of Moody's Investors Service. Format for this is gonna be a fireside chat. With that, welcome. Thanks for joining us. Mike, despite massive volatility in pockets of the equities market, credit conditions remain quite benign with spreads near historically tight levels. Maybe the events the last few days have widened them a little bit, but still, relative to where they've been historically, it's a very tight market. When you were here last year, your expectation at the time was for spreads to normalize in 2025 back towards their historical 400 basis point spread relative to the reference rate. Today I'm wondering whether it's gonna take a legitimate credit recession to cause that normalization and what are your current thoughts on that topic?
Okay. Well, first of all, thank you for inviting me. Thank you for everyone joining. When it comes to credit spreads, as many of you know, very complex inputs going into this, whether it's economic market liquidity or others. When I was here last year, our default study was expecting that we would go back to about 400. In fact, I looked and it, and it tipped over about 300 but then came back. It is still our assumption that it will still gravitate towards that number, the four, the 450, even up to 500. I did just take a look at this moment. Spreads are still hovering around about 300 despite what's happening out there in the world today.
I think your response segues well into my next question, which are what are the puts and the takes in the form you've recently issued, or recently announced issuance expectations in 2026, including your spread expectations then?
First of all, I just want to do a quick clarification on the earnings call. Rob Fauber, our CEO, outlined that revenue would be on a calendarized basis about 25% for the first quarter. Not to be interpreted that revenues would grow by 25%. I just wanted to clarify that because there was some uncertainty out there in the market. When it comes to the upside this year, obviously keeping a very, very close eye on spreads in the short term and in fact, how that is feeding into current issuance. Far this year, they've still been relatively tight. What that allows for is this opportunistic financing coming into the market. We have substantial numbers in the refinancing, but the opportunistic refinancing comes over and above that.
This year, we're also expecting about a 25% increase in M&A activity. That's announced M&A. A portion of that will be debt. It's been relatively subdued over the last years, particularly in the private equity space. We've also factored in more specifically, an increase in debt associated with the investments going into data centers, power generation, and supply. The overall sentiment around the economy, notwithstanding what's happening out there today, and also particularly for the U.S. issuance that is supported by the pro-growth agenda by the current administration and deregulation, particularly as it relates to the banking sector. On the flip side, when you think about the downside scenario, one would be a prolonged geopolitical conflict that would reduce investor confidence. I think that's been tested at this moment.
Ultimately, depending on what happens to energy prices with a prolonged expectation of inflation, particularly as it relates to oil and gas, that may pause authorities around the world with regard to easing of rates that were still expected for this year. On top of that, you may see in any one of the sectors credit events that may throw the market to a risk-off environment. If that risk-off is a few days, that is materially different from if that's something that's prolonged going into a matter of weeks that would increase volatility, increase spreads on that. That would again feed in to concerns about the health of the broader economy and potential deteriorating trade and other dynamics.
You, you touched on inflation and the implications on the long end of the yield curve. If rates were to move meaningfully lower from here, could that be a positive catalyst? I guess on the other side, if inflation appears to pick back up, like how significant of a, of a headwind could that be?
Yeah. When we look at the duration of rates, and at the moment what you have is an elevated rate scenario towards the longer dated. If that starts to come back in, and if I recall back in COVID times that the back end of the curve started to come in substantially, what that allows for is longer dated paper being issued into the market and allows for certain assets to be funded at a longer duration. When you think about infrastructure, you think about energy, you think about real estate, and importantly at the moment about data centers, there's an opportunity to tap that longer dated paper. It will also depend on the nature of the assets that need to be financed.
Often, certain assets just need short-term, whether it's securitization, you just need to back that until it's paid off. It really is a matter of what assets are out there and the pool of assets that need to be financed. That's why it's important when we look at our first time mandates, we're expecting around about 750-800 new mandates this year, and the nature of those, whether they're long-dated and whether there's access. We did see that during COVID and normal corporates like Moody's actually issued a 40-year bond during that period. It doesn't always have to be those long-dated assets.
I promise I'm gonna touch on AI, but before I do that, question on your pricing power and just the broader competitive dynamics. How do you view the durability of your pricing power, and do you ever get pushback from clients?
I mean, first of all, we are constantly in discussion with our customers with regard to the value that we bring. I don't know if people are familiar with this slide. This is a, a perennial in the investor relations deck, but we've just updated this.
It's posted on the IR website, so you don't need to.
Yeah, this is on the IR website. It's just gone up there. When we think about the value of a Moody's rating, it is really saying to the market, do you get a better pricing with a Moody's rating than a bond that goes to market without a Moody's rating? That could be with other agencies or no rating at all. What we are indicating here, this has been done by an independent firm, is that on an adjusted option-adjusted spread basis that with a Moody's rating you are saving about 22% in terms of your overall coupon.
If you actually translate that into dollars, and this is a $1.5 billion, 5-year term, you can see the difference and what that translates into, which is a substantial amount of dollar savings for the issuer. As long as those dynamics remain, then the pricing power of a Moody's rating and the basis points that we charge folds into that. That make sense?
Yep. Terrific. Artificial intelligence, obviously a big topic at the conference this year. What are the implications of AI for Moody's Investors Service , starting with the revenue opportunities?
Yeah. I mean, first of all, when we think about the revenue opportunity, what do we do? We rate bonds. We rate bonds of and instruments of major players that are issuing in the market. We have estimated in a recent paper that there will be approximately $3 trillion of investment going into data centers and to the related power associated with that. A good portion of that amount will be debt and unrated. When you think about the sizable requirements of that sector, that does not include the amount of debt that is being now issued by the hyperscalers. In a number of cases, we're seeing CapEx at multiples of historical levels. Again, those are rated entities and those are issuing debt to support that CapEx.
That all feeds into that revenue and that upside that I talked about on one of the earlier questions.
To the topic of data center build-outs and hyperscaler build-outs. A lot of times, I think these are big chunky bond issuances. How do we think about how those issuances scale for Moody's in terms of the revenue? Is issuance volume gonna grow faster than issuance revenue? Even if it were to happen, I suppose it's a good problem to have.
When you think about the nature of a frequent issuer, and as we're seeing a number of these hyperscalers are starting to issue very large sums on a frequent basis, what we will do is engage with the finance teams at these companies to understand their profile of issuance over the next three to five years. If that profile moves that they will become a substantial and frequent issuer, then we may shift our pricing scenario to accommodate that. However, if there's a short-term boost in the next one to two years, and then they are not issuing the same amounts in the outer years, then it may make more sense to stay on more transactional pricing.
we will follow these individual companies, we'll talk to them on an individual basis, and we will make sure that that pricing arrangement meets their needs going forward.
How is MIS using AI to drive operational efficiencies?
Yeah. One of the key things to first of all think about is that, I said, I think I said this last year, that we have been on a multi-year investment in our technology stack and our data stack. We sit on substantial amount of data. When AI, in particular agentic, is available, which has happened in the last 12 - 18 months, it gives us a significant boost to the efficiency of what we do. When you think about what do we do? We process first and foremost a substantial amount of debt ratings.
We rate approximately $6.6 trillion a year, and that is processed through regulatory requirements, and therefore you can use AI and agentic in particular to help you with all that processing that helps you streamline the teams and the focus of the teams. When it comes to the analytical teams that we are bringing in vast amounts of data and the use of agentic tools to gather, to parse, and to put into these datasets, both on a, again, on a structured data, whether that's spreads or on unstructured data that you're pulling, that you can use these tools to our advantage to extend the opinions and insights that we have.
What that allows our analytical teams is to get to that credit analysis point much earlier and therefore time save with regard to the focus and the prep. Both operationally and analytically, we are benefiting from AI.
I think building on that, your MIS segment had incremental margins that were north of 100% last year. I think some of that was due to bonus accrual timing, has AI structurally changed the incremental margin profile of the business?
I would say that where we are at the moment is that it's probably too early to state that we've got a structural change. What we are gaining is incremental leverage, being able to accommodate more volume through the business. If you even think about the refinancing study prior to the pandemic, the refinancing amounts were about $2.8 trillion-$2.9 trillion. When you look at the study, that's north of $5 trillion. We're able to process much of this on a more moderated increase in our resources because of the efficiencies and the way that we operate inside the company. It's very early to call, is it a structural change? What we're seeing is that we're increasingly able to be volume, what I like to call volume agnostic.
As the volumes go up, that we're able to hold much more steady on our cost base.
Are there any regulatory constraints on how you deploy AI within MIS?
When you, I mean, first of all, we are a heavily regulated business around the world and many jurisdictions have particular requirements of what you can and cannot do in the ratings process. We try to level that out in order to provide a global service. What we do is constantly talk to each of our regulators to keep them updated as we are implementing our AI and an agentic strategy. A number of the jurisdictions require that there is human judgment in the decision-making inside the company, and more importantly, that we are often dealing with significantly complex transactions, private contract transactions with heavy documentation that does still require a very human involvement.
Going back to my earlier comment that what we also talk to our regulators about is that we can get to the starting point of our analysis much faster and in a controlled manner by using agentic tools and broader AI. That is something that is seen as acceptable as we invest further, and we will keep them on that journey with us as we continue to implement and get those efficiencies, but also the controls. That's what many of our regulators are focused on. Are we safely playing in the broader financial ecosystem and are we controlled in the manner that which we produce ratings? We believe we can prove that too.
Structured finance question for you. last year at a different conference, your CEO, Rob Fauber, mentioned that sometimes Moody's methodology in structured finance can lead to issuance moving away from you. Obviously, one of the big outcomes of the financial crisis was a clear separation between the business side of things and the rating side of things.
Mm-hmm.
What sort of levers can you pull running that business to try to grow market share in structured finance while still also kind of remaining true to your guiding principles?
Yeah. I mean, the backbone of running a rating agency is front and center you must get the rating right, because this is all about the trust that people have in the market. The challenge that you have in terms of the business versus the analytics is that you are driving to get the rating right and the cost of that opinion may be that the issuer of that transaction does not like that opinion and will decline to publish that in the market. That is something that we have to live with because at the backbone of what we need to do, we need to get that rating right. We have methodologies that cover all of the asset classes.
It all depends on the structure of a particular transaction and the layering in that, whether in fact they want to go with a Moody's rating. The other thing about our structured finance business is that we are continually investing in the innovation. Many of you may have seen that Moody's was the only rating agency on the inaugural CLO from the World Bank, and that CLO was backed by emerging market loans, a very first of its kind. Similarly, when it comes into new asset classes, whether it's ABS for data centers that we recently just published the first Aaa rating on a structure for that.
You have to distinguish between certain run and flow transactions where we may have a different opinion to others, and then the innovation and the front, end of that innovation where we play very heavily.
Staying on the theme of competition and turning to the private credit space. Obviously, there's multiple components to private credit. It's not just one single thing. Broadly speaking, how would you evaluate Moody's competitive positioning in the private credits markets as opposed to the public credit space?
Yeah. Get lots of questions on this one. I mean, first and foremost, credit is credit, whether it's in the public market, whether it's in the bank market, or whether it's in the private space. When it comes to methodological rigor, we use the same methodologies, whether it's in the private space or in the public space. We continue, again, to compete on the standards in that market. As the private credit market continues to mature, then the need for even greater transparency, the need for even greater rigor lends itself to coming to a player like Moody's that can offer a full service across fund finance, across asset-backed, across infrastructure, and into the insurance and the large players that are buying that. We feel we're in a very good position.
As this market gets increased scrutiny, and if there is any, market, turmoil that raises that scrutiny, then that's where we can offer our services, as a major player in this space.
Following up on that, a comment was made in your last earnings call that, you guys have seen about 70% year-over-year growth in the number of MIS private credit-related deals. Can you give us some color on the sorts of mandates that Moody's is winning? Are these wins a function of Moody's gaining market share within private credit, or just there's more ratings in general in the private credit space?
Yeah. Well, first of all, the private credit market continues to grow, it also continues to grow not only in volume, but also in complexity. Again, this is why many of the players, as they continue to mature in their role and they want greater transparency, that they want to come back and deal with someone like Moody's. When you think about the nature of transactions, there is fund finance, which is often at the very front end, and you're dealing with transactions like subscription lines where pooling of funds to be deployed to transactions. There's ratings at the front end. There is also money that is coming from insurers, we often have a relationship with the insurers.
That money gets applied, and it can get applied into structured finance, it can get applied into infrastructure finance, broader asset-backed finance. That's where additional transactional ratings are required because if some of those transactions need to go back onto a balance sheet of an insurer, then there's a requirement to gain capital relief that you need a rating from an NRSRO. As there, again, is greater review and transparency required that many of those insurers are wanting to evidence Moody's. We're seeing the front end, we're seeing the insurance end, and we're seeing all the transactions that come through on the deployment of funds, and that could be short end, investment grade, structured type transactions, or it could be very long-dated infrastructure paper, whether it's in data centers or others.
We're seeing it across the board.
Very helpful. I certainly wanted to take advantage of Mike's presence here today to ask a lot of questions about the ratings side of things. I think it would be remiss if I didn't ask any questions about the AI threat and opportunity as it pertains to Moody's Analytics. Kira, there's so much fear of the unknown as it pertains to AI right now. Can you speak to what gives Moody's confidence in the competitive moat around Moody's Analytics and why LLMs won't be the drawbridge for competitors to cross that moat?
Sure. Thank you so much for the question. You know, I think as AI becomes the interface for decision-making, you know, it's not just that we're supplying data to these AI models. We're embedding the trusted context in the analytics, in the data, and in the judgment, and we're where customers are actually making these decisions. You know, broadly, we service very regulated customers where we've heard from them that good enough is just really not good enough.
Maybe a few things just to think about as you're thinking about our competitive moat, you know, around the data, the context layer that Rob talked about and where, you know, how and where work gets done. First, as you all know, we have a very massive proprietary data estate that we've been building over quite a number of years. It's not just the data, but it's the process of taking all of that underlying data and models, the ratings, the research, the credit assessments, and putting that around a single normalized record for each entity. What this enables is that we can have a comprehensive, interconnected view of that entity which supports, you know, agentic and automation.
When it comes to the context layer that we talked about on our most recent earnings call, this is the layer that sits between the raw data and the AI reasoning agent. This is what makes the data usable for reasoning. It's, you know, it has to be structured. It has to be governed. It's what the data actually means. When you think about how that relates to entities, time, different scenarios, this is when and how this data should be used in those particular scenarios. If you take Orbis, for example, it's not just the company data. It's the years of the entity resolution that we have there. It's the ownership mapping, and it's the expert judgment that's been applied to that.
Then, of course, we have a very complex network and ecosystem of the IP rights and the licenses to be able to use that data. This is the context that goes into our analytics and our methodologies, and as Rob called it, makes this data decision-grade. Lastly, you know, as we've talked about a bit more on the most recent calls, we're embedding ourselves into where the work gets done. Whether that's into a customer's own internal system, their workflows, their increasingly internal different AI environments that they may use or third-party interfaces, as AI accelerates, we actually think that Moody's is needed more, not less.
Maybe to follow up on that point. You know, Moody's is embedding AI within your products and your services and starting to monetize those efforts. What are a couple of highlights that you guys are pretty excited about right now?
Yeah. I think that two that I would sort of point you to is when you look at the growth that we had in Q4, the strongest growth that we had actually came from our most strategic customers. When you look at that over the year, those customers actually grew at twice the rate of the MA customer base overall, and have, you know, increasingly become very sticky and durable customers for us and recurring revenue streams. The second thing is we've talked about a cohort of AI customers at big institutions, and that's actually what's driving the growth. We've seen those customers grow again that have upgraded or upgraded to a standalone or upgraded to an AI version of our product. Those customers have also grown at twice the rate.
We see that as a very good proof point and a leading indicator of what's to come.
Perfect. Then maybe a good place to end the conversation. What are some of the key messages that you wanna make sure people walk away with today?
Yeah. Well, I'll leave with two punchy, final comments, which, you know, first of all, we believe that Moody's is a durable and compounding business with very solid positions, both in the ratings side and on the analytics side. Secondly, as AI becomes more central on how financial decisions are made, our differentiated position is with regard to what Kira just mentioned, this decision-grade data and where we play in the financial ecosystem and what our customers need from a player like Moody's. As those capabilities are embedded in everything that we do, then we continue to compound and be an AI winner in this space.
Terrific. Well, I think that's a great place to wrap up. Thank you, everybody, for joining us.
Yeah. Thank you, everybody. Thank you for your interest. Thank you.