Conference Transcript - MCO 2026-05-28

Christian, Analyst — Adage

Good afternoon, everyone, and thanks for making it this far to the last session of the day. I'm 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 Farber. Rob, thank you very much for coming back to the conference, and a special thank you today. I know you've been in meetings all day, so I appreciate you making it all the way here.

Robert Scott Fauber, CEO

Yeah, 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 o'clock 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.

Christian, Analyst — Adage

Good stuff. No better place to start than AI strategy. How did I know that was going to be the first question? I would say, as from my observation, your AI offering has evolved. It's gone from, you know, standalone research assistant tool. Now you're doing more MCP-based API models, more integrating into developer workflows like, you know, in 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?

Robert Scott Fauber, CEO

Yeah, so, Christian, over the last, you know, let's call it eight 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, said, look, this can be a threat or this can be an opportunity or both. But I think we really, really believed there's going to be an opportunity for someone who has an intelligence estate like we do. And 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

Christian, Analyst — Adage

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

Robert Scott Fauber, CEO

What's interesting is in 2023, you know, we announced, you know, kind of a partnership with Microsoft. We deployed co-pilot 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 toolbar and be able to call Moody's content into your co-pilot answers. So if you want to develop a credit memo and strengths and weaknesses and do peer 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, you know, intelligence source that the financial community uses and trusts. 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 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. 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 core parts of our content and intelligence system available now 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'll 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 we're not doing consumption-based pricing at this point. What we really want to do is drive embeddedness and usage at these financial institutions and have them get tremendous value out of our content. So 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.

Christian, Analyst — Adage

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

Robert Scott Fauber, CEO

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 three 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 a 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 In some cases, we actually form industry working groups, and the customer community, the insurance community, actually invests in the tooling. So there's a real, between the catastrophe models and the actuarial models, these are 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 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 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 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 gonna 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 where understanding the connectedness that we have

Christian, Analyst — Adage

created is particularly valuable. Cool. Let's dig into your businesses. We'll start with Moody's Analytics. Just a near term here, as you think about sort of AR growth in that business, it's kind of held in around 80-ish percent. As investors think about, say, 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? Yeah, so

Robert Scott Fauber, CEO

it's a broad portfolio. I'll probably just touch very quickly on five things. One, when you think of our flagship product is really the credit research, right? And we're 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 one offering with an agent layer over top of that. That creates a lot of utility in the ability to see things from our content estate that 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 one view platform. That's one. Two, agent-ready data, AI-ready data, we formed a sales SWAT team at almost every major financial institution and 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. 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 two and tier three 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 a 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, you know, kind of contributing to growth across the portfolio.

Christian, Analyst — Adage

So you recently brought in a new head for the MA business, which was kind of an interesting choice, somewhere 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 one of two things that you think are very important for her to accomplish in the first couple of years?

Robert Scott Fauber, CEO

If you didn't see the announcement, we have hired Christina Kozmowski. She was employed 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 their 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 friction 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 Logic Monitor for five years, a 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 Christina's 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, you know, 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.

Christian, Analyst — Adage

You sound it, for sure. Question on just MA around regulation. Historically, that's been a catalyst for incremental demand of some MA products. But as we're in a, you know, quote-unquote deregulatory environment, how do you think about that as a maybe headwind for that business?

Robert Scott Fauber, CEO

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. They're 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 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 a regulator has 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 this, 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.

Christian, Analyst — Adage

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

Robert Scott Fauber, CEO

Just like typical equity analysts, decent margin expansion.

Christian, Analyst — Adage

The best I'm going to get. The context, though, is over the last five years, the business has nearly doubled in revenues. You know, 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?

Robert Scott Fauber, CEO

Yeah, so you can see we're well in 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, you know, 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 lifecycle 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 I don't want to sound defensive and I'm not looking for kudos but we don't have five different divisions I have ratings and then I have everything else and and we have been working on pulling all of that together and bringing together 13 different tech stacks and going to one 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 making progress on that, that has been also contributing to our ability to start to get some margin. And I think Christina, as she comes in, is going to be able to continue that. Okay. Let's move to your ratings business.

Christian, Analyst — Adage

Believe it or not, that is your actual biggest business. It 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 pair. Maybe just walk through how you're thinking about 2026 in terms of the building blocks to get there. It's clear a lot of tailwinds. So curious also balance between tailwinds and risks.

Robert Scott Fauber, CEO

You know, and we didn't change our guidance in the first quarter. And obviously, we had a war breakout, and we had a Sazpocalypse and all sorts of stuff. But, you know, 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 had enough, 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 six 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's 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 pickup 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 the 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. You know, our guidance doesn't really take into account a risk-off month, right? So I think that's, you know, that's something for us to watch. But right now, the markets are quite constructive. And, you know, so I, you know, I continue to, you know, feel good about it.

Christian, Analyst — Adage

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

Robert Scott Fauber, CEO

Yeah. 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, you know, project finance or CMBS or structured credit. it. We're also seeing it with our utility and power issuers. And, you know, 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, you know, 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 things, Christian, just as we think about the economics of that and how that rolls into the business. In general, 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 bursts, there are a number of other major drivers of funding around the world that are supporting our business.

Christian, Analyst — Adage

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

Robert Scott Fauber, CEO

So I've made some progress because Christian just described private credit as a tailwind. And three years ago, when I would do these investor meetings, this was the number one 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 on 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 looks it'll look different in the private markets than public markets but but there are needs for investors to have a better understanding of the credit profile of what they're investing in. And, you know, we have a very extensive relationship with the big private credit players. And, you know, we talk about, you know, 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 credit. That is our job. to help investors understand credit risk, whether it's public or private. And shame on us if we were slow on 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 trillion dollar 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, 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

Christian, Analyst — Adage

and ratings, particularly around products and middle market credit rating? We've heard some of the smaller agencies be public about just attacking that space. So maybe over the next couple of years, are there particular areas where you're monitoring share dynamics?

Robert Scott Fauber, CEO

Yeah. So after the financial crisis, the competitive landscape in structured finance ratings changed. And I think it changed permanently. It was a two and a half agency market, something like that. And it is now kind of a six 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 one other thing I would say, Christian, is, you know, 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, you know, for us, we'll 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 number one 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.

Christian, Analyst — Adage

Okay, good stuff. Let's go back to the top of the house firm-wide here and just think through margin and investment appetite. Clearly, you've done fairly well. margins have improved. But as you invest in AI, I'd imagine platform organization, you're boarding 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?

Robert Scott Fauber, CEO

So 53% margin. Rating agency in the high 60s. You know, I do get asked, you know, can it go higher, right? But we've done a pretty good job of driving operating leverage into this business. And, Christian, again, I continue to think about is 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 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 product, 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 lifecycle across our engineering teams are smaller in ratings, but we've done that. and then NMA. 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 four eyes. There's two 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 a quarter 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, you know, there's a lot of opportunity across the enterprise, I think.

Christian, Analyst — Adage

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

Robert Scott Fauber, CEO

Yeah, you know, those were two 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, you know, 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, you know, when looking at anything that looks like workflow or software, we're going to look very, very hard at whether there is actually a proprietary data asset embedded into that software. In some cases, there is, and 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, good stuff.

Christian, Analyst — Adage

All right, let's bring it all together and just think through the stock. Clearly, the stock has traded as a pretty healthy premium over peers for a very long time. Some of that, you know, compressed over the last year or so. You know, what's your compelling case to investors as to sort of why Mutishiro gained its premium valuation?

Robert Scott Fauber, CEO

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 five 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. There are enormous drivers for funding, and there is very little fiscal space in sovereign balance sheets. 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 is going to 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 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 get to the AI piece and um 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 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 Wong 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 has the best models? 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 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 one 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.

Christian, Analyst — Adage

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

Robert Scott Fauber, CEO

Thank you so much.