Good day, everyone, and welcome to the Moody's Corporation 4th Quarter in Full Year 2025 Earnings Call. At this time, I would like to inform you that this conference is being recorded and that all participants are in a listen-only mode. At the request of the company, we will open the conference up for questions and answers following the presentation. The call is scheduled to last approximately one hour. I will now turn the call over to Shivani Koch, Head of Investor Relations. Please go ahead.

Thank you. Good morning, and thank you for joining us today. I'm Shivani Koch, 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.moody's.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. 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 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 31st, 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. And 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 70% earnings growth over the past three years. So that'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. It 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 and 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 served 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 number one provider in the Chartist RiskTech 100 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. And 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 standalone 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 isn't 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, Intap, 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 Credit Lens 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 two-thirds 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 percent of each memo and saves analysts hundreds and hundreds and thousands of hours of time, equating in some cases to 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 in 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 15 times. So some real efficiency. And KYC continues to deliver mid-teens growth driven by customers' trust in the quality, 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 20-fold over the last three 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 there's a pattern here, one of the world's largest global payment platforms signed a multi-year, multi-million dollar agreement to embed Orbis via API into their new customer onboarding processes. And they're threading two critical requirements. They're creating a smooth customer experience through pre-populated 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 and firmographic data to support their operations targeting illicit finance, with a recent operation resulting in 83 arrests across six countries. And it's in environments like this where accuracy, provenance, and the auditability are non-negotiable. Our data can't be synthesized from public sources. It reflects how ownership and control actually work in the real world, cutting through complex, multi-layered 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 risks. 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 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've continued 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 three primary areas. First, in lending and credit decisioning, we're upgrading customers onto more integrated AI-enabled platforms. This includes moving credit view users to what we call Moody's view, expanding credit lens into a broader lending suite, and delivering agentic 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 a company's size, exposure, and sophistication. All of that will be delivered through the Moody's for 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 Predicap'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 CatBond rating methodology and revamped CatBond 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. That'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 Noemi, I want to thank our teams for their exceptional work in 2025. Noemi, over to you.

Thanks, Rob, and hello, everyone. The fourth quarter kept 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%, which is in line with organic cost constant currency recurring revenue growth, also at 8%. Now, before turning to the drivers of AR 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 deliver double-digit AR growth and represent approximately 45% of total MA AR, 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 two years and 15% AR 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 non-financial 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 tiered bank that also leverages a broader set of Moody 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 2025 and continues to present meaningful expansion opportunities in 2026. Beyond the payments company customer example Rob mentioned earlier, we want new business with two 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% rule 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 and 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-end workflow solutions that are ready to deploy. Banking delivered AR 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 offerings for lending, including with AI capabilities from the numerated and Able AI 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 for our more sophisticated high-definition models and cloud-based intelligent risk platform drove 7% AR growth for the year-end 25, and that's an increase of 21% over the last two years. And looking at this two-year view is important because 2024 was particularly strong, reflecting record levels of customer migrations onto 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 four-year period. That's a transition that was supported by sustained customer demand and meaningful platform-led upsell activity. Next, turning to research and insights, we achieved 8% AR growth in this more mature business, underscoring the durability of demand, continued innovation, and improved customer retention. As Rob shared, we are enhancing credit view 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 adoption. Finally, data and information delivered 7% AR growth, supported by strong pricing power, and sustain customer demand across two distinct but complementary areas. Ratings data feeds are the primary growth driver within the segment, with AR growth well above the overall line of business. And that underscores their decision-grade 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've shared, 2025 was impacted by Doge-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 continued to invest in future growth. What differentiates Moody's analytics is our ability to invest in growth while expanding margin. 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 lifecycle process across MA, which we expect will drive higher productivity, improved quality, and faster delivery for customers. In parallel, we're 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 and infrastructure finance also had near-record issuance in the quarter. Private credit across all asset classes grew 40% in Q4 from particularly strong activity in fund 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 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 debt remains an attractive funding source. Accommodative monetary conditions, declining default rates, and healthy investor demand for yield should support access to capital across sectors. For the 4-year 2026, we expect total issuance to increase at a low single-digit percent pace, followed by ongoing refinancing needs, and 40-45% 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 projects year-over-year growth across all four 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 an 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 two years, we expect organic constant currency recurring revenue growth to be aligned with AR in the high single-digit percent range. From a margin perspective, our 34% to 35% adjusted operating margin outlooks 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 BIPs to the 50% to 53% 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 one-time 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 announce 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 our 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.

Thank you. If you would like to ask a question, please dial star 1 on your telephone keypad. If you are on a speakerphone, please pick up your handset and make sure your mute function is turned off so that your signal reaches our equipment. We'll ask that you limit yourself to one question. The option to rejoin the queue will be unavailable. Again, that is star 1 to ask a question. Our first question comes from Curtis Nagel with Bank of America. Please go ahead.

Terrific. Thanks so much for taking the question. 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're most confident in terms of investment, or should we expect more pairing 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, you know, 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 state, 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, 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.

Okay. Thank you.

Appreciate it.

Our next question comes from Alex Cram with UBS Financial. Please go ahead.

Yes. Good morning, everyone. 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.

Hey, Alex, thanks. And I think in a way, there's kind of two 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, you know, as you'd expect, when you've got, I'm going to say, kind of a portfolio, you know, we're selling into very different customer bases, you know, there's some puts and takes in terms of what's growing faster and what's growing not as fast. If you look at, you know, kind of the ARR trend across the portfolio in 2025, you know, 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 Noemi mention, we've talked about before on the call, some of that with KYC was impacted by Doge. And, you know, 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. You know, everybody wants to understand how much revenue is being generated by AI. And there were two 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 standalone 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, you know, our view is that that's going to then trickle through the rest of the customer base over time.

Very helpful. Thank you.

Our next question comes from Manav Patnaik with Barclays.

Please go ahead.

Thank you. Good morning. I was just hoping on the rating side, you could just help us with the cadence for the year in terms of how you, you know, assume the issuance trajectory there.

Yeah, Manav, hey, great to have you on the call. So I'm going to start with issuance, and then maybe I'll just go into revenue real quickly for you, because I know that'll 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 a, 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, 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 being front-end loaded. So I would say from a revenue perspective, we expect it to be, you know, 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.

That's super helpful. Thank you.

Our next question comes from Tony Kaplan with Morgan Stanley. Please go ahead.

Thank you so much. 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. Thank you.

Yeah, Tony, 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, we all understand we have a massive proprietary data state. 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. 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 AI reasoning engines. So it makes the data usable for reasoning. And what that is, is a structured, governed representation of, you know, 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.

Thank you.

Our next question comes from Ashish Sabhadra with RBC. Please go ahead.

Thanks for taking my question. 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 Cloud 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?

Yeah, Shish, hey, great to have you on the call. Well, again, I think the way to think about this, and it's interesting if you think about, you know, you heard me talk about credit lens 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 know, you heard me say at the high end, almost all of the banks, the big tier one 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, you know, we had a bank that's working on agentic, I mentioned it in my remarks, they're building an agentic workflow for lending. So while they don't need to adopt credit lends, 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 models. So they're consuming it through either through smart APIs and MCPs or specialized agents that are going right in to the workflow that they're building. So for me, again, it comes back, you know, we talk about we're going to be wherever our customers want us to be. If you are a tier three bank and you want a lending software platform that's enabled with AI and has access to a lot of our data, 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 an 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.

Please go ahead.

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

Yeah, Andrew, hi. 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 a one 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 two percentage point headwind to the revenue growth – sorry, one percentage point headwind to MCO revenue growth and two percent headwind to MA revenue growth, which is embedded in our guide. And there's – most of it is one time. 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 mid-year 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% each point 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 5 to 10 cents 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 AR, are 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.

Thank you, Noemi.

Our next question comes from Owen Lowe with Clear Street. Please go ahead.

Good morning. Thank you for taking my question. 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 drive of these strengths, and how should we think about your medium-term guide from here? Thanks a lot.

Yeah, so we're guiding adjusted operating margins with these ratings of about 65%. I think there's two components, obviously, revenue and transaction revenue growth. But we've also made significant investments, if you recall, over the past couple years or three, four 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 ratings committee, spending time with issuers, and less so on more administrative tasks. 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're looking to also in 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.

Please go ahead.

Great. Thank you, Rob. Bob, 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. You can see in your stock price and in 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 in 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 you 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 perceived 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? Thank you.

Yeah, 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, you know, we get questions about this. And, you know, I would say a few things in terms that, you know, 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, you know, 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, you know, there's legal and regulatory issues, you know, 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, you know, 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, you know, the models are not simply doing entity resolution. And that is a really important thing to be able to resolve against the right entity. And we've combined probabilistic models, a human in a 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, 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 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.

This concludes Moody's Corporation 4th 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.