Conference Transcript - MCO 2026-03-12

Curtis Nagel, Analyst — Bank of America

Good morning, everyone. Welcome to the BVA Information and Business Service Conference. We're bringing back after a two-year hiatus. We're happy to have all you here. I'm Curt Nagel. 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 basically the entire sector, covering what we think will be the most pertinent themes, and then, of course, headline with all things AI. Um, opening the conference today, uh, really pleased to be, uh, welcoming Rob Fauber. He's the president and CEO of, uh, Moody's 20 year veteran, uh, of Moody's, uh, started at B of A his career, um, and under his tenure as CEO for the past five years, led the company to record profitability, both in ratings and in analytics, uh, and is embedding, I think I turned off for a sec. Uh, embedding AI across every fashion of the business. That's a huge focus for him, driving internal efficiencies, new product development, solutions, and revenue streams based on their 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?

Robert Fauber, CEO

Yeah, thanks for having me, and it's great to have you covering Moody's. Yep, great to be here.

Curtis Nagel, Analyst — Bank of America

So, yeah, in terms of the first question we're generally starting with, at least for the info service companies, is unsurprisingly on AI and moats, right? We'll get into some of the, you know, what we think are or could be the biggest opportunities, how you're harnessing the technology. But, yeah, sticking with moats, I think it's generally understood that, you know, anything around credit, you know, it's 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, you know, stuff that isn't outright owned by Moody's, you know, what are the moats around there? You know, and I guess in terms of maybe moats that people, you know, don't recognize or don't appreciate as much, whether it's regulation or switching costs, you know, how would you address that?

Robert Fauber, CEO

Yeah. 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 in 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, you know, basically our content estate, I'm going to move now over to analytics. I would say a few things. And then 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 three 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 know, 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 lost 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 cap models, our customers use of those models and those data sets is being reviewed by their regulators right 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 three 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 um then we have um uh information that we get from these bureaus uh 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 uh ownership structures

Curtis Nagel, Analyst — Bank of America

and trees that that is transformed proprietary data that's where most of the value is in the orbis database yeah i'll pause there okay um maybe a good segue in terms of uh thinking about adoption right for some of these uh you know enabled products genic workflows stuff like that ai enabled databases um during the last call you talked about your large customers right consuming at you know much higher rates than twice the rate uh for the rest of the business uh or you know your other customers, in part due to, you know, as you talked about, more sophisticated AI tools. Where specifically are you seeing, you know, the adoption curves, you know, 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?

Robert Fauber, CEO

Yeah, so I'm going to focus on banks. It's our largest customer segment. And there is a tale of two customers. So you're right at the 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 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, they're building those platforms. And that means it's either, historically, people have consumed our content from our workflow software maybe through our website uh 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 every big financial institution i talk to is talking to me and and i'm sure others in 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 the the strategic the largest banks and that's very encouraging to us if they if they wanted if they thought it was commoditized we'd be having very different conversations but then when you go down to tier two and tier three banks the regional banks the credit unions it's a very different story we serve a lot of them they're 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.

Curtis Nagel, Analyst — Bank of America

I guess another good segue, I think maybe a little bit 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, you know, not to belabor the point, but, you know, companies like yourselves that have mission-creditable proprietary data. You know, do you foresee, I guess, you know, 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 one to three years?

Robert Fauber, CEO

Yeah, I think that's the right timeline, 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 i would say a couple things um so uh 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 it's my credit process right so that's a great discussion for us to be having it is a different discussion um and then it's all about business case and roi and all those kinds of things and you start to say wow the the data is going to be the data and models and contextualized intelligence can be very valuable right in in there's going to be a huge return on that how do we think about the pricing um i think you're going to see uh us move over that time horizon to implement elements of consumption into the model and i 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 old fat good old-fashioned data feeds we don't know all of the usage in a in a traditional data feed environment we have there are ip restrictions and usage restrictions we audit our but we don't know what 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 rev ops piece and then there's a customer piece a lot of times people you know lose sight of this because you think aren't you just going to get uncapped upside for usage of the data that that sounds great but the customers you think about what the customers are dealing with uncapped cloud costs and they want you know 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 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 uh uh intelligence yeah and i guess maybe as a byproduct you know before uh you know maybe pricing consideration stickiness i would imagine would be a good consequence of that right i would think the more embedded we are the stickier we are and you know 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

Curtis Nagel, Analyst — Bank of America

okay um switching gears maybe a little bit so again we've talked about ai customer relationships revenue opportunities um value of the data um how should we think about ai within moody's internally in terms of, you know, asset and labor efficiencies. Again, kind of let's call it the one to three year time horizon. You know, just looking, you know, 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, you know, good old fashioned, you know, expense management or, you know, whatever. But, yeah, just basic question of kind of how to think about, you know, internal utilization and asset efficiency.

Robert Fauber, CEO

Yeah, you talk about one to three years, and this is coming at us fast. So I'm a real bull on the efficiency opportunity across our organization. So we, like many other companies, went after customer service and some other things. That was low-hanging fruit early on. And now we're going after a product development lifecycle. And what that 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 i built a website at 3 30 in the morning the other day i mean so um 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 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 right it's just a it's just another vehicle to to to consume our content so uh i can't change the you know i'm not going to change the medium-term targets but i can tell you we're going after this aggressively and you know it it it starts with me and i'm vibe coding and everybody at the company knows that and um so i i think there's a real opportunity here okay and maybe

Curtis Nagel, Analyst — Bank of America

just to you know put i guess a you know final point of that um can't change the uh long-term target right or the medium target high 30s um but i i guess in terms of you know not to sort of again belabor a point but in terms of the arc of potentially reading you know getting out there maybe even at some point you know thinking about maybe get the 40 i don't know but yeah yeah there's a general margin implication yeah so i guess there i would say um i'm bullish on the opportunity um 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. Talked a lot about analytics business, AI and ratings, right? Your highest margin business by a pretty good margin. I think your guidance this year is above your targets and that is obviously on things like the volume leverage and you're lapping some investments. But yeah, just very broadly, how does AI change your ratings business?

Robert Fauber, CEO

I would say two 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 on with AI is 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 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 um and you've seen already the operating leverage that's that's continued to come into the business even last year 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, you know, 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, you know, unique insights that the rest of the market doesn't have.

Curtis Nagel, Analyst — Bank of America

Okay, fair enough. Sticking on, so we'll, I guess, put a bookend on AI. Sticking on the ratings business, you know, I question, and I know there are a lot of moving pieces here. You know, just generally, I guess, assessing the puts and takes, the risks, opportunities for the guidance you gave, low single, for issuance, you know, for the market, you know, whether it's uncertainty on pulling forward, you know, refi walls, geopolitical risks obviously are a huge question right now, or just, you know, general data center CapEx, that's been a big driver. What specifically is and isn't the model? And again, how should we think about the puts and takes?

Robert Fauber, CEO

You know, 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 Day, 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. 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. uh 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 two years they're all still firmly intact what kinds of things are they um so economic growth uh it certainly has been one but you know uh blackrock put out a number 68 trillion dollars of infrastructure funding needs by 2040 that hasn't gone anywhere uh you put ai and data center and not just data center but all of the related uh energy uh production transmission grids renewables transition finance all of that that's all still there uh heightened geopolitical risk has meant military build-ups massive investment is going to go on in militarization uh and defense uh and uh 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 oh by the way we also have a huge a huge amount of debt has been issued over the last five six 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 still there yeah structurally so no no change okay and yeah march is always tough it is it's it's early

Curtis Nagel, Analyst — Bank of America

in the year that's what that's what i we have to keep in mind okay um maybe just a segue here um private credit right um you know small um has been a high growth uh business for you um i guess how should we think about um a if you know you're willing to say just the revenue contribution for this year and then going out maybe a few um and then just kind of thinking about it like you know you've got certainly some puts and takes right things you talked about uh you know impact private credit we've got concerns about outflows and credit quality um which would you know technically be a negative on the other hand right that theoretically drive more demand for deeper analysis of of you know portfolios and specific companies uh so how does it all that balance out

Robert Fauber, CEO

how you're feeling about private credit um so i feel much better uh you know just where our franchise is now than several years ago it's interesting the the discussion with investors and analysts several years ago was um isn't private credit a big negative to the rating agency because it's the disintermediation of the public markets and that that was a huge narrative we geared up we found ways to serve that market there's still lots of that market that are unrated yeah um uh we have seen very strong growth in parts of the rating agency serving parts of the private credit market and now the questions are hey is this now a headwind because there may be as you said you know heightened defaults and out fund outflows and well um that means you know The public markets are going to take up the slack. And I have said before that a lot of the direct lending is like a deferred, 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, you know, to some extent, I'm relatively agnostic, right? 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 uh and the second thing just to your point is you know i've been saying this for a couple 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 uh to the investors and allow this market to scale and i you know i would hear all the reasons that that didn't need to happen and but i think now there's a much much greater understanding of the benefit that third party uh 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 the proprietary default databases the gold standard credit models and guess what they're ideal for for assessing private credit and so we're addressing that market opportunity yeah so um i guess in the context to get you know i mean just judge it by the headlines we're seeing um in terms of rate i mean is that rate of adoption um you know accelerating you know in a fairly linear you know path of relationship i would say it's very small so the investor use of credit models not surprisingly has has been small the the biggest customer base for all of our credit models are bank credit departments. 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 problem? 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 and private credit. Setting the table, I guess.

Curtis Nagel, Analyst — Bank of America

Okay, fair enough. Switching just quickly back to MA. So I guess you're kind of breaking it down by sub-segment, right? your KYC business is doing really well. One, you know, in terms of thinking about the rate of growth, roughly 20%, is that a sustainable rate? Insurance, you know, you're calling out, and we've talked about this a little bit more, you know, demand for sophisticated products. So how should we think about that, you know, again, as a rate of growth this year? And then, I guess, what needs to happen within your banking business to get that to reaccelerate? I know there were some purposeful, I guess, pullbacks in transaction revenues, but how do we think about that segment?

Robert Fauber, CEO

Yeah, so you kind of talked about the big three, 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 two 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 revenues, 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 de-emphasizing 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, not only do we have the cloud-based platform adoption of our core catastrophe models but we've now moved into um uh we acquired a company a couple years ago that that provides geospatial ai geospatial intelligence um to support uh insurance companies in underwriting property underwriting and then that feeds in uh to 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 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 um and then of course you know we talked about uh kyc the demand for that continues at pace um 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 you know kind of uh 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 and that included the second half of 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 it just there's going to be a little different cadence of arr growth okay um uh so i i would expect in the first quarter we probably have a little bit of a downdraft towards the you know the the lower end of our you know high single digit uh ar you know guidance and then you know that'll pick back up through the balance of the year because i think it's really about just the calendarization and the selling okay understood yeah um let me quickly touch on uh capital allocation um i get one just in terms of um i don't think it's a huge focus but both on m a what assets would look attractive um and then i guess just thinking about you know buybacks uh considering you know current valuation and just

Curtis Nagel, Analyst — Bank of America

Yeah, how are you thinking about that framework?

Robert Fauber, CEO

Yeah, so 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 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. um uh and then um you know from an analytics uh perspective i mean gosh you know 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 you know when you when you look at uh do you want to bring more workflow into our into our solution suite um it's got to be something that has uh 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 work at this point yeah so and then obviously everyone is thinking about can they get access to proprietary data but for us you know 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 So wherever we can find uniquely valuable data sets that we can put into that connected intelligence system, make the system itself more valuable, make that data more valuable and monetize that through multiple customer segments, that's attractive for us. Then I think, Noemi, 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 you know absent that you know no amy talked about the two billion dollar share buyback this year that's up uh i think something like 25 percent from last year um and no amy did signal that you know we're aggressively buying back stock uh you know here in the first half of the year okay uh maybe one um quick very quick lightning round uh word association uh so uh first refi well very strong very strong okay uh private credit needs independent credit assessment

Curtis Nagel, Analyst — Bank of America

margins very robust very robust okay rates tbd tbd fair uh and mna it's coming it's coming okay all right uh by that i mean the market the market right fair clarification all right well i think that wraps up time rob really appreciate the conversation thank you thank you so much for uh