S&P Global Inc. (SPGI) Earnings Call Transcript & Summary

Okay. All right. Good morning to, I guess, everybody, thank you for being here. My name is Manav Patnaik, I cover business and information services for Barclays. We're very pleased to have with us today from S&P, Eric Aboaf who's the CFO. Thank you for being, Eric.

Eric, maybe just a place to start would be you've been now, I think, at the company about 1.5 years almost. So just talk about what you kind of -- what's kind of surprised you, both positive or negative in the 1.5 years? And perhaps what have you brought to the table differently?

Yes. I think I spent 20 years in banking in your corner of the world. And it's been really exciting to come to S&P. I've worked at -- worked with S&P as a partner, a supplier, vendor, whether it's around ratings, benchmarks, for asset management, market data, energy data is probably the one area that I spend less time on before coming. And what I found is much as I had expected, just a set of growth businesses focused on transparency, clarity, scenarios and what to make financial institution corporations and energy companies even more successful. And that's where I spend my time is where do we grow? Where can we accelerate? What's next? There's a great innovation engine, which I think is a little different than what you see in banks because banks have to be constrained by definition, and innovation is at the heart of what we do. And the areas I focus the most is around creating really transparency in MIS into our commercial activities, some of how we think about pipeline, some how we think about sales and how we think about segments and targeting different segments, how we think about product offerings in one area that supports a different group of clients. Because as we become larger and larger, there's so much to bring to our clients, we have to do over time is measure and operate at scale and that requires a set of insights and over time, you can launch campaigns, you can roll out products more quickly. You can drive more productivity over time, so then we can deliver the margin expectations that our shareholders have that we have for ourselves while we reinvest in the business.

Got it. And like yourself, there's been a lot of new management across the company as well. So maybe just some insights into how that shapes up today and looking forward?

I think Martina and the team have brought a lot to the company over the last 2 years, really thinking about in the we've had a great run, 5, 10 years and really thinking about how do we drive the next round of growth, the creation of the Chief Commercial Officer organization where we cover 130 clients, which are the top 1/3 of our revenue base, is really a sea change for how we operate. And what we found is it's brought our product lines together at a level of sophistication in seniority, where now we're having discussions in the boardroom, with CEOs about the wide range of what they're facing out in the marketplace. You think about all the hyperscaler issuances, for example, you've got CEOs of enormous banks like yours thinking about what does that mean for underwriting hyperscaler issuance. We've got our ratings understanding and insights there. Some of that's in the public domain, some of it's in the private domain. What kind of market data do I need to really understand that, how do energy supply chains and electricity grids and so forth in different parts of the world play out. How do I want to underwrite electricity prices, which are inherent portions of data centers, which support those hyperscalers and those AI companies. So there's wide range of activities that I think Martina has really thought about how do we bring together to our clients that they can really value. And that's really an opportunity, one that we think is unique to us because without the fortitude and the depth in each of those areas, right, we wouldn't be in the C-suite, right? We'd be working with the CEOs of divisions or COOs of various divisions, but that client connectivity really is an opportunity. And what we find is that the stature, the sophistication, the trust that they have in S&P Global is just second to none.

Got it. Okay. Let's move on to, I guess, touch on the segments of the business. So maybe the first question together out of the way. I mean there was some market rumors about you potentially considering the Cap IQ business up for review. So just your comments on that? .

Well, there's always been speculation just about every industry, I've been in, probably you've been in. And as a matter of principle, we're just not going to comment on unwarranted rumors, just it's not helpful. I would say that right now, as we said, as late as our second quarter earnings, we're highly focused on growth in MI, right? We've had a very strong, I'd say, solid start to the year. Growth is up north of 6%, comfortably within our guidance of 5.5% to 7% for the year, and we feel comfortable in delivering on that. And I think importantly, we've also said, look, we'll selectively trim elements of that portfolio, but we talked about small, subscale product lines, which is the kind of thing we've done before. We've done it recently in the energy business, right, where we thought that kind of software layer wasn't as valuable because, in truth, we're really a data company. And what we're really doing is trying to find a share benchmarks on data to our business and our clients.

And some of those underperforming areas that you called out, any examples or which broader categories that would fall in? Or is it just on the software side, given the analogy to energy? .

It's actually not analogous to energy because the Market Intelligence Data business is really quite strong. As I said, growth of north of 6% top line, first half of the year and comfortably within our guide. Continued growth in platforms, including some big announcements we made in the second quarter around clients. Enterprise Solutions, which is not just software, it's really a system of record software solutions with a data component, that grew 10% year-over-year in the first 2 quarters of the year. So we're seeing real momentum there that's important. In the data space, we're growing at high single digits, low double digits, depending on which quarter we're looking at. We're signing up more clients for MCP Connector to 500, which is 50% more than the prior quarter. And data usage rates through API and LM call volume is up 5x, 5x Q1 to Q2, and it was 5x 4Q to 1Q, right? So think about the economic value that we're bringing to clients. And then just recently, we've continued the integration of S&P data into the that ChatGPT financial services workflows. And just last week, OpenAI released a study of those workflows and shared how error rates with the trusted, proprietary, branded S&P Global data are below 3%. Our nearest competitor was at just around 6.5% errors, right? And it's something that clients have been telling us over the year, which is that our data is particularly valuable. They trust in it because of its quality, they can ingest it and process it in ways that are, in many cases, better than our peers and brings immediate value. And so I think there's a lot to come over the coming quarters and years as we see AI developed interfaces for clients, develop either within their own organizations through new channels that they're ingesting data for. But that's going to be the heart of growth of the [ everything ]...

Yes. Just a few follow-ups on that. But before we get into that, you used the Mobility spin-off to resegment some of the numbers. So within MI, can you just remind us again what the new segmentation is? And kind of why did you bucket those in such a way?

MI is segmented in a pretty straightforward way. We've got the Kensho data and Platform product line, which is about 2/3 of MI, 1/3 of it is the Enterprise Solutions, which is that workflow software. And we did it that way because in Kensho data and Platforms we have is some unique platforms have been deeply embedded in client workflow. So think about the client franchise that we have there is exceedingly deep and broad at the same time. And Kensho over the years has brought a set of data and MCP connectivity and so forth to that client base. And what we want to do is accelerate that, right? Because we're happy for clients to connect to us through our proprietary platform, but also every other platform that exists out there. And we want to be on the forefront of any evolution that's playing out. While we modernize and improve and so forth, our own platforms. And then there's Enterprise Solutions, which is a great. And it's not just a software business, right? It's a system of record software business, which is critical to workflows for loan syndications, loan trading, private markets activity with iLEVEL, as an example, and creates an area, right, for clients not only to operate their businesses, but to record their data, ingest our data and unique data that we [ pool ] across clients and creates real value and real growth for us.

Got it. In terms of the -- so the segmentation, I think makes sense, help us -- I think you have different leaders for each segment, like I think you had Bhavesh in Kensho data and et cetera. So why separate leadership? Or is it just -- are we still talking to each other a lot I suppose.

They're definitely talking avidly. What we have is we have integrated multiproduct sales force, right, that has to -- that is really from a go-to-market standpoint, holistic in how it approaches financials, corporates, even Energy clients within MI. But the product set has some uniqueness. And so you want to create innovation and feature functionality and even new products within that product. So and that's why you've got that line up and we, from an internal standpoint, look at our business from a client lens, client segments, right, the CCO clients and then all the other groupings of clients of midsize and small clients we look at a product lens, and we look at a regional lens, right? And there are a couple of others, but let me just stick to those 3. And that lets us find opportunities. It's spot execution successes in areas of further opportunity and a good way for us to run the business.

Got it. Moving on to the AI aspect of things you talk about, 500 MCP Connectors now, the OpenAI part, et cetera. Impressive numbers, good growth. Can you just help us appreciate the monetization model? Like how is that going to convert into revenues and what the kind of the pluses and minuses of that?

For us, AI is an accelerant, right? Monetization will come over time. And what we want to do is be there for our clients as they're expanding and experimenting. We talked about how some of the client discussions are even taking a little longer, why? Because we're talking with them about not only our value-based pricing, but also experimenting with some volumetric pricing, right? And clients on the other hand, are thinking themselves, wow, even more of this data from S&P Global, I trust it. It's branded, it's reliable. It's got a ceratin that is unique. And they want to make sure that they can get as much of that as possible for a reasonable price as well. And so there's just -- I think there is a development of an economic model or maybe a, I'll say, we have an economic model around value pricing, which is around what clients use and how much they use and how many people use and what products they're engaged in that's pretty sophisticated. And I think over time, that will evolve probably a little more towards usage, but that transition will come over time because clients first need to actually experiment, they experience it, and you've read about how folks are monitoring token usage and so forth. That's within their own environment. Typically, we provide the product, the data sets behind that for clients and as clients work through that evolution, but want us to be fair with them and that will come with time. I think for now, we're extremely willing to encourage, right, and help them take full advantage with our data so long as they do it on our terms, right? Our terms are our data is proprietary, it's behind our paywall. It's not to be used for training, right? It's quite unique in ways and we'll maintain that. And at the same time, of all the economic models that makes sense.

Got it. One of the concerns, I think with the MCP and the AI connections is that customers might use it a la carte or whatever you want to call it for MCP and that will come at the expense of your platform that they might have subscribed to. Are you seeing some of that trend? Or is that something the MCP pricing might take offset. Just curious your thoughts on the pluses and minuses there? .

I'm smiling because we're not seeing an either or, right we're actually seeing folks continue to re-up on some of our proprietary platforms and ask for even more data. Now the data business is growing much more quickly, right, which we're thrilled to have. And in truth, we're agnostic, right? We'd love to grow the data business, not just high single digits, but mid-double-digit teens. We'd like to accelerate it through the breadth of channels. Over time, that's our expectation of what's likely to happen. And if that means that some of the platform revenue is replaced with data revenue, that's great. If the platform revenue continues to grow, which is what it's doing today and we get data revenue on top of that, that's great as well. So there's a variety of different scenarios that we're that we're looking towards. But in every one of those, there's an economic foundation of where we are today. There's a trusted brand of where we are today. There's control of our data, right, including audit rights and protections that we're going to ensure we have, while we continue to serve our clients and see them grow with us.

Got it. You mentioned token costs. I think one of the things investors are trying to figure out also is who's controlling token costs and how. So maybe a 2-parter, like, specific to MI and then even just broadly stepping back for all of S&P, just some thoughts on what the token costs look like and how you control that. .

Yes. Let's maybe take it from the sort of client side, and then we'll talk a little bit about internally. Clients of S&P, whether they're MI clients or energy clients or what have you, are especially the largest clients are building their own environments for large language models within their ecosystem, right, with harnesses and layers and so on and so forth. And they're trading off one model for another and optimizing an open source and so on and so forth. And what they're doing is, we're connecting to them through our energy data sets or financial data sets or corporate data sets, right, and making sure they can access our data in a highly efficient manner and scaled manner. As they do that, right, it's quite natural for them, right, to incur the token cost because it's within their environment. For us, it's just -- we're just fulfilling data. And so primarily, it's a client question. We want to make sure that our data gets them in a highly efficient way in a highly effective way, so that they're not maxing out, right, of their own cost. And so that's the primary area where it comes to the 4. The other line area that is -- has some importance is we're building AI functionality within our products and our energy ecosystem, our MI ecosystem, some of our ratings data is deployed through that, configuring indices in our index business can be done by clients and the AI of drivers and feature functionality of those products, those tend to be on us, but they're much more. They're small scale in relation to just enormous amount of data pulling. And then finally, we're using internally on productivity opportunities, whether it's data operations, software development speed, whether it's research, right, that we provide. And there, you'd expect the CFO to do what he or she should be doing, which is just monitoring token costs and seeing who's using it and how much and then asking why. And if why has a good answer, great, let's do more of that because they are paybacks. And if why doesn't have such a hot answer, let's go and look again.

Got it. I'm sure the other thing we're focusing a lot on is all these productive initiatives are probably creating a margin opportunity. You guys already have pretty healthy margins. But how should we think about if we'll see some of that in the numbers? Or you put that all back into reinvestment? Just some thoughts there. .

I think you'll see -- I think we're -- you'll see continued margin expansion and reinvestment into our products, feature functionality, geographic growth and so forth. I think what we're finding with AI, it's just another in the long list of tools, right, that we can put to use in data operations where we now see a way to 20% reduction in costs across a $0.5 billion area. And now the discussion is with even the more advanced AI and AI quantitative models. Can we go after the next 5%, 10%, 15%, 20% in data operations, right? That's the discussion we're having right now as part of our budget cycle or '27, '28 and '29, as an example. How exactly we'll get there? We'll figure out over time. But our view is that at -- for a company of our scale, productivity matters, reinvestment matters, and we have continued confidence we can continue to deliver at the margin expansion of the 50 to 75 basis points across the company, and we've even said even higher in certain divisions.

Got it. And just on that comment, maybe just help reiterate kind of the divisional qualitative guidance you gave at Investor Day in terms of margins? Like where are the bigger opportunities? .

Yes. We said -- let me take it from 2 directions, right? We said that margin expansion will typically be 50 to 75 basis points for our divisions over time on average and so forth, right? They'll partly depend on the -- where we are in the revenue cycles, but we see that with confidence. We also said that MI just because it's a higher proportion of the expense base, right, we'll have -- we'll be typically at the upper end of that. And to be honest, if you look at the first half results, we had, what, 75 basis points or more growth in margins in Energy and Index. We had more than 100 basis points of growth in margin in MI, and we have more than 200 basis points so far growth in margin in Ratings. Now happy to make a year, but it just gives you a sense for the -- our ability to drive not only top line but also margin expansion, including in areas where we're seeing both acceleration of cycles as well as some other scenarios. So it's been a good year, and we'll continue to do that.