Right. Trust. Yeah. We're calibrating with the clients of the industry. It's interesting questions. We won't jump in there. Yeah. This is us. Hi, everybody. I'm Andrew Steinerman. Welcome to the Info Services Track of the Ultimate Service Investor Conference. If you get a chance, pull up an Information Services Data Book, which is our quarterly primer on the sector since 2013. This is Rob Fauber, the CEO of Moody's. We appreciate you coming back every year. Loving me. It's always a really good discussion. And don't worry, everybody. We will get to discussions about AI. I just thought we'd ask some questions beforehand. When you look at just this year in terms of issuance and ratings, revenues, your expectations were more modest at the beginning of the year and have been more robust as the year has gone forward. What's driven that kind of upside to issuance relative to initial expectations just this year? We adjusted downward after Liberation Day, as you remember. Then we have come back since then. I would say that a few things. We originally, at the beginning of the year, had a view about kind of M&A in the Trump administration. I think there was a little bit of a false start again with Liberation Day. As we have seen in the second half of the year, M&A has really picked up and a lot of strategic M&A. We are also looking at sponsor-backed M&A because there is a real flywheel effect that goes on in our business when we see sponsor-backed M&A. You have got M&A volumes picking up. You have got economic growth that, while has slowed a bit, not as much as people thought. It has actually been better than the market had thought. You've got default rates, which are slightly above long-term averages, but have generally been coming down, maybe a little slower than we thought. Spreads are really tight. They're at near multi-year lows. All of that's pretty conducive for issuance. The strongest issuance that we've seen this year has been in the corporate segment, both opportunistic investment grade. We see a lot of big infrastructure financing getting done, some of that getting done through corporates, and then leveraged finance, both high yield and leveraged loans. When you say M&A, usually the ratings and the issuance happens closer to the close, right? So M&A announcements this year should even help issuance even more so next year, right? Yeah, that's right. As we look into next year, we have a service called a rating assessment service. So we have companies that come to us and will understand what the rating profile may be in an M&A transaction. That pipeline is very strong at the moment. That's the same thing that we're hearing from bankers, that the M&A pipelines look quite good. As we're going to round into from Thanksgiving and into the end of the year, some of that deal flow is actually going to also get announced in the beginning of the year. As you say, then get financed subsequent to that. Talk about the four deep currents. These are something you've been talking about for a while. Are they coming to fruition in terms of revenue growth the way you would expect them? Yeah. So it was interesting. During COVID, or right after COVID, and we were a beneficiary of COVID. We were a COVID stock, right, with ultra low interest rates. There was a lot of fretting from investors who said, "Oh my gosh, interest rates aren't close to zero. It's going to be terrible for your business." Obviously, there was an adjustment period in 2022. We ripped the Band-Aid off and rates moved up. I would argue that we're in a much better environment for debt issuance over the medium term than we were then, right? Then it was a monetary bubble. Now we look at what is going to drive financing volumes. The first one is there's just a massive amount of debt that's been issued over the last five years. That debt's got to get refinanced. We've published these. We call them our refinancing walls. Those look quite good, especially for speculative-grade debt. That kind of underpins issuance. The deep currents that we talk about, private credit and assets coming off of bank balance sheets and going into investor markets, capital markets, that securitization, that's a positive for us because we're providing credit assessment in many cases. Infrastructure, I've seen a BlackRock report that says something like $68 billion of infrastructure financing needed by 2040. Of course, AI, it's all in the news. These massive AI data center and infrastructure investments also driving that. We're seeing that. I'd say in the earlier days, that's rolling through the ratings business now, Andrew. I would say earlier in its maturity is digital finance. We do feel that that is an inexorable trend and transition finance. I think maybe a little bit of that slowed down a little bit. When you look at companies that are going to be decarbonizing and evolving their business models, and what we're going to do with energy grids and all of that, there's still a lot of financing that's going to get done for transition finance. That is still out in front of us. Okay. That's great. Okay. When you look at the categories, you just mentioned a moment ago that spec rate looks good. But when I look over the Moody's categories of issuance projections, both structured finance and the public category was actually tapered in terms of MIS rating issuance outlook. Why is that? Is this an important thing to watch? Obviously, leveraged loans and high-yield bonds are more important. Should I be watching these other tails? Look, there are always ebbs and flows within the different asset classes. That is one of the great things about the business is sometimes when we see we will see issuance slow down in one area and we will see it pick up in another, whether it is a region or an asset class. In this case, Andrew, you are right. Corporate has been very strong for the reasons I talked about. In a couple of parts of structured finance, primarily around consumer finance, we have seen a little bit slower growth than we had thought in the beginning of the year. That is not particularly surprising because I think there are elements of a two-speed economy in the United States. There is the AI economy, and then there is kind of everybody else. We have seen a little bit of stress, in fact, as we move down the socioeconomic spectrum, right, with subprime autos and undocumented populations. You see a little bit of that in parts of our structured business as it relates to project and infrastructure finances. It's an interesting question, right? Hey, if there's all this infrastructure funding, why did you, again, modestly trim our outlook for the year? Yeah, that stuff is, it's interesting. Just take data centers for a moment. They're coming to us through all of the different lines of business within ratings. You have data center financing that's getting done in our corporate rating segment. I'd call that infrastructure, but that's in corporate. We see it in CMBS. We see it in REITs. It's rolling through different parts of the rating business. There's a little bit of a, I'd say, a quarterly downtick just in that particular line. Infrastructure is much broader than that across our rating lines. Okay. That's fine. When looking at the MA, organic revenue growth targets, the medium-term targets that you said earlier, high-s ingle digits to low- double digits, you kind of left that kind of low double digits there as kind of an ambition. What would it take to get there? Is that really a stretch, or is that kind of a key part of the range? We're not bringing forward any of our guidance estimates today. That's still certainly the medium-term targets in this particular case. I'd say a couple of things. One, this year, we've talked a little bit about a few of the, I have to be careful about this, the idiosyncratic things that we've experienced in terms of whether it was canceling a distribution agreement, whether it was, a little bit of the ESG runoff from when we did the MSCI partnership. I only caution that because we're in a very dynamic world, and there are always things that are happening. Those things did provide a headwind to growth. We had a little bit higher attrition in those particular areas for those reasons. I would just go back to kind of what is it going to take. I'd say, in particular, we're going to be investing where we see where we have the strongest Right to Win and the strongest growth tailwinds. Those are going to be in our banking segment. It's around lending. Right now, we feel very good about our lending suite. In fact, that's growing faster than the rest of Moody's Analytics. Underwriting, particularly building out in insurance and expanding from property into casualty and financial lines. That's another opportunity for us, cyber. KYC continues to be an important opportunity. Certainly now with AI, there's a really interesting opportunity between our data and agents and thinking about providing huge amounts of value to our customers that have very manual, people-based workflows. The last thing I'd say, Andrew, is kind of an agentic layer over top of our content estate. In general, I think of AI as a great opportunity for us. It must be a tremendous unlock when you have a massive, mostly proprietary data and analytics estate. I think this offers us at this moment in time so many more ways and channels for us to monetize that content. Okay. Maybe we should jump into AI as it just seems like the conversation's naturally migrating that way. I have this figure that I put together really was kind of worked from the research we did over the summer of who's most at risk, who's least at risk. The rating agencies are actually, in our opinions, kind of least at risk. Just start out with a big picture question about info services. There's been a sell-off broadly of info services stocks. It's not just Verisk, Moody's. It's everybody. We've sold off. There's a worry about AI. Of course, I've come to the conclusion there's companies more at risk and least at risk. Just start with the big picture point. Do you think this is a group, the whole group, that's going to net benefit from AI on average or be dislocated by AI? The whole group. Take it with a grain of salt to who it's coming from, right? I know. I firmly believe that this must, for the reason I just touched on, this has got to be a big opportunity for the owners of, I'm going to say, proprietary or heavily derived data and analytics. I'm happy to kind of dig into that, but. Please do. Okay. Why is that? We've talked about this a lot today. First of all, I think there are many more opportunities for us to monetize that content across new customer segments, new customer personas, and new use cases. In some ways, if you think about it, I'm going to think about a utility curve of our content. I'm going to give an example of our catastrophe models. We have these really sophisticated catastrophe models that the insurance industry uses to assess risk of extreme events. We've done an amazing job of monetizing those models at the very high end of the utility curve with catastrophe modelers through our catastrophe modeling software. Guess what? That IP is very, very valuable to personas and customers well beyond insurance companies. You're a bank and you want to understand the risk of a piece of real estate that you're taking as collateral. We have an opportunity to leverage that IP and to be able to provide that to a bank during their lending process. I can embed that into my software. I can pull that into an agent. In general, I just look at this and think, gosh, there are so many more ways to access our content. For me to think about who I'm serving, what use cases, and how I price along that utility curve, in many ways, I think I'm just getting started. The other thing I would say to this is, and this might sound a little trite, but more and more, we know there's enormous value to the data, right? All of a sudden, we've not all of a sudden. We know that our data is valuable in supply chain and supplier risk, for example, right? Now I know that I want to have my data and my content and my models where our customers are making decisions, whether that's in SAP or Salesforce or Coupa, any of those third-party platforms, whether it's in a bank's internal AI workflow orchestration layer, take my content with AI rights to it, take my specialized agents, or whether it's in our software and our web platforms with an AI interface or agentic layer over top. I don't care. There are many more ways for me to monetize that content for broader uses. Also thinking about, over time, different commercial models for that content. If a financial customer discovered Moody's data on a third-party LLM and wanted to subscribe to the data, would you charge them the same as an existing customer? They might not have the broad use cases that an existing customer has. I mean, it really depends. We're going to have a variety of different pricing models. I'll tell you. In that case, I think you're talking about a situational access to our content. What I'd like to do as I think of that example, Andrew, is somewhere lower on this utility curve, right? There, I've got to have the capability to be able to do essentially digital fulfillment, right, and enablement for that content at that moment of time. Historically, our company and many companies like us, we have products and we have field sales, right? What would happen in that particular scenario is, in theory, up to now, it would kick off, you'd have to call a salesperson. That's not a scalable model. We have built a platform layer underneath all of our application estate, starting with single sign-on and moving to metering and fulfillment to be able to understand what our customers are doing across our applications and how we can then start to think about a digital fulfillment model that will allow us to sell the content and monetize somewhere different on that utility curve. One other thing I would say about, you gave a bank example. Our content with the big banks is being consumed all over these institutions in different departments in different parts of the world. We will have many different contracts. There is a really interesting opportunity at this moment to uplevel the way that our content is consumed at these institutions. In many cases, like at JPMorgan and others, they are building out these AI workflow orchestration platforms. They might be at the enterprise level or more likely at the corporate investment bank level, the commercial bank, and to have us be able to get core parts of our risk operating system, as I like to call it, make that available to the AI and then be able to have that content consumed much more broadly across the institution to serve many more use cases. I am going to price behind that. Right. I just want to make sure that Moody's isn't going to lose its pricing power as it does more digital fulfillment for new customers. Yeah. Again, when you're talking about pricing power, we're going to price for the utility and the use case. I think that's going to be very important. You saw my risk continuum a little bit here. I put the ratings as rating agencies least at risk. If you were going to talk about MA, where on the risk continuum for AI do you feel like MA is? I know, obviously, MA is a mix of businesses. It is. If you think about our content estate, the largest part of the content in Moody's Analytics is the exhaust from the rating agency. It is the research and the data. It is all proprietary. We are creating it. On average, we are issuing a rating every 20 minutes, 24 hours a day, seven days a week. It is all proprietary. You can only get it from Moody's. We then have built out what I think of as one of the world's, I think it is the world's best commercial credit franchise. We have credit models, and we have a giant contributory proprietary credit default database contributed by banks that helps us to calibrate models for public companies and private companies. We have gone all the way down to credit workflow, right? We have loan origination, a lending suite. We have asset liability management software, portfolio analytics, all because we have such deep domain expertise and proprietary content in credit, right? That anchors our research business for the most part, anchors a lot of the banking business. I'm now going to move to insurance. I get asked questions about, you sell software. Our software, we're only in the software business as a delivery chassis for the content. Yes, we have something called the Intelligent Risk Platform, which has, I think, industrial strength cloud compute to run models for the insurance industry. Really, what the insurance industry is buying are the CAT models. I got asked earlier about, could AI just recreate the CAT models? It's much more than that. Our CAT models, first of all, are the currency of risk across the global insurance industry. It's how they manage and price risk. Our CAP models are then calibrated with claims data from the insurers. The insurers want and need these models to be accurate. They work with us to help us with the calibration of the models. An interesting example, the insurance industry wants to grow cyber insurance underwriting. We work together with the industry, biggest broker, biggest reinsurer, biggest insurers of cyber, to form a cyber industry working group where they contribute claims data and content to us to help build models and solutions for the industry to help the industry grow and write more cyber policies. That is how to maybe think about insurance. The last part, because I get asked this question a lot, and I think this is important, is around our massive company database, right? This powers a whole range of use cases across banks and insurers and corporations. We have the world's largest database on companies, 600 million, 2 billion ownership links. We have really rich data on politically exposed people and adverse news and all of that. We link it all together. The biggest use case for that is KYC. That is assembled through a relatively complex ecosystem of information providers. We have to have the rights to use the content. We have commercial arrangements with them. We then normalize and cleanse the data and make the data available. It is not as easy as you can just go out and scrape all this data. Is there data available on private companies that can be scraped? Yes, there is. Not what we are doing through these company bureaus where we curate an ecosystem of information providers where we have the rights to use the data. You're not going to believe that I don't know the answer to this question. My question is, you already have an incredible database of private companies in your credit research. Could you combine your BvD database with your credit research database, or do you have to keep those separate? If you were to go on to moodys.com today, you can type in any company that you want. Andrew, you're going to find rich information on companies, whether it's public or private. You may find model-derived ratings on private companies, right, where we're leveraging our credit models where we have financial statements on private companies. We say that the financial profile of this private company not rated is a BA1 model implied, right? Guess what? That gives us, that's also what we're bringing to the private credit opportunity. If I could just touch on that for just a second. Private credit is a super interesting opportunity when you have arguably the world's best commercial credit scoring franchise, right? It starts with ratings on public companies, but we have the ability to put a model-derived score with high fidelity and high confidence on virtually any company on the planet. Now, as it goes to smaller and smaller and less information, the range of confidence around that is wider. Gosh, you want to understand the credit profile of a private company? We can do that. And we've been doing it. Right. I think your answer was, if it's model-derived ratings, yes, we can combine it with our other database. If it's a rating that is by an issue where you can't combine it. The one thing we're going to do is make sure that if you're using our rating, you will know if it came from the rating agency or it was model-derived. Other than that, it's all going to be available to the same investor group. Because guess what? Our investors tell us all the time, "Hey, look, in my portfolio, I've got 90% public and 10% private. I need help on the private." We offer that. What do we do? When we layered in all of those hundreds of thousands of private companies, we went back to our CreditView customers and said, "Hey, are you interested in the private company package?" Right? There's an upsell. Just make sure I got the question right. There are some pieces that you can't combine together, right? We're not sharing information that we get from the rating agency with any other part of the institution. Yeah. Okay. Great. Let's open it up for questions for Rob. Go ahead. Maybe if you could expand on that MSCI partnership, I guess, where is that market at in terms of, is this being demanded by kind of the investor groups and the LPs, or is this something that build it and they will come? Maybe if you could just also expand on what exactly you guys are doing together as well. Yeah. It was interesting. I was on the road for most of the last two months. At the beginning of that trip, when I would sit down with various folks in the investment community, and I spent most of the time outside the United States, I would ask questions about, "How are you understanding the risk of your investments in private credit?" It was interesting. I would get, "Well, it's a higher yielding asset class, lower defaults. That's interesting." Towards the end of that trip, I started to have a very different level of interest and engagement. "Why are you asking? Tell me more." "Yes, I've been wondering more about the credit quality of my private credit funds." What we did with MSCI, they had a dataset. It's hard to get access to information on these companies. We have the credit models, and they had some data. We went together to their customers that are on one of their GPLP platforms and said, "Hey, if we could provide you a Moody's modeled credit rating." We take a probability of default and map it to a rating. "Would you be interested in understanding what the credit profile is of your investments in your private credit funds? Would that be interesting to you?" In many cases, we had very good feedback, and investors said, "Yeah, well, it would be interesting." We had to think about how much are they going to pay and what is that going to look like and all of that. It is not going to be a game changer from a financial standpoint, right? What's really interesting, I think, is that we're introducing the language of credit ratings and credit risk to these investors to help them have a third-party rigorous independent understanding of what the credit risk is in the funds they're invested in. To allow them to have a dialogue then with the GPs who are like, "Today, how do they understand the credit risk?" It's informed by the GP, right? They're telling the investors what the level of credit risk is. If you think about the way we built this business over decades, it was by building investor demand. The investors found the ratings useful. Once again, what I want to do is have the investor community in private credit start to use our ratings to say, "Hey, I need to know more. I want to ask why you guys have marked it like this and why Moody's has marked it like this. Help me understand this." Over time, you could imagine more and more of the GPs, because this is really about direct lending, right? More and more of the GPs saying, "Look, rather than having Moody's effectively providing a model-based score on our funds, why do not I just go to Moody's and have them provide an assessment with my engagement, whether I am Apollo, Blackstone, whoever it is, right?" That is the way our business works, is we have had issuers come to us. We look at this and think, "We have a very important role to play in the private credit market, just like we did in the public credit markets. We created the language of credit risk, and then we developed the scorecards and the data and the benchmarks and the research to help investors understand risk and scale the market. That is what private credit, when I talk to all of the big GPs, say, "Look, if you're going to go from $2 trillion to $10 trillion, you're going to need this." We can play a very important role here. Let me ask you a question about clients that you have that are very AI-forward. Do you find that they consume more data and content from Moody's? I also sort of an add-on question, are these forward-looking, forward-leaning AI clients more in the regulated industries? Like, is that who's moving quickly, or are they moving in a more measured way? The first part, we gave some interesting data about looking at the cohort of customers who take some form of AI solution from us from those who do not. This was back a quarter or so ago. We talked about it was like almost twice the growth rate of that cohort, meaning we are very engaged. Think of them as maybe early adopters. We have a different engagement model with the early adopters. To your point, Andrew, yeah, they are actually taking more things from us. We are engaging with them differently at different parts of the institution. That is what is particularly exciting. The second part of your question was around. Regulated versus not regulated. Regulated. It is interesting because it took the banks a while, right? They had to get through the risk governance and all that stuff. Every single big bank that we are talking to, we are actively engaged with them. It is actually, when we look at the growth of the tiers of our bank customers at the moment, the fastest growth is coming from the largest banks where we have where that engagement is really about the content and pulling the content into their environment. Ultimately, they're trying to measure risk better, right? That's right. Okay. Last questions for Rob? Go ahead. I don't want to read too much into the answer to the question about MSCI, but just curious, you mentioned this inflection point while you were on the road where you were seeing more interest. Is that just an organic conversation that evolved between LPs and GPs, or is there potentially some sense that these actors are concerned about greater scrutiny post first brands and if there's not some type of self-regulation? I am specifically referring here to investors, right? Investors who are just saying, "Hey, look, I've," and it may be insurance companies. "I've invested a lot in private credit. I'm watching what's going on in the market. By the way, I, the investor, am now getting questions about the investments I've made in private credit and how do I understand the credit profile of what I've invested in." That is a place where Moody's has a great opportunity to help those investors by saying, "Hey, we can give you a third-party independent battle-tested view of credit risk. We've been doing it for 115 years." I mentioned that there's more in the news. There's more interest from investors because of what's going on in the news and the awareness now of we're not at maybe the market felt frothier over the summer, and now it feels like I think people are starting to focus more on credit risk. That's always good for our business. Okay. Rob, I think that's the time for us to. Sounds like it. Thank you very much. Thank you. Thank you.