment community, and I was -- I spent most of the time outside the United States, and I would ask questions about how are you understanding the risk of your investments in private credit? It was interesting. And I would get, well, it's a higher-yielding asset class, lower defaults. That's interesting. But towards the end of that trip, I had a very different -- started to have a very different level of interest and engagement. Why are you asking? Tell me more. Yes, I've been wondering more about the credit quality of my private credit funds.

And so what we did with MSCI, they had a data set. It's hard to get access to information on these companies. We have the credit models and they had some data. And so we went together to their customers that are on their -- one of their GPLP platforms and said, "Hey, if we could provide you a Moody's modeled credit rating," so we take a probability of default and map it to a rating, "Would you be interested in understanding what the credit profile is of your investments in your private credit funds? Would that be interesting to you?" And in many cases, we had very good feedback and investors said, "Yes, well, it would be interesting." So we had to think about how much are they going to pay and what's that going to look like and all of that.

And so it's not going to be a game changer from a financial standpoint, right? What's really interesting, I think, is that we're introducing the language of credit ratings and credit risk to these investors to help them have a third-party rigorous independent understanding of what the credit risk is in the funds they're invested in, and to allow them to have a dialogue then with the GPs who are -- today, how do they understand the credit risk? It's informed by the GP, right? They've -- they're telling the investors what the level of credit risk is.

So if you think about the way we built this business over decades, it was by building investor demand. The investors found the ratings useful. And so once again, what I want to do is have the investor community in private credit start to use our ratings to say, "Hey, I need to know more. I want to ask why you guys have marked it like this and why Moody's is market like this? Help me understand this." And over time, you could imagine more and more of the GPs -- because this is really about direct lending, right? More and more of the GP saying, look, rather than having Moody's effectively providing a model-based score on our funds, why don't I just go to Moody's and have them provide an assessment with my engagement, whether I'm APOLLO, Blackstone, whoever it is, right?

That's the way our business works is we have issuers come to us. And so we look at this and think we have a very important role to play in the private credit market just like we did in the public credit markets. We created the language of credit risk and then we developed the scorecards and the data and the benchmarks and the research to help investors understand risk and scale the market. And that's what private credit. When I talk to all of the big GPs, say, look, if you're going to go from $2 trillion to $10 trillion, you're going to need this, and we can play a very important role here.

Let me ask you a question about clients that you have that are very AI forward. Do you find that they consume more data and content from Moody's? And I also -- sort of an add-on question, are these forward-looking, forward-leaning AI clients more in the regulated industries? Like is that who's moving quickly? Or are they moving in a more measured way?

So the first part, we gave some interesting data about looking at the cohort of customers who take some form of AI solution from us from those who don't. And this was back a quarter or so ago. And we talked about, it was like almost twice the growth rate of that cohort, meaning we're varying -- think of them as maybe early adopters. So we have a different engagement model with the early adopters. So to your point, Andrew, yes, they're actually taking more things from us. We're engaging with them differently at different parts of the institution. That's what's particularly exciting. The second part of your question was around...

Regulated versus non-regulated...

Regulated. So it's interesting because it took the banks a while, right? They had to get through the risk governance and all that stuff. Every single big bank that we're talking to, we're actively engaged with them. It's -- and it's actually when we look at the growth of the tiers of our bank customers at the moment, the fastest growth is coming from the largest banks, where we have -- where that engagement is really about the content and pulling the content into their environment.

And ultimately, they're trying to measure risk better, right?

That's right.

Okay. Last questions for Rob. Go ahead.

I don't want to read too much into the answer to the question about MSCI, but just curious, you mentioned this inflection point while you were on the road where you were seeing more interest. Is that just an organic conversation that evolved between LPs and GPs? Or is there potentially some sense that these actors are concerned about greater scrutiny post first brands and if there's not some type of self-regulation?

Yes. And I'm specifically referring here to investors, right? So investors who are just saying, Hey, look, I've -- and it may be insurance companies. I've invested a lot in private credit. I'm watching what's going on in the market. And by the way, I, the investor, am now getting questions about the investments I've made in private credit, and how do I understand the credit profile of what I've invested in. And that's a place where Moody's has a great opportunity to help those investors by saying, "Hey, we can give you a third-party independent battle-tested view of credit risk. We've been doing it for 115 years." And so I just -- I mentioned that there's more in the news. There's more interest from investors because of what's going on in the news and the awareness now of -- we're not -- maybe the market felt frothier over the summer and now it feels like I think people are starting to focus more on credit risk, that's always good for our business.

Okay. Rob, I think that's the time for us.

Sounds like it.

Thank you very much.

Thank you.

Good day, everyone, and welcome to the Moody's Corporation Third Quarter 2025 Earnings Call. At this time, I would like to inform you that this conference is being recorded. [Operator Instructions]

I will now turn the call over to Shivani Kak, Head of Investor Relations. Please go ahead.

Thank you. Good morning, and thank you for joining us today. I'm Shivani Kak, Head of Investor Relations. This morning, Moody's released its results for the third quarter of 2025 and updated guidance for select metrics. The earnings press release and the presentation to accompany this teleconference are both available on our website at ir.moodys.com.

During this call, we will also be presenting non-GAAP or adjusted figures. Please refer to the tables at the end of our earnings press release filed this morning for reconciliation between all adjusted measures referenced during this call in U.S. GAAP. I call your attention to the safe harbor language, which can be found towards the end of our earnings release.

Today's remarks may contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. In accordance with the act, I also direct your attention to the Management's Discussion and Analysis section and the risk factors discussed in our annual report on Form 10-K for the year ended December 31, 2024, and in other SEC filings made by the company, which are available on our website and on the SEC's website. These, together with the safe harbor statement, set forth important factors that could cause actual results to differ materially from those contained in any such forward-looking statements.

I would also like to point out that members of the media may be on the call this morning in a listen-only mode. Rob, over to you.

Thanks, Shivani, and thanks, everybody, for joining today's call. This morning, I'm going to start with the highlights from Moody's strong third quarter results, and I'm going to provide some insights from our latest refunding [ well ] studies as well as some examples of how we're winning and the deep currents that we're operating in. But let me give you the punchline.

We delivered record quarterly revenue. We're raising our full year guidance across almost all metrics, and we continue to drive significant innovation throughout the firm all at the same time. Now following our prepared remarks, Noemie and I, as always, we'll be glad to take your questions. So with that, let's get to the results.

We finished the third quarter on a high note. Markets closed with the busiest September on record and Moody's notched a new record of our own. We exceeded $2 billion in quarterly revenue for the first time ever in our history, and that was up 11% from the third quarter of last year. Moody's adjusted operating margin was almost 53% in the third quarter, up over 500 basis points from a year ago, demonstrating the tremendous operating leverage that we've created in our business. We delivered adjusted diluted EPS of $3.92 in the third quarter. That was up 22% from last year, and that's particularly impressive given the tough comp in the third quarter of 2024, when we posted 32% year-over-year growth, on top of the 31% growth in the third quarter of 2023. And just to put this in perspective, we've more than doubled adjusted diluted EPS from the same quarter just 3 years ago, consistently strengthening the earnings power of the firm year after year after year. And all of this, while investing to harness the immense opportunities and the deep currents that we've talked about over the past several years.

Now on to the highlights for our Ratings business. MIS delivered 12% revenue growth for the quarter and surpassed $1 billion of quarterly revenue for the third consecutive quarter, setting an all-time record. Our position as the agency of choice enabled us to capitalize on a healthy issuance environment and record tight spreads. And the strategic investments we've made in technology, analytical tools and talent are equipping us to meet surges in issuance volume and capital markets innovation.

Now looking forward, the issuance pipeline is robust. Demand is solid, with spreads hovering around near record lows, and the refi walls continue to build. Additionally, demand for debt financing remains strong in areas that we've consistently spotlighted over the past year or 2. That includes private credit, AI-powered data center expansion, infrastructure development and transition finance. And you can see this coming through in some of the marquee deals that we rated in the quarter.

First, we were the sole rating agency on the first of its kind emerging market CLO in APAC for the International Finance Corporation, which is a member of the World Bank Group. That was a very innovative financing vehicle for frontier markets. Second, our corporate ABS team rated a more than $1 billion data center securitization, also the first transaction of its kind, which is backed by 3 high-quality newly constructed data centers and their related leases. And third, we rated the largest Asian corporate bond ever issued at almost $18 billion with much of the proceeds being used for data center investment. And all of these are notable examples of deep currents driving demand for debt financing.

And while those deep currents are driving new issuance, refunding needs continue to grow as well. Our most recently published refunding study shows that refunding needs over the next 4 years are projected to surpass $5 trillion. That represents a compound annual growth rate of 10% from 2018 to 2025. That number is approximately double the dollar volume seen in 2018 and this gives us some real confidence in the medium-term growth trajectory for MIS.

Now there's typically a lot of interest in these reports on this call. So let me just share a few key findings with you. First, nonfinancial corporate refinancing walls in both the U.S. and EMEA grew [ 6% ] over the upcoming 4-year maturity horizon. Overall, investment-grade maturities are up 5%, while spec-grade maturities are up 7%. And notably, within spec-grade, U.S. bond maturities have increased by more than 20%. And in EMEA, spec-grade bonds and loans each rose by approximately 20%. And all of this points to a favorable backdrop for future issuance and the mix is especially encouraging given that spec-grade issuance tends to be more accretive to our revenue profile. So for those of you interested in exploring the full reports they are available on moody's.com, or through our Investor Relations team.

Now Beyond the refunding walls, we remain well positioned to meet the evolving market needs in private credit. And that's a theme that we've consistently highlighted on prior calls. Private credit continues to be a growth driver for Ratings. In the third quarter, the number of private credit-related deals grew almost 70%. Notably, Direct lending remains the smallest portion of our private credit related activity, while fund finance and securitization are leading the way in both deal counts and issuance volumes. Revenue tied to private credit grew over 60% in the third quarter across multiple MIS business lines, albeit off a relatively small but expanding base.

We're also seeing a growing number of private deals returning to the public debt markets for refinancing. And according to Bloomberg's [indiscernible] Insights, issuers are realizing material savings. On average, something like 200 basis points, but in some cases, as much as 400 basis points when compared to private market rates. And as I've mentioned before, this dynamic effectively acts as a deferred maturity wall as we see unrated private direct lending deals refi into the rated [ BSL ] market. And as this market continues to grow, we continue to invest in experienced analytical teams and methodological rigor to ensure Ratings quality.

Now turning to Moody's Analytics. We delivered strong results again this quarter. Revenue growth was 9% year-over-year, including 11% Decision Solutions. ARR is now nearly $3.4 billion, that's up 8% versus last year. And we're delivering margin improvement ahead of our plans just earlier this year. Our cross MA initiatives are yielding results, delivering a 34.3% adjusted operating margin, up 400 basis points versus last year. And as a result, we're increasing our full year margin outlook for MA to approximately 33%, and we believe this puts us solidly on track to meet our medium-term margin commitments.

Now we're continuing to invest in scalable solutions across high-growth end markets, while at the same time, simplifying the product suite and optimizing our organizational structure. So one example of that simplification. In the third quarter, we entered into a definitive agreement to sell our Learning Solutions business to Fitch. We had a good run with our Learning business, but we felt it no longer fit the profile of where we're seeking to invest in scalable recurring revenue businesses.

In parallel with these portfolio simplification efforts, we remain very focused on the deep current driving demand for our Analytics offerings. And in M&A, that includes an increasing focus on physical climate risk, and enhancing and expanding our solutions to help customers embed AI more deeply into their workflows. On a recent trip to Asia, where we celebrated 40 years of Moody's in the region, I heard firsthand about two customers. We're investing in our Physical Risk solutions to understand the impact of extreme weather events, and both of these are outside of the insurance sector.

First, one of the largest banks in Japan, and for that matter the world, is using the RMS models that are traditionally used by our property and casualty insurance customers to understand physical climate risk across lending and portfolio management. Second, we recently won a multiyear deal with an Asian regulatory agency to deliver Physical Climate Risk data to 11 banks and insurers. And this marks the first time globally that a regulator has purchased Moody's Climate Solutions on behalf of its financial sector. And this initiative enables the integration of Physical Risk Analytics into regulatory reporting, in core business functions, and also establishes a precedent for further regional adoption and collaboration.

Now on AI, you've heard me talk before about the very encouraging engagement that we have with a number of large banks who are interested in leveraging our data and models in their internal AI-enabled workflows. And while these discussions have taken time to move through bank's risk governance frameworks, we're now seeing some tangible momentum. In the third quarter, we signed over $3 million in new business with a Tier 1 U.S. bank, which included solutions to automate credit memo creation and to deploy early warning systems across its real estate portfolios. These solutions are driving meaningful efficiency gains for our customers, are [indiscernible] time to decision and delivering a competitive edge. And this is a powerful example of how Moody's is uniquely positioned to bring together proprietary data, advanced analytics, software, and now Gen AI capabilities and agents into our customers' mission-critical workflows.

Now these agentic capabilities are just one part of a broader investment strategy. One that's focused on unlocking the full potential of our data and analytics estate. And we're not only investing in how we build intelligent AI-powered workflows, but also in how we package and deliver our proprietary data and analytics, embedding that directly into our customers' internal systems and our partners' platforms.

As we've discussed on recent calls, partnerships are an important part of this strategy. And we're embedding our data into partner ecosystems, extending our reach while preserving the depth of our domain expertise. And this approach not only scales our impact. It also deepens customer integration, improves retention, and it will help to continue to drive durable growth across our portfolio.

So a prime example this quarter is our partnership with Salesforce, where we continue to see strong growth from our integrated suite of connectors that includes company phermographic data, news and other content. And this supports third-party risk management and compliance monitoring, among other functions, bringing Moody's unique data and intelligence directly into Salesforce's workflows with great success. We're now expanding our partnership to make available our proprietary Gen AI-ready data and analytics within Salesforce's Agent Force 360. And in addition, Moody's will make available on Agent Exchange, our new agentic AI sales tool, that I think I've talked about on prior earnings calls, and that elevates sales teams by automating lead prioritization and delivering predictive insights, leveraging our data. And this is one part of our broader AI strategy.

So zooming out, there are a few dimensions to that AI strategy. The first is our foundational AI agent builder platform that all of our employees can use to reimagine workflows and increase productivity. As we've highlighted before, we're delivering efficiencies in engineering and customer support and we're now setting our sights on sales, product development and a variety of corporate functions as well as ratings workflows.

The second dimension is our AI Studio Factory, which is a platform designed for agentic product development. And the third is our recently announced Agentic Solutions, enabling us to commercialize smart APIs, MCP servers and domain-specific agents that leverage our vast proprietary data and content estate and deep subject matter expertise.

So switching gears. We also continue to invest in growing our Ratings footprint in emerging markets. And this past quarter, we signed a definitive agreement to acquire a majority interest in [ Merus ], the leading ratings agency in Egypt. And this transaction will deepen Moody's presence in the Middle East and Africa, giving us a very strong first-mover advantage across all of the region's domestic debt markets. And these -- and you've heard me say this before, these are generational investments as emerging markets, including China, are expected to account for more than 60% of global GDP by 2029. And to that end, of the approximately $30 trillion of debt outstanding in those markets, only about 10% is cross-border. That means that the remaining 90% is issued locally and rated locally. And that's why these domestic market investments are so important.

So before I hand it over to Noemie for more details in the numbers, a few key takeaways. This past quarter, we delivered strong growth, significant operating leverage, and we have good momentum heading into next year. And of course, just a quick shout out to all of my teammates for the fantastic work this quarter helping deliver one of the strongest quarters in Moody's history.

Noemie, over to you.

Thanks, Rob, and hello, everyone. Q3 was outstanding. We showcased the full force of our earnings power. We are lifting both our top and bottom line guidance, and we're proving we can invest for growth and expand margins at the same time. So let's [ get right ] in.

Starting with MIS, revenue grew 12%, a very strong result, especially given the typical softness in Q3. All Ratings lines of business contributed to the growth, supported by the constructive issuance environment. The largest increase came from leverage finance activity, followed by financial institutions, driven by heightened issuance from infrequent issuers, including fund finance and BDCs. Issuance totaled nearly $1.8 billion, marking the highest third quarter on record. This reflects a combination of factors we've previously discussed, including historically tight spreads, strong investor demand, and the announced rate cut at quarter end, as well as a pickup in M&A activity.

MIS transaction revenue rose 14%, slightly trailing the 15% growth in issuance due to high volume of repricing activity this quarter. As noted before, simpler and less complex bank loan repricings typically yield lower revenue and are less favorable from a mix perspective. MIS recurring revenue increased 8% year-over-year, reflecting the impact on ongoing pricing initiatives, portfolio expansion and sustained monitoring fees. Foreign exchange contributed to a favorable 1% uplift consistent with the benefit seen in the second quarter.

Now some color on Q3 transactional revenue by asset class. Corporate finance transaction revenue increased by 13%, supported by a 29% rise in bank loan revenue, compared to 58% insurance growth. This issuance surge was largely driven by repricing activity, which were bounded following subdued levels in Q2. Spec-grade revenue rose 43% and marking the strongest quarter for rated issuance since 2021. This was fueled by a positive investor sentiment and robust market access for these issuers. Investment-grade revenue declined 17% year-over-year, reflecting a 6% drop in issuance. Despite the decline, overall activity remained solid, supported by several large M&A transactions. Notably, Q3 of last year was the second highest third quarter on record for investment grade, driven by significant deal volume in the energy, oil and gas sector, creating a bit of a challenging comp base.

In Financial Institutions, transactional revenue grew 34%, significantly above the [ 3% ] issuance growth. This was driven by the strongest volumes in a decade from frequent issuers within the banking sector. Public, Project and Infrastructure finance transactional revenue remained relatively flat, reflecting weaker activity in project finance and sovereigns. However, this was partially offset by strong performance in U.S. public finance, especially within the regional and [ muni ] space. Structured finance transaction revenue rose 10%, and supported by strong activity in CLOs, especially new deals, driven by growth in leveraged loan formation. This was complemented by improving activity in U.S. RMBS, underpinned by sustained investor demand and healthy deal flow.

As Rob mentioned, private credit continues to be an important driver of MIS revenue growth, mainly from fund finance and business development companies, or BDC activities. First-time mandates reached 200 in Q3. That's up 5% year-over-year. Growth was strong across both North America and Lat Am, putting us on track to reach [ 700 to 750 ] for the full year. This momentum was partially driven by private credit-related mandates across financial institutions, structured finance, and private investor requested ratings in PPIF. As a reminder though, with the growth in private credit, some issuance activity will not be captured in rated issuance figures reported by external data providers.

Now turning to margins. MIS delivered an adjusted operating margin of 65.2%, which is an expansion of 560 basis points year-over-year. And as a result, we are raising our full year guidance to a range of 63% to 64%.

Looking forward and as shown on this slide, we are updating our issuance outlook by asset class. Our forecast for the remainder of 2025 assume continued momentum from the third quarter, even as we approach the typical unexpected normal seasonal slowdown towards year-end. We expect issuance growth to be mid-single digit for the full year with notable updates in investment grade, leveraged loan and high-yield bond issuance bolstered by improving M&A activity. As previously noted, we expect spreads to remain near historic lows despite some modest widening.

Investor demand remained strong and size of renewed M&A momentum are emerging. And that's actually reflected in the uptick in our Rating Assessment Service, or RAS business, which often serves as a leading indicator for M&A. In fact, Q3 marked record quarterly revenue for RAS. This reinforces our expectation that M&A will be a positive contributor as we head into 2026. In the near term, we're raising our estimate of M&A issuance to a range of 15% to 20% for the full year 2025.

Now translating this to revenue, we now anticipate full year MIS revenue growth in the high single-digit range, and that's an upward revision from our previous outlook. Overall, we remain optimistic about issuance activity, but it's important to note that our guidance doesn't factor in a significant disruption like the one we've experienced earlier this year. Risks remain with ongoing tariff and trade negotiations, and the full impact of a prolonged government shutdown on market conditions is difficult to predict. That said, we believe we have accounted for the broad spectrum of the most plausible scenarios in our updated guidance.

Turning to Moody's Analytics. This business continues to deliver an impressive financial profile. 93% recurring revenue, a 93% retention rate, and consistent growth at scale. Reported revenue grew 9% year-over-year, while recurring revenue grew 11%, or 8% on an organic constant currency basis. As we've talked about a lot in recent years, we've been actively reshaping the revenue mix by downsizing low-margin services and increasingly leveraging implementation partners across regions. As a result, transactional revenue continues to decline, down 19% this quarter.

ARR growth of 8% is consistent with last quarter. You'll notice some quarter-to-quarter movement in individual line of business growth rates, often driven by large new business wins or large attrition events. Across the portfolio, though retention rates consistently hold in the low to [ mid-90% ] range, and that supports high single-digit ARR growth. Now let me double-click into each of the lines of businesses to give you a clearer view of the underlying dynamics.

First, Decision Solutions, which includes our banking, insurance and KYC, delivered double-digit ARR growth this quarter at 10%. KYC continues to be the fastest-growing part of Decision Solutions with sustained growth in the low to high teens over the last several quarters. This quarter, we reported 16% ARR growth, and I want to highlight two recent sales in the tech sector that illustrate the appetite for our KYC solutions beyond financial service customers.

First, a large technology company signed a major deal to integrate Moody's Orbis data into its denied party screening system, helping block transactions with entities in countries of concern. This deal positions Moody's as a trusted provider of critical data for regulatory compliance and showcases our ability to address complex challenges with innovative solutions.

Second, a global social media platform is using Moody's to strengthen fraud detection and business verification across its ecosystem. Our data helps uncover hidden ownership structures, circular directorships and branding consistencies, streamlining investigations, reducing [indiscernible] review and accelerating decision-making. Insurance delivered 8% [ ARR ] growth this quarter, and there are a few dynamics worth noting given the diversity in the end markets we serve.

First, growth in our Life Business remains strong and has been bolstered recently by customers adopting more sophisticated models and increased usage. On the property and casualty side, 2024 was a standout year for both new business and retention, with several large cross-sell wins and retention rates in the high [ 90s ], presenting a bit of a tougher comp. In our banking line of business, which includes our lending suite as well as risk, regulatory and finance solutions, we delivered ARR growth of 7% in Q3. Reported revenue was flat in the third quarter versus last year, influenced by the revenue accounting for multiyear sales of on-premise solutions.

With Risk, Regulatory and Finance Solutions growing at mid-single digit, the headline growth rate masks the strength of our lending business, including credit lends, which continues to grow ARR at a low to mid-teens pace and is the largest revenue contributor. We're investing to expand our offering into a more comprehensive solution that spans the full lending workflow. This approach is resonating with our core customer base. [ Mid-tier ] banks and is increasingly enabling us to cross and upsell across our solution set.

Next, turning to Research & Insights. We delivered ARR growth of 8%, and that's an improvement as we lap last year's attrition events. Growth was further supported by strong upsell execution, fueled by our ongoing investments in CreditView, including research assistant and our suite of organic agenting solutions. Finally, data and information ARR grew 7% and continues to be affected by cancellations from earlier this year. On the positive side, we still see strong pricing power, sustained demand for Ratings data fees and strong Orbis new business volume.

Moving on to margin. We delivered ahead of our initial plan so far this year with a 400 basis point improvement in Q3, and we now expect approximately 33% for the full year. This represents over 300 basis points of year-over-year margin expansion before absorbing a headwind of about 100 basis points from the three M&A deals within the last year. But let me be clear, we're not stopping there. This progress is rooted in programs designed to maximize investments in strategic growth areas and realize a more efficient organization footprint. We remain focused on expanding margins towards our medium-term commitment of mid- to high [ 30s ] over the next 2 years. To get there, we are prioritizing and redeploying R&D spend across our portfolio, redesigning enterprise processes with Gen AI, deploying productivity tools and optimizing vendor relationships. We remain confident in Moody's Analytics high quality, predictable ARR growth, and our ability to deliver sustained margin expansion, strengthening the earnings durability.

Now to help with modeling, I'll walk you through a few additional details behind our updated outlook assumptions. And you can see the MIS [ NMA ] guidance update here on Slide 13. We now expect MCO revenue to grow in the high single-digit percent range. We are reaffirming our operating expense guidance, which supports an adjusted operating margin of about 51%, highlighting the strong operating leverage of our business. At the MCO level and excluding restructuring charges, we anticipate operating expenses to increase by $10 million to $20 million quarter-over-quarter, consistent with expectations we shared in the second quarter. We also expect incentive compensation to be approximately $100 million, in line with Q3.

As demonstrated by our margin performance, particularly in MA, our efficiency program continues to deliver meaningful improvements. We have already executed over $100 million of annualized savings helping offset annual salary increases and variable costs. We are updating our adjusted diluted EPS guidance range of $14.50 to $14.75, and which implies roughly 17% growth at the midpoint versus last year.

One [ modeling ] note on our tax rate. In October, a statute of limitations expired related to certain pre-acquisition tax exposures, Moody's assumed in the prior year M&A transaction. This will result in a onetime approximate 200 basis point favorable impact on our full year 2025 effective tax rate. Please note, this benefit will be fully offset by the release of the indemnification asset, so there will be no impact to net income or EPS.

Turning to cash flow. We now anticipate our free cash flow to be approximately $2.5 billion, and we are increasing our share repurchase guidance to at least $1.5 billion. That puts us on track to return over 85% of free cash flow to our shareholders this year.

To wrap it up, this quarter's results reflect the strength of our strategy and execution. We are approaching transformative shifts in technology from a position of financial strength, allowing us to invest in innovation while continuing to expand margins and grow revenue as seen again in Q3. And with that, operator, we're now happy to take any questions.

[Operator Instructions] Our first question will come from the line of Manav Patnaik with Barclays.

This is [ Brendan ] on for Manav. Just wanted to ask just to get your guys' thoughts on just pros and cons of AI in your Analytics business. It sounds like you had some recent wins, but just curious how you're thinking about seat-based exposure, whether or not it's explicitly tied to your contract or not? And just what you're hearing from your key financial services customers on the topic?

Yes. Brendan. So first of all, we've really never had kind of seat-based exposure that's generally not the way the contracts have been structured. So AI is not going to be any different. I would say, maybe just to kind of zoom out in terms of how we're thinking about it and going about it.

First of all, we're embedding AI into a bunch of our own workflow solutions and software. Obviously, we've done that with Research Assistant. We now have something like 20 different stand-alone or AI-enabled applications. So we're -- that gives us an opportunity to monetize there. But we also just launched what we call [ Agentic Solutions ]. So we've got smart APIs and [ MCP ] servers. And think about that as like tools that are built on top of Moody's data. This huge data state that we talk about all the time, and they can power LLM and third-party agents with that Moody's data. And then we have been building a suite of highly specialized workflow agents. We've got more than 50 domain-specific agents already today that leverage our proprietary data and subject matter expertise, and support all that automation and can be embedded into customers' internal workflows.

I gave one example of that on the call. So -- and I think what you're seeing from us is we have this massive content estate. AI is really an unlock opportunity, and we're trying to meet our customers where they are. Whether they need to have access to that content through our own workflow and supported by AI, whether they want it on partners' platforms, or whether they want it embedded into their own internal AI workflow orchestration. So everything we're doing is to try to meet our customers where they are.

Our next question comes from the line of [ Peter Knutson ] with Evercore.

I'm just wondering if you could help me think about to what extent, if any, the third quarter's record issuance reflect full forward activity? And then within that as well, what you guys are assuming for CLO activity, maybe in 4Q but more broadly in 2026, since that was such a large driver of that upside?

Yes, I can start with the kind of the pull forward. I would say, and we've talked about this before that there's a lot more pull forward that goes on in spec-grade than there is investment grade. Understandably, right? Because investment-grade issuers tend to always have market access, and that's less true for spec-grade issuers. So we tend to see pull forward more in spec-grade.

I would say the pull forward that we've seen in 2025 is pretty consistent with what we've seen over the last, call it, 4 years. So it's in line with that. Very little pull forward from investment grade. And as we've talked about, we've got some pretty healthy maturity walls going forward.

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

I wanted to focus on the KYC business. Can you talk about what data sets within that business are proprietary? And are you seeing the longer tail of competitors there get stronger by being able to integrate AI? That's a concern that we've been hearing. So I was hoping you could weigh in on that.

Yes. So there's a few data sets that really go together for our KYC solutions. The first is Orbis, which is our massive company database. And I think it's -- we think of that as derived data, first of all. It's accessed through a global commercial ecosystem, where we've got the rights to use and aggregate the data and then we cleanse it, and we normalize it, and that really enhances the value of all that data. So it's not as easy as just going out and web scraping that content. That's first of all.

And the second data set that we have is around politically exposed people and risk-relevant people. That's a fairly unique data set that we have that was originally -- that was actually part of our [ RDC ] business that we purchased years ago that was formed by a consortium of banks after 9/11 who wanted to compact [ terrace ] financing. And so that business grew out of that. And then the third is our AI curated news. And then I think part of the secret sauce is that we then link that together and we have really the world's best beneficial ownership and hierarchy data. And that really gives our customers a 360-degree view of who they're doing business with, that I think is relatively unique in the marketplace.

Our next question comes from the line of Andrew [ Steinerman ] with JPMorgan.

Rob, if you saw, there was a Wall Street Journal article from October 15 that wrote up the Moody's report on refi walls and the way they portrayed it for U.S. companies that there was a decline in refi walls. Again, I don't know if you saw the article. It caught my eye. But obviously, that's framed a lot differently than Slide 6, where you're seeing a really favorable environment for refi walls. And if you could try to square the difference, that would be helpful and mention something about the U.S. refi walls.

Yes, Andrew, I think that article was citing U.S. spec-grade, which was down, call it, 5% to 6%. Yes, that's right. So it was really a subset of the broader maturities. And I think I might point out a couple of things that there's actually, as we kind of look further out, there's actually a significant portion of maturities that are actually a good bit farther than 4 years out. And that's because of the -- basically the steepening of the yield curve over the last, call it, a year or so. So we've actually seen average tenors shortening. We've seen issuance less than 7 years being more attractive than issuance out past kind of 7 to 10 years. We've seen average tenors shorten up. And all of that ultimately is going to be, I think, positive as we think about the stock of what needs to get refinanced over not only the 4-year walls that we quote, but even beyond.

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

Rob, usually during the third quarter, you talked about your early thoughts into 2026 for issuance. And just in light of that, refi wall is still healthy, but maybe less of a tailwind next year. And M&A, though, could provide a nice uplift. And then wanted to also get your thoughts on the data infrastructure financing and if that's going to be a meaningful driver in '26, and how you think about that opportunity overall?

Yes. Thanks, Toni. So -- it's -- as always, in October, it's a little too early for us to actually give guidance for next year. But we can kind of tell you how we're thinking about next year. And I would say that and you've heard me use this kind of framework in years past.

Right now, I think there are more tailwinds than there are headwinds going into 2026. So we're thinking it's going to be a pretty constructive issuance environment into 2026. And let me talk about -- let me start with the tailwinds because we think they're more tailwinds.

So first of all, we've got spreads at very tight ranges right now. We have [indiscernible], so we have the potential for lowering benchmark rates. You touched on M&A. We've certainly seen the M&A environment really pick up in the third quarter. You heard Noemie talk about our RAS pipeline is very robust. We're hearing very positive commentary from the bankers about the M&A discussions and pipelines that they have. So 2026 may be the year that we really see not just M&A, but sponsor-backed M&A, come back into the market. We've talked about what a positive that will be. We do have the potential for further resolution in some of these geopolitical conflicts that I think could provide a little bit more market confidence.

Kind of a mixed sentiment really around economic growth, but the current thinking is that we're not looking at a recession, while there's been a little bit of a slowdown, we think the current levels of growth across the [ G20 ] are generally sustainable into next year. You mentioned the refi walls. And we do think that the default rates will continue to decline. They're a little bit above historical averages at the moment. But we look for that to continue to decline. So all that feels pretty good.

And just in terms of what the headwinds could be. I mentioned economic growth. And obviously, we're looking at things like job growth and consumer confidence and spending to get a sense of whether there could be actually a further deceleration of economic growth. Obviously, we've got some headline risk around global trade dynamics, particularly with the U.S. and China. That creates volatility in the markets. That's usually a negative for issuance. It can create some risk off environment that can widen out spreads.

So in general, Toni, feeling pretty good about it. And you asked the last thing you asked about data centers. That's why we talk about these deep currents. You're seeing tens and hundreds of billions of dollars going into infrastructure investment and particularly around digital infrastructure and data centers. And we're having a lot of dialogue all around the world, and we expect that to continue into 2026. So that will be a deep current that continues.

Our next question will come from the line of Alex Kramm with UBS.

Just coming back to Moody's Analytics. A lot of things going on there. It seems that things are maybe tracking a little bit slower than your expectations at the beginning of the year. Please correct me if I'm wrong. And I know you mentioned a couple of things, but maybe just talk about relative to the expectations at the beginning of the year. What maybe are the things that surprised you negatively? And how we should be thinking about those items as we get into 2026?

Yes. Maybe, Alex, I'll start and then Rob can add if needed. So if I look at the top line for the third quarter in MA, we were right on our expectations in Q3. You may recall, earlier in the year, we took slightly down our guidance for the full year because of some attrition in U.S. government. And then -- which affected mostly KYC and our data and information line. But since then, we've been pretty consistent with our expectations.

If you look at ARR growth of 8%, very in line with the second quarter. We have a strong pipeline for the fourth quarter. Growing nicely, very strong coverage. So pretty heavy weighted in December. But I think there's a very strong focus on execution.

The way we look at the portfolio, I know there's a few puts and takes in each of the different mines. But overall, we're managing to a high single-digit growth. We're investing in our lending, underwriting KYC for corporate. We had a few very nice wins in the third quarter. So that balances out to a high single-digit growth, and we're pretty confident with the outlook for the full year. And we'll talk about next year, a bit more color in February, but we're delivering as expected.

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

Just wanted to ask one on private credit. We're starting to hear more, see more headlines, hear more concerns about just the health of private credit. I'm wondering if you can talk about how you see that potentially impacting growth there? Like I think there is potentially a school of thought that if there is more concern around the health there, there could be more demand for understanding of Risk and Ratings. Or could also be more debt, as you said, moving from public or private to public markets. Just wondering if you can kind of tease out some of the potential ramifications of that?

Scott, it's Rob. I think you started to nail it there. We've been talking for a number of these calls about how important it is to have a rigorous third-party independent assessment of credit risk in the private credit market. And that was the driver behind what we did with MSCI. And it's interesting.

I mentioned in my prepared remarks, we don't have a lot of Rating exposure in the direct lending market, right? And that's, again, one of the reasons that we partnered with MSCI to be able to provide investors with that third-party view. And I mentioned -- so I'd say two things. Whenever you start to see a little bit of credit stress in the market, and I talked about, at least in the public markets, the spec-grade default rate is higher than historical averages. So you can imagine that there's similar stress in the private credit market. That drives more demand for Credit Insight and Research. We see that with the usage of our website and all sorts of thing, the engagement that we have with investors. So I would say that's true.

And then second, you're right. I mean, we're now seeing a little bit of a of flow back into the public markets because at the end of the day, those coupons that you can get in the public markets are typically represent a fairly substantial savings versus funding in the private markets. So I think we could see an ebb and flow between the private and public markets. But I think we're pretty well positioned to serve the needs of investors and issuers, whether it's in the private market or the public market. And that's what we've really been working on over the last, call it, 2 years.

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

I just wanted to shift back to the M&A discussion you talked about a bit earlier. Noemie, I think you said that you're managing MA growth top line to high single digits. If I remember correctly, before you came, there was an Investor Day, I think the medium-term guidance for that business was low to mid-teens. Has that changed? Or should we be looking more medium term MA growth in the high single digits?

Yes. We've updated our medium-term outlook for MA earlier this year in February. So we're looking at a high single-digit growth for ARR and revenue. That said, there's different dynamics within the portfolio. We are obviously having -- printing more higher growth rates in areas where we're strategically investing. And that was also the logic behind the restructuring program and looking at our organizational footprint. The way we deploy our engineering teams, the way we deploy our product groups, our sellers to the areas where we think we can generate higher growth. But overall, the growth rate is expected to be high single digit.

And we've also expanded margin quite significantly. We've updated that also in February, and we are now very well on track to meet those commitments. As a matter of fact, we've increased our full year guidance for MA margin to approximately 33%. So that's another thing we've also updated along the top line.

Yes. And I would just say we talked to a lot of investors over the years, and we had heard about this idea of the kind of the sweet spot being kind of high single-digit growth and getting some further margin expansion. And so that's what you see reflected in the medium-term targets, and that's where what you see us executing on.

Our next question comes from the line of Craig Huber with Huber Research Partners.

Rob, I want to ask, there's a school of thought out there with investors for last year plus that AI on a net basis is bad for your company and for other information services stocks. So I want to give you a chance to just talk about that, about the moats around your businesses both on the Rating side as well as MA, why you could fight that off any new potential entrants out there?

And then secondly, I just want to quickly ask, what in your mind was better about debt issuance so far this year versus your original expectations coming into the year?

All right. So first, on the AI is bad for our business. I'd love to double click with you on that. I just don't see that. I've been pretty consistent about -- when you think about, we have a massive mostly proprietary data and analytics estate. And remember what anchors that, Craig, is it starts with the Ratings agency. We're producing unique proprietary rating content and research every single day. That is our largest content set. And I talked about Orbis and how it's not just aggregating publicly available company data. This is a complex curated web of information providers where you have to have the rights to this data, and then we're aggregating it and normalizing and creating value.

And even where we've got workflow software, right? So let's talk about our insurance franchise. Yes, we're delivering our solutions through software. But at the core of what we do in insurance are, I would say, mission-critical models, right? It's the axis actuarial models, and it's the RMS physical risk and catastrophe models. That is really, really unique IP that's delivered through software.

And so Craig, I actually think about, in some ways, we have a lot of this content that has been effectively trapped in our workflow software, right? If you wanted to get access to our [ CAPE ] models, you had to be a subscriber to our software, and you're a [ CAPE ] modeler. Guess what? Now we have the ability to democratize that access to this content to co-mingle the access and get unique insights. So it makes it, A, much easier to access our content in many more channels, as you heard me talk about. And that's going to open up new ways for us to monetize the content on different platforms, with different customer segments, where there's different value that they derive out of our content. And it's also going to allow us to have unique insights as this content is co-mingled.

So I feel very good about AI. And that's why, Craig, we've been really trying to be so front-footed on this from back in 2022. It's because we believe that this ultimately is an unlock. And we've talked about this on these calls. It takes a little bit of time when we're working with the regulated financial industries, but we are seeing some good signs of traction.

Your second question was, what is driving the issuance? I'd say, look, in the first 4 months of the year, obviously April, we had a lot of volatility in the market with the tariffs. That was, in a way, kind of a lost month, right? And we hadn't factored that into the guidance at the time. But you've seen, I think -- and you see it with the equity markets. The markets have gotten much more comfortable with the current environment. You've seen -- I said default rates are a little bit above average, but still fairly close to the long-term average. So spreads are tight. You've got -- and you've got a real pickup in M&A activity.

And you remember, back in February, we had talked about our M&A assumptions and that this would be back half loaded and -- so I think we are starting to see that M&A volume and activity that's supporting issuance and business investment that we had been thinking we would see back in that call in February. It's just that we hadn't anticipated the volatility in the first half of the year.

Yes. And to that point, we -- if you look at our Q4 implied guidance for MIS, that's pretty consistent with what we had at the beginning of the year. We've always had a pretty strong fourth quarter with the low teens MIS transaction revenue growth, and that's been pretty consistent throughout the year.

Our next question will come from the line of Russell Quelch with Rothschild & Co Redburn.

Noemie, you put out some headwinds around slowing retention and sales driving that slowdown in the insurance [ ARR ]. And I wonder if you can elaborate on that a little bit more, given insurance has been a strong pillar of MA growth over the last 12 months. Wondering how you're thinking about insurance growth into 2026, given that there's a slowdown in premium growth in the underlying P&C market and normalization in storm activity?

Yes. Insurance, we have a few dynamics going on in the third quarter and that translates into the full year outlook that I talked about. We have actual data and models. So access is trending very nicely. We have high double-digit growth. We continue to see customers switching to a high-definition models, and that's been really driving growth this quarter.

The RMS and the [ IRP ] migration, we had a lot of significant transactions in 2024 and early 2025. There's a bit of pull forward of pipeline. So now there's a digestion going on with our customers. We are going after the largest -- the remaining pool of customers who haven't yet moved to the platform. So that's one driver. So we have a lot of pipeline there that we expect will drive growth of that business in long term.

There's just a -- it's not so much of a headwind. In fact, it's just more like tough comparison from 2024, where we had a lot of those customers migrating into the RMS platform, and we still have a lot of pipeline with the remainder as we head into 2026.

Yes. Russell, I would also -- I mean, I spent a lot of time with our insurance customers. And I feel pretty bullish about what we can do in that industry. You've got insurers who I would say, are behind the banks in terms of their adoption of digital platforms. Noemie talked about moving to the cloud, but also just sophisticated third-party data and analytics. And so there's a lot of interest from insurers and thinking about how they can leverage a lot of our content to get signal value to help them understand risk. And you've seen us broaden from really a property focus with our [ CAPE ] business. And obviously, we have a Life Business as well.

But in the P&C business, we've moved into casualty. There's a lot of interest from insurers to have a more data-driven approach to thinking about casualty risk, and that's what we did when we acquired Praedicat. We've pulled together a cyber working group across the industry. I think there's still a lot of opportunity for that market to grow in terms of GWP and so do the insurers, but they need to have models and data that they can be very confident in to help that market grow. So I feel very good about it over, let's call it, the medium term.

Our next question comes from the line of Sean Kennedy with Mizuho.

I had a follow-up on Moody's Analytics. So I believe last quarter, you mentioned that sales cycles were lengthening a bit. I wanted to ask if anything has changed there as we got further away from [ the spring ]? And also how is the general demand environment for banking?

Yes. So I'll start with the demand environment for banks is actually pretty good. We're having some very good discussions and wins, frankly, with our banking customers. I talked about that one kind of marquee deal. But actually, we're seeing very good engagement and growth from our biggest banking customers for the reasons that I talked about. And so I'd say I'm not sure there's much of a change from the last quarter in terms of how we talked about kind of sales cycles.

I think we talked about there was a little bit of a lengthening in the sales cycles over the, call it, last year. But there was also an expansion of the size and the complexity and number of products that we're pulling together as solutions for our customers as well. So to me, when I look at those together, I feel fairly comfortable when those things are moving in tandem.

And I would say -- the last thing I'd say, I spend a lot of time with our customers. There's a lot of focus right now on growth. And that, at the end of the day, and I get it. We get asked about is it regulatory drivers that drive the growth of your solutions? There's nothing better than being able to talk to your customers about how you can drive growth. And that ultimately means that there's a more positive sentiment across the customers as they're thinking about the future and investing in their business.

Our final question will come from the line of Jeff Meuler with Baird.

Rob, you had a couple of call-outs on climate solution wins outside of P&C insurance. Obviously, that was one of the thesis points of the RMS acquisition. Is the message behind the message that you feel like you're at an inflection point where you expect that to really start taking off? Or are you just kind of conveying some large wins that you had in the quarter?

And then just to be clear, does that revenue, when you sell Climate Solutions outside of insurance, does that get reported within insurance or elsewhere?

I guess one of the reasons I brought it up is that was -- as you noted, that was one of the thesis that we had when we bought RMS was that this content, this -- the models and the data to help institutions really understand the physical risk of extreme events was going to be important beyond just the insurance business over time. And so we -- I've been trying to give some examples of where we've had some wins of banks who are taking these solutions.

I would say that, that started with the biggest, most sophisticated banks who are using the RMS models. We've been thinking about how do we take some of that content and package it differently so that we can make it more useful and available to a broader segment of banks over time. But you can -- we hear from banks as they're underwriting loans that they're interested in understanding the physical risk of the collateral they're taking. We hear from corporates. They are interested in understanding the physical risk of locations across their supply chain and across their own physical footprint. We're engaging with governments who want to understand the vulnerability of communities to various extreme events. And of course, we're starting to hear that from investors as well.

So there's some product development work as we start to see the demand from these other sectors to be able to package the content in a way that's useful for those different customer segments. So I'd say it's still relatively early, but I am giving examples of demand outside of insurance. And we're going to continue to lean in on that.

The last point on -- 2-point actually on your question about where that the revenue goes into the insurance line within Decision Solutions. And then the other thing I'd add is we -- when we acquired RMS, we had revenue synergy targets that we've published, and we are well on track to achieve those.

And that will conclude our question-and-answer session. I will turn the call back to Rob for any closing remarks.

Okay. That's a wrap. Thanks, everybody, for joining. We'll talk to you next quarter. Bye.

This concludes Moody's Corporation Third Quarter 2025 Earnings Call. Immediately following this call, the company will post the MIS revenue breakdown under the Investor Resources section of the Moody's IR homepage. Additionally, a replay will be made available after the call on the Moody's IR website. Thank you. You may now disconnect.