Good morning, everyone. I'm excited to welcome you to today's discussion about our private asset business. I'm Jeremy Ulan, Head of Investor Relations and Treasurer here. Before we jump in, I just want to read our usual disclaimer. Today's discussion may contain forward-looking statements. These statements are based on current expectations, involve risks and uncertainties, and our actual results may differ materially from what we discuss. Please review our filings with the SEC for more details. Also, you'll see on the website that we posted a presentation. It is not something we're going to walk through, but it is supplemental, and you can review it at your own pace. Jumping in here, I'm pleased to be joined today by Luke Flemmer, our Head of Private Assets, as well as Alex Kramm from UBS, who I think everyone knows. He will help us moderate the discussion today. Let me now pass the microphone to Alex. The virtual microphone, I guess. All right. Thanks for having me, everyone. Luke, thanks for doing this. Maybe just given that a lot of people probably don't know you that well, have met you, why don't we just start there? You joined MSCI 18 months ago, but you've had an interesting career before that. Can you just give us some more detail about you, your background, and why you were excited to join MSCI in that particular role that you have now? Yeah, absolutely. I'm great to be here, Alex. Thanks for your time today. My background has always been around fintech and data. I co-founded a firm in the early 2000s called Lab49, which was a technology consultancy, really working a lot on electronification of Wall Street. Worked on a lot of fixed income systems and really had a ringside seat to the transition of fixed income from being a voice-brokered, white shoe business to being super low latency, central order book world that we know today. Got to experience a lot of technological and data change in the 2000s. Sold that business in 2015. I worked at the ION Group, for a few years post that acquisition, working in capital markets, data and software. I went to Goldman Sachs, and I got offered a very interesting role at Goldman to run digital strategy for the alternatives business. Goldman was really focused at that point on consolidating their private asset businesses, moving them off balance sheet, and really creating a third-party, multi-strategy manager within that platform, which they've done a terrific job of. I spent about four years at Goldman working on the target operating model design and digital infrastructure of how to do fundraising, investing, and portfolio management at scale. Learned a lot there. Was approached by MSCI and was very excited to come into this role. I was excited to be back running P&L again. I've known MSCI for a long time. I think it's a terrific company, to be on an entrepreneurial platform, building data and tech for alts at global scale just seemed like a terrific opportunity. All right, fantastic. Thanks for that background. I think there's going to be a lot to unpack here over the next 35, 45 minutes. The way I want to do this, as we talk about the Private Assets business, I want to start the discussion with the current state of your business, then maybe talk about the big picture strategy for a little bit, get into some specific opportunities, and of course, AI, then maybe close with the long-term growth outlook of the company. Let's just jump in here with the current business. The Real Assets business is the larger part of the Private Assets business, of the two parts. We'll talk about the other one next. Can you maybe just remind us what the biggest offerings are in that business today, why growth has maybe been a little bit slower, and what really needs to happen for that acceleration to come here again? The real asset business was MSCI's original foray into private markets. We got into real assets 15 years ago at this point, and we've had a strong and growing franchise in there, global franchise in there, for several years. The core offerings that we provide there, we really help investors understand fully real asset portfolios. We help them understand the drivers of performance. We have a very rich set of global benchmarks in various markets that are well-adopted. We also help them understand the dynamics of transactions, but from a debt and equity perspective. We really try to give both managers, which are originating risk and managing risk, and the asset owners that are clients of that, a fulsome understanding of the dynamics of that business. In terms of the recent market dynamics, the industry has definitely been in a little bit of a secular slump. That coupled with the significant rate increases in 2022, that was somewhat adverse to core real estate. That coupled with the COVID dislocation in a lot of CBDs, has really taken a while to work through. It's quite interesting, though, and I think this actually legs into where we see a lot of opportunity, which is the nature of the vehicles and the investment opportunities is actually shifting in the real assets business. The traditional core plus vehicles have been somewhat in retrenchment as a function of those drivers that I talked about. What we're seeing is a lot of growth in opportunistic and value add, because there's a tremendous amount of real estate, commercial real estate in particular, which is being repurposed, transitioned from commercial to residential, redesigned, et cetera. There's a lot of opportunistic capital that's moving into those assets, the traditional shape of our business that was heavily core plus focused is shifting, we see the forward growth areas in opportunistic and value add, and I can talk about some of the offerings that we've brought to market there. Also crucially, we see infrastructure as a very significant growth area, which we consider part of the real assets business. We'll definitely get into that in a bit. Similar question on the PCS business first, which is the Private Capital Solutions, which is growing faster and I think people are more excited about. The business came to MSCI clearly through the Burgiss acquisition in 2023, but you've also made a few acquisitions here, this year actually, recently. Again, similar question, what are the biggest offerings today? When I think about the 16% growth that you just had in the recent quarter, is that still mostly driven by the core offerings that came with Burgiss, or are they actually new initiatives that are also contributing already? Great question. Couple comments on that. Burgiss was a terrific acquisition for us. It's a fascinating business. Obviously, it has a multi-decade lineage of data, right? Burgiss was in the business of collecting private assets data really before anyone, and collecting it at scale. That gives us really an unreplicable data set, and we leverage that heavily to do a lot of the work we do around pricing and modeling, and we'll talk about some of the things where we're innovating there in a minute. That data set is a really unique asset that unlocks a lot of potential for us. Within the Burgiss business, there were really sort of two key capabilities that we're doubling down on. I would say we're very much strengthening the base of the franchise, and that's accelerating growth. We're layering enhanced capabilities, new products on top of that are expanding it. They're broadly aligned with the core shape of the business. What I mean by that is Burgiss really was in the business of doing two complementary things. Thing number one was a data management service. Making sense of all of the plethora of manager reporting, all of the unstructured data flowing in. I think at last count, we processed 3 or 4 million documents a year on the platform from about 7,000 different managers. It's really a scaled operation. We'll talk about AI a little later. Obviously, AI is a huge accelerant for us in the platform. That data ingestion, data management, data structuring service is fundamental. The second component is really the portfolio analytics, portfolio management of that private asset portfolio. Where we've really enhanced both of those offerings, on the data side, we've launched self-service data products, so that this competes with a number of the newer sort of AI-native vendors in the space, and we have some very compelling capabilities there. We've also expanded our capabilities in pre-trade and diligence, which are all driven off the same data platform. On the portfolio management side, we've really been leaning into total portfolio management, and we see that as a key strategy for the business. Burgiss had acquired actually a business called Caissa. It came as part of Burgiss, which is a very, very strong product, and we've made a significant investment in that product. It's now called Total Plan Manager, and it forms really a key dimension of our go-to-market for our entire asset owner community. We're really innovating in that space of total portfolio, i.e., how do I have a deep and comprehensive understanding of my private assets and their characteristics, but also in the context of the total portfolio, my public equity, public fixed income exposure. That's where we're really building on MSCI DNA to bring that whole story together. Definitely the core is solid and growing, but there's a lot of innovation that we're driving off it. Excellent. Thank you. All right, jumping into the bigger strategy. You've described the real opportunity at MSCI as not just bringing order to the private markets in isolation, but actually, I think you just touched upon this a little bit, unifying the total portfolio. Giving investors a single view across public, private assets, strategies, geographies, et cetera. Why is this still such a big problem in 2026, and what is MSCI doing to really solve that problem? Yeah, absolutely. I mean, the view that we sort of espouse in the private assets is it's an asset class that's really grown in some ways a little faster than the infrastructure that underpins it. It's become a very material allocation in institutional investors. In some cases, it's 20%-30%, very material. Increasingly, there is really a public policy in the U.S., in Europe, even in Asia, where they're encouraging wealth flows into the asset class, right? In the U.K., we have Mansion House rules. In the U.S., obviously, we're discussing 401(k) adoption of target funds, et cetera. This is a global phenomenon, right? We're going to see more and more capital flowing in from a broader range of investors. Our view is that the infrastructure is not really there to sustain that at scale. We need more systematic data extraction. We need taxonomy and classification. We need fit-for-purpose benchmarks, and we need a risk and performance framework that can stretch across that. Especially as you start to move into wealth exposure and individual investor exposure, you really can't get away from the total portfolio question because no fiduciary, no advisor can really recommend a material allocation to an asset class if they can't make sense of it in terms of a diversification cash portfolio. We think there are huge secular tailwinds behind total portfolio. Hmm. Maybe a follow-up question because it's the same theme of private and public convergence. You just mentioned some of these large LPs already have 20%-30% or so in private assets. Maybe just going a little more into detail, what does MSCI offer to those investors in terms of the unified view of the public and private that you just talked about? What really does the product suite look like for people if they're using MSCI for both private and public data? This is really where we've been driving a strong set of integrations between the private assets business, the business I look after, our traditional index franchise, our analytics franchise, BarraOne, RiskManager, et cetera, and our sustainability and climate franchise. We're really unifying a significant amount of our IP to serve these institutional asset owners. What we're looking to do for them is really provide a layer cake of capabilities, where the foundational capability is very rich data ingestion and data management and normalization. We do that, as I mentioned, on the private side, where we need to digitize a lot of unstructured data and make sense of it. We do it on the public side, where we have a very rich set of feeds that we bring in, both on the public fixed income equity and on the liquid alternatives on the hedge funds. We can really bring in the total portfolio from a data perspective. We'll talk maybe a little more of this. We put it on a common taxonomy and convention, so we can classify funds and fund strategies on a uniform basis, and we can classify the underlying operating company exposure on a uniform basis. Obviously, we have GICS, very well known on the public side. We've been extending GICS on the private side for a cohesive framework. Once we've pulled in the total portfolio and made sense of it, now we can start to provide fit-for-purpose benchmarking, and we can actually use the classic MSCI factor model approaches to start to think about factor exposures in the total portfolio. We've done a lot of very rigorous methodological work there to actually extend those factors so that they work in a common way across the total portfolio. We can help investors understand exposures, concentration, performance, cash modeling, and then also scenario planning, capital markets assumptions, shocks, et cetera, that they can do uniformly across the whole portfolio. We think it's really a very compelling and innovative product as it stands today. Maybe digging a little bit deeper on this theme, but then talking about the competitive landscape. Obviously, you clearly have a major brand in the public markets. Why do you think you can be competitive in the private market space? Some of those that you just talked about. Look, there are very well-capitalized incumbents that are out there. They're also trying to get into the private market data analytics business, basically. Yeah. They're a very reasonable question. Certainly we're not in any way complacent about the competitive landscape. I think we face, as you say, well-capitalized and scaled incumbents, and we also face smaller disruptor, AI-native firms, et cetera. I think of it as a bit of a competitive barbell, if you will. We're not new to this business, as I said. We've been in the private assets business for 15+ years at this point, so it's not a new business for us. We've served thousands of clients in that segment, and we have for many years. We have a very established franchise. Burgiss really scaled that for us, and it brought in several thousand asset owner now that we have on the platform. It's a scaled platform from an asset owner perspective. Again, we're serving all of these clients already. We're integral to their workflows and process. For many of them, we're actually managing even the capital calls and distributions at scale, et cetera. We're very much plumbed into this ecosystem as it stands today. We're very committed to the business. We have very strong sponsorship from the top of the house down. We're very committed to growing and winning in this business. We think that our combination of deep private assets expertise, the ability to also then bring in sustainability and climate dimensions and start to unify the financial and the physical portfolio is extremely interesting and differentiated capability. Then, as I've said, the ability to do total portfolio benchmark and index at scale with high methodological precision is. There are not very many firms that are positioned to do that. I never say we have a right to win, but I think we're well positioned to win if we execute on these themes. Good. Another theme that's been well-documented, you actually touched upon this as well, is the expansion of private markets into the wealth channel, and the growth of, for example, evergreen fund structures, et cetera. What infrastructure needs to exist for that channel to actually scale? Again, I think you touched upon this a little bit. Again, where does MSCI fit to build this out? Yeah. It's a very topical question, right? As I'm sure you and folks on the call are aware that those fund structures have been somewhat tested recently, right? Particularly in the regime of private credit. Yeah. I think these kinds of market shocks, as long as they're not too destructive, right, and we seem to be weathering, this seems to be working its way through. They're actually good for the market because they literally stress test dimensions of it, and I think people become more thoughtful going forward. I'd say the two main dimensions of evergreens that have become more front and center to people's mind, question number one is the portfolio construction, right? Do we understand what's in these products? In the recent case of evergreen in private credit, I think a lot of the dislocation or concern there came from, was there an overweight exposure to enterprise software? Right? It wasn't necessarily easy to understand that because classifications weren't consistent, et cetera. I think MSCI can really help, and we're working with a number of clients on this, bring standardization and clarity from a classification and a benchmarking perspective. We're talking about apples and apples and oranges and oranges. The second dimension was a liquidity issue, right? You saw pretty much all of the major players breaching their redemption limits, right, and having to gate redemptions. This essentially is a case where the liquidity design of the instrument is not really matching what investors need. I think that I wouldn't be surprised if that drives some further innovation in product structure, where people are like, "Maybe not all products do exactly the same thing." In terms of where MSCI is helping, we're working very actively with clients. We have a liquidity stress test model, which is built, again, on VAR and our factor architecture, to help managers understand much better the characteristics of funds and liquidity and communicate that to investors. Again, in pretty much all of these thematics, the role of MSCI is to try to bring order and clarity and transparency for the growth of an orderly market. We're also doing some stuff in pricing, which maybe I'll come back to later, because that's bigger than just evergreens, but it's also relevant to kind of evergreens. Yes, let's do that. Last question on the kind of big picture strategy, going back to real assets for a minute here. The commercial real estate transaction data set that you guys have is very deep and established, maybe the deepest and most established. Feel free to chime in on that. Look, there's a lot of enthusiasm in the real estate industry about infrastructure opportunities, data centers, energy assets, et cetera. How is MSCI positioned in that particular growing market? Yeah, absolutely. Yes, the firm that we bought a few years ago, RCA, is I think reasonable to say it's considered sort of the gold standard for that transaction data, debt and equity transaction data. Very rich data set, very timely, huge contributor network where we gather data there. As I said earlier, we see a lot of opportunity in commercial real estate itself. The shift out of the core plus and into more of the opportunistic and closed-end fund structures opens up a lot of product opportunities for us there. We're bringing products to market focused in that area. We also see real estate debt as a growth area. There's quite significant growth in that debt complex in order to fund a lot of these transitional projects. You're quite right, infrastructure, data centers is a subset of infrastructure, but infrastructure as a broader asset class has done very well, has continued to show double-digit growth over many cycles. Data centers is just one example of that tremendous growth. We do have data center products in market. We have some deep information on data centers. We have clients that are using that to underwrite data center initiatives. Increasingly, we are, again, coordinating that with our physical risk data because data centers are a great proof point of where sort of the financial and physical world are colliding through AI. I actually think it's extremely interesting because you have issues with data center construction, you have land availability, you have local concern and resistance, you have water availability issues. You can't ignore the physical dimension of this infrastructure investment. We're really leaning into that space with a number of products, and we expect to grow our infrastructure footprint quite significantly. We do already have a very well-established global infrastructure index. It's broadly adopted. It's one of the strongest indexes in the market. We're not new to infrastructure, but we think there's a lot more that we can be doing in that space. Very good. All right. Moving to some specific topics and starting with AI, everybody's favorite topic these days. Thanks for setting your avatar today, by the way. I do have one. Look, MSCI senior management has talked about how AI has helped ingest data better. I think you talked about this briefly before, speed up time to market, et cetera. You've also, I think, launched some kind of AI-enabled products. I think there's the diligence platform, there's the private assets data platform, I'm sure some other things. Maybe can you just talk about what problems AI is now able to solve for you that you weren't able to do before for clients? Yeah, absolutely. I'd say sort of two or three dimensions of it. Dimension number one is just from an operational perspective, we get a huge amount of efficiency and uplift from AI. Really tremendous. That's a function of, ultimately, these were manual processes, right? We used to do document ingestion in sort of emerging market locations, cost-efficient locations. Even pre-large language model transformation, we were already using a lot of machine learning and data science to automate those processes, but we've accelerated that dramatically over the last couple of years. The use of AI in those pipelines to really scale the data processing and completeness has been very significant for us. Not only can we process more data faster and cheaper and more accurately, but we can go much deeper in the data sets, and we can extract even more information from this unstructured data than we did before. That's a huge uplift. The second dimension of it is we are now exposing those capabilities to clients. You mentioned the data platform and the diligence platform. What we're doing here is we're trying to solve an unstructured data management problem where our clients also meet those problems. In the case of diligence, we are helping clients underwrite their investments into new funds. We have a platform that will pull in an entire data room on the fund prospectus, all of the track record and information. It will use AI to digitize and extract all of that information, and it will then contextualize it obviously with the client portfolio and MSCI benchmarks, et cetera. Very rich AI native platform. The data platform itself is a self-service extraction capability. We're allowing clients not just to have us provide the managed service, but also to bring their own documents and for us to bring order and completeness to that, and that's been a very well-received product in market. The third dimension is actually allowing clients to use AI to do their jobs and interact with our data. We have conversational interfaces embedded in most of the products at this point, so you can query interactively and interact in the product. We also have a series of MCP plugins that we're making available, we have customers consuming those in Claude, in ChatGPT. We have one coming for Copilot soon. We're really trying to meet clients where they are from an AI perspective, but we're definitely leaning into AI-native consumption of our datasets as well. Since you just mentioned MCPs, yes, you made your private market data available. Claude's OpenAI, you mentioned. Didn't know about the other one, but can you talk about the uptake you've seen from clients here already? Maybe also what the economic perspective is from an MSCI perspective. How specifically is the growing data consumption that a lot of people are expecting actually helping you, or how is it priced? We've seen very good uptake from MCP, a lot of enthusiasm, and a lot of client adoption. We expect that to grow. I'm going to give you a two-part answer to your question, not getting too technical, the MCPs themselves don't actually use a lot of tokens because it's actually an API endpoint that the client is consuming the tokens to call. The cost there is fairly managed. We certainly are leaning into a agentic delivery, and in that case, we are consuming tokens on our own side. Without getting into the exact specifics of the pricing model, we have a model that puts appropriate guardrails on token consumption, so that we're managing our cost structure there. We're not charging on a per token consumption model. We're charging just still more on a data licensing model for clients on that side. It's definitely something we're thoughtful about, and obviously those models are evolving, and we're staying close to those. Good. Moving on to benchmarking, if that's the right topic. Maybe it's also reference data and index can lump a lot of things into this next section. You introduced PACS in private assets and GRACS, is that how you say it? Yes. For real estate as classification standards. Maybe you can talk about the adoption you've seen so far and how do we actually measure progress in that? Absolutely. The Private Asset Classification System really focused on operating companies and debt, and then GRACS is focused on physical assets, so identifying a building or a bridge and the geocoding and all of the things associated to that. The interesting point is these emerged out of internal data modeling that we've been doing for many years. These standards are already embedded in our products from an asset owner perspective, and so when asset owners go in and look at their portfolio, they're already looking at it through those lenses. We have actually strong adoption already from an asset owner perspective. Where we've been leaning in is with managers and custodians and other market players to adopt this as a uniform way to talk about these assets. This goes back to my point of the infrastructure needs to scale, if we really want to do this efficiently and at scale, and we really need to have a common language. We can't have an asset owner looking at things through one lens and then a manager using their own classification system, because then we waste a huge amount of time in investor relation calls and data calls between the parties to do that reconciliation, right? We also don't have as much investor confidence if the manager, and I'm not saying managers do this, but if ex post there can be a reclassification, right? In private credit, we talked about if you asked the industry pre the Anthropic, the SaaS-pocalypse or whatever, how much of this fund is enterprise software? They'd have said, "Oh, lots of it," because enterprise software was a good thing, right? You have this shift in sentiment. All of a sudden, people are concerned about aspects of that segment. You can have potentially ex post reclassification, and it wasn't really enterprise software, it was more like healthcare or whatever. That's not good for the market, right? That's not an orderly market. We think these classification systems are very compelling for managers. We're hearing from managers that they like them. They want to adopt them. We're seeing interest from custodians and other scale players that need to make sense of all of this complexity for their clients, and we think this can be a terrific tool. As you said, that's definitely an area where we track adoption very closely, and we see it as a flywheel product that will be very accretive to the business as we drive more adoption. Very specifically on indices and maybe return trackers. You've had offerings here for quite some time. Where is the, I guess, benchmark business today in terms of penetration, and what is really the path towards maybe investable private market vehicles? Sure. Those are closely related but separable questions. Yeah I'll take each of them. From a benchmark perspective, we have a broad range of private asset benchmarks in market. We have about 400 of them across real estate and private capital. That number is big because it ends up being kind of the product of region and strategy and whatever, so you end up with a lot of those. Last year, we launched frozen indexes, which is a methodology whereby as new information comes in, we don't restate the benchmark. We actually freeze it at a point in time, which makes it a lot more applicable for certain sort of performance benchmark use cases, et cetera. That was very well-received. In general, again, similar to the PACS thing, and again, our benchmark's derived from PACS because in order to create a fund benchmark, we need to be able to classify the funds that are of a similar form, and that constitutes the benchmark. Similarly, on the asset-level benchmarking, we need to be able to classify operating companies or loans as being of a sector so that we can again create the benchmark. We definitely see that again as a sort of a flywheel or an ecosystem-driving area, and so that's something that we're really focused on. We've been having great success with benchmark adoption. There's been a degree of kind of evangelism in that market where historically, a lot of people use public market benchmarks, right? They would use, for private equity, they'd use Russell plus a spread, or they'd use the Agg plus a spread, like very coarse-grained benchmarks that weren't really fit for purpose. We've done a lot of work, a lot of thought leadership, a lot of client consultation, and I think clients are really starting to understand the value of private market benchmark. I think effectively, the TAM is expanding there as more and more asset owners see the value of those benchmarks, and we're having very good success going after that market on the benchmark side. On the investable product side is a really interesting question, and I think lots of people are talking about it. People are trying to do it to varying degrees. I'm not telling you anything you don't know, but there's a real sort of duration liquidity mismatch between underlying illiquid assets and a more liquid or investable wrapper, and I think these evergreen BDCs we're talking about and the redemption pressure is just one example of that. We are very active in that space working with clients. We do actually have a couple of investable products already in market. We did a product last year with Goldman Sachs, which is a private equity replication strategy. It's essentially a synthetic replication of buyout performance that we were able to develop because we have such a deep data set and modeling capability. Effectively, what that is, it's replicating, as closely as we can, the performance of buyout with a basket of publicly traded equity. Goldman has an ETF that expresses that because you can actually buy and sell the underlying in real-time. We have another product which builds on our capabilities in late-stage venture, and that product tracks some number of late-stage venture names, right? The SpaceX prior to IPO, Databricks, et cetera. That's actually an interval fund structure, which is directly investable, and the manager goes and redeems and buys in-market to actually track our index there. We are already doing investable product in market. We're doing a lot of innovation around pricing, and we think that some of the things that we're doing in pricing are going to open up new opportunities for investable products and either synthetic or direct strategies. It's a great question, and it's definitely a super interesting area that we're very focused on. Good. The final one on benchmarking, I just wanted to touch on real estate for a minute because I think most of this has been more, like you said, like venture and private equity- Yes and so forth. You have the MSCI Global Intel. Can you just talk about what you can offer here that others really cannot, just to bring us home on that topic? Yeah, sure. Two things. There are a lot of benchmarks out there, so having a benchmark is not a unique thing. We have a very, very deep data set. We have a data set which goes back 30+ years, a couple of trillion of assets in it, 30+ countries, very, very comprehensive data set. The richness and completeness and depth of that data is differentiating. We combine that with our capabilities around portfolio analytics, performance attribution risk. It's data, but it's data in the context of an analytical framework, which is very powerful, we think that offering is quite differentiated. Again, as the market moves forward and as things become more interconnected, right? Like we talked about data centers. Data centers, they bring together the credit side, they bring together infrastructure, they bring together physical risk, they bring together debt, all of these things, right? The ability to help investors think about that whole problem set is quite differentiated, and we think the sort of Venn diagram of capabilities is quite unique for us. Good. Few questions to kind of close that out for the day as I look at the time. One topic we really haven't talked about that's been everywhere is private credit. You mentioned it briefly, actually. Yes. Significant growth in that asset class also some stress here recently, which you touched upon. Where or what role does MSCI really play here in helping investors understand and manage their private credit exposures? More specifically, I think you touched upon earlier as well, the daily pricing service you are now providing, is that gaining traction? Where do we go with that? Yeah, sure. We do a number of things in private credit. Again, my overall comment on that asset class would be the same as my general comment, which is, has grown very rapidly, has scaled very rapidly, maybe there's a need for investors to have a little bit more tools to sustain, again, the orderly growth of that market. Private credit, direct lending in particular, serves a very important role in the economy. As banks have retrenched from that space, non-bank lenders have really stepped in there, and it continues to scale and be an important segment. Again, I think the thematic is the same, which is that asset owners are getting more demanding and more critical of understanding their exposure to these asset classes. The total portfolio is one dimension of that. There may be emergent concentration or multiple exposures to the same name through public debt and private credit structures. Many asset owners don't have the tools to actually be able to see that, where we're able to identify that for them. We have a terms and conditions product. For all of our asset owners, we make sense of the terms and conditions of these underlying loans and present them in a uniform and comparable way. We did a partnership with Moody's last year, we integrate Moody's analytics into our platforms, and we're able to provide implied ratings on the loan books, which is quite powerful. Then, as you mentioned on the pricing side, an area where we're very focused is this timing mismatch between public and private markets. As you know, the managers historically have reported quarterly. In some cases, folks are reporting monthly in some of the evergreen structures. Generally, there's a big delay between private reporting and what happens in the public markets. This causes a lot of problems for folks, right? I think the private credit BDC issues are actually, in a sense, they're a timing issue, right? Where the last known NAV was struck at a point in time, the next one's not going to be struck for three months. In between, the public market does all kinds of crazy stuff, right? I think a lot of this redemption pressure is people saying, "Gee, my prediction is the next NAV is going to gap down, right? Therefore, I should exit the position." It's not really what these products were designed for. The liquidity, the semi-liquid feature was really just supposed to be a sort of cash release mechanism. It wasn't supposed to be an arbitrage mechanism. There are a lot of reasons why investors would like to have a better sense of where is the stuff in the intra-mark period, if you will, right? We've launched a couple of, I think, very compelling products, one for private equity, one for private credit, direct lending, then we will have products for real estate and infra later this year. What we're doing there is we're essentially doing a NAV forecast. What we're doing is we're saying, if the manager were to mark today right, on Thursday, where would they mark? Not going to mark for another two months, but where would they mark today? We've built a very powerful kind of econometric model that allows us to impute that based on a lot of different observables, including public market observables. Now we're able to provide clients with a view of where is the NAV today, as imputed through that model. We're now extending that with clients to actually provide more real-time pricing on their funds. We see this as a tool that can really help the industry accelerate the pace of reporting in those products that makes sense, or for institutional clients to have a more real-time view on where their portfolios are. Interesting. Maybe before I finish on the numbers, second last question here. I think we talked about the biggest building blocks in the business, hopefully. You've also launched a lot of new products over the last couple of years. I mentioned that, and we talked about a few of them, I think. Maybe just in almost in closing, what new initiatives are you particularly excited about that we actually haven't really touched upon yet? I'd call out a couple. I think the acquisition of PM Insights earlier this year. We talked about Vantager, which is the due diligence AI platform we bought. We also bought a firm called PM Insights that provides real-time pricing and market information on these late-stage venture firms that I mentioned. They're a leader in that space. That's a very interesting acquisition. We're integrating a lot of those data capabilities into our products for our asset owner and manager clients. I think the whole game in these private assets is how do we bridge the dimensions between public and private, right? Whether that's depth of data, completeness, timeliness, et cetera. I think that's a really interesting building block for us in the space. The other area that I'd call out is the work that we're doing in the GP segment. We're really expanding the work that we're doing with general partners. I mentioned the liquidity stress testing tools that we're providing. We're also doing a lot of work around secondaries investing, broader sort of portfolio management, more real-time portfolio management that the larger GPs are needing to do now, given the kinds of products they have in market. We see that as being a significant potential growth area for the business. Good. Maybe last one, as I promised, finishing on the growth again. Yeah. The business is closed, the segment, because I think there's some revenues may be captured in other areas related to private markets, but the segment is around $300 million in run rate today. The momentum in PCS in particular has been very strong. I mentioned the 16% last quarter. As we look ahead, how should we think about the growth trajectory in the business? What are the biggest one or two growth drivers investors should be focused on? Of course, what's the biggest risk to the outlook? I think we feel positive on the growth outlook. I think we've been building visible momentum. We're showing the momentum in the business, and I think that the engagement with clients, coupled with some very exciting new products that we have in market and more that are coming to market, we'll continue to build on that momentum. I expect to see us continue to build there. Thematically, I think the whole area of benchmarking, classification, indexation is going to be a growth driver, total portfolio, I think there's a huge amount of opportunity for us in that space that we're going to be pursuing. In terms of outlook, I'm not too concerned about the secular, the sort of market context. Whether private credit is sort of in favor or out of favor on any given day, the reality is there is a huge amount of assets in this industry. People need to track them. They need to make sense of them. For the most part, we see institutional investors' long-term outlooks are flat to growth still in private assets. I think we'll feel confident on that. I think that the risks to the business are really we just need to win competitively, right? As you say, I think we have significant incumbent competitors, we need to move faster with them, engage more deeply with clients, provide differentiated services. From an AI or a disruption perspective, we just need to make sure that we stay at the cutting edge, which I think we really are doing, but that people continue to understand that MSCI is the source of truth, the source of the best quality data and insights, and whether that's delivered through an agentic framework or a more traditional data feed or software application, that what they're going to get is going to be differentiated, and that's where we're focused. Excellent. I think it's a good place to stop. Again, thank you very much for making yourself available. Jeremy, thank you for helping set it up, and if there's any follow-up questions, please reach out, and I'm sure we'll get them answered and put you in touch. Terrific. Thanks, Alex. Enjoyed it. Appreciate it. Great. Thank you. Thank you, everyone, for joining.