London Stock Exchange Group plc

Good morning and welcome to the investor and analyst call for LSEG's third quarter 2025 trading update. At this time, all participants are in listen-only mode. Later, we will conduct a question and answer session through the phone lines and instructions will follow at that time. I would like to remind all participants that this call is being recorded. I will now hand over to David Schwimmer, CEO of LSEG, to open the presentation. Please go ahead.

Good morning, everyone. Thanks for joining the call. I'm here with Map and Peregrine as usual, and we are also joined by Daniel McGuire, our head of markets, to talk about the post-trade transaction that we announced this morning. For this quarter, we're going to take a slightly different approach from a normal Q3, given the intense debate in recent months around our business and AI. I'll cover some key aspects of our AI strategy and the excitement we have about the current opportunities before Map goes through the Q3 numbers and Dan covers the post-trade transaction. Then, of course, we'll be happy to take your questions. It has been a really busy quarter with great progress on several fronts. Group organic growth continues to be very healthy at 6.4%, with DNA growing at 4.9%, similar to the first half. ASV growth came in at 5.6%, a little better than expected, and we anticipate it being better again in Q4. We're raising our margin guidance to the top of the original range at around 100 basis points of improvement, reflecting strong operating leverage and cost control. As you may have seen, we've launched a number of AI-related partnerships involving our data, which is valued and relied on by partners old and new as industry standard. We've announced an important transaction today that creates a strong partnership and aligned incentives for the adoption of post-trade solutions, while also increasing our revenue share from Swapclear and extending the profit sharing arrangement with our partner banks by 10 years. More on this in a few minutes. And on the share buyback that we announced at our half-year results, the original intention was to complete that by mid-December. But we've taken advantage of a lower share price and accelerated the £1 billion buyback to finish by the end of this month. And we're today announcing a further £1 billion buyback to be completed by our full-year results in February of next year. Our strong cash generation gives us the firepower and the flexibility to invest organically, to make important strategic moves, and to be active in returning cash to our shareholders. On the next slide, we have summarized our LSEG Everywhere AI strategy under three key pillars, trusted data, transformative products, and intelligent enterprise. We'll talk more about those second two at the Innovation Forum in November. But let me take a minute or two to dive into our data and the critical and valuable role it plays now and will play in an AI-rich world. The easiest way to think about our data is that the content itself and access to it is effectively financial markets infrastructure, something we know a lot about. It is industry standard, deeply trusted, embedded in highly regulated customer workflows, and supported by processes and infrastructure that are extremely hard to replicate. And we are and always have been open. We deliver data to wherever our customers want it, their screens, their servers, their cloud, and of course, through third-party providers. Let's unpack this over the next few slides. Data and feeds accounts for a little over one fifth of group revenues. On this slide, we've broken down these by data type. But before we get into that, I want to remind you of the scale of our data. It is the largest pool in the industry, both in terms of breadth and depth. We have over 33 petabytes of data. That is over three times the so-called common crawl, the data set formed from the public internet, which is used to train many LLMs. Let's begin with the 45% of our data and feeds revenue derived from real time. This is a business built on physics, not probability. We've built connections to 575 exchanges and execution venues globally with our own infrastructure. In the blink of an eye, we standardize and translate the exchange outputs into a single common language and deliver them directly into the world's financial institutions. Millions of hard facts per second, not probabilistic algorithms. In a nutshell, AI cannot replicate or replace our real-time data. Then we have 25% of our data and feeds revenue, which is specialized and enhanced by our own enrichment. By specialized, we mean proprietary. Think trade web, fixed income pricing. or exclusive like the Reuters news agreement or contributed like our deals database. So an LLM could not access these data sets through public sources. And then on top of that, we are enriching this data with value-added enhancements and augmentation by our data experts. That is our additional value add. And then that all comes with the LSEG curation standards, accuracy, normalization and tagging. So think of this data as protected by three modes. It is either proprietary or exclusive. It is enriched by our own intellectual property and it is curated applying the LSEG standards which have often become the industry standard. Let me give you an example to bring this to life. Our deals league tables are highly valuable to banks, advisors, and law firms. These league tables are widely considered the industry standard with LSEC data obtained daily from thousands of sources commingled with data sourced from nearly 2000 financial and legal advisors actively contributing their deal flow. We get up to 25,000 of these contributions per month. This input, which is from humans, is crucial to the quality, accuracy and completeness of this data. These contributions clarify and correct deal details that appear in the press. They also add additional information to public deals and supply information on other deals that are not reported anywhere. So a data set built solely on public disclosures would be both inaccurate and incomplete. We further enrich this data with our proprietary calculation of rank value, which sets the standard for deal comps, market share and pitch books around the world. We refine this methodology each year through round tables with advisory firms, So in case anyone is missing the point, no LLM can gather this data from public sources. Three moats, LSEG proprietary or exclusive data enriched by LSEG IP and curated by LSEG applying the LSEG standards. Let's move on to the next bucket representing 10% of data and feeds revenues. It is almost exactly identical to the previous bucket. It is specialized data, proprietary, exclusive, or contributed with LSEG standards applied. So not accessible by an LLM through public sources, our aftermarket research, for example. And to carry on the analogy with the moats, this is data protected by two powerful moats. Next is another 10% of revenue from data that is indeed public, but to which we apply our enrichment and analysis, similar to what I was talking about with customer contributions on the league tables. And we also applied the LSAT curation standards. Examples here would be earnings estimates and sent to mine analytics applied to earnings calls and other sources. So can an LLM access it? Yes, but the data will be incomplete. Here it is two modes applied on public data. So 90% of our revenue is from data that is non-replicable by an LLM. That leaves us with the last 10% of data and feeds revenue. which represents the data derived from public sources for which we apply LSEG curation standards, data like company filings or economic metrics. This data is rarely sold on a standalone basis. And here there is still one moat, a powerful and important one, and that is our standards, which I will cover on the next slide. Now that we've established that 90% of data and feeds revenue is from data that is simply out of reach or inaccessible to an AI model trawling for public data, let me take a minute to explain very concretely what I mean by that third mode, the LSEG data curation standards. There are five major processes in the curation of LSEG's high quality trusted data, which are simply non-negotiable for our customers in regulated activities. These five processes are the foundations of what we call the LSEG standards. Let's look at them in a little bit more detail. We do not build our data sets on probabilistic models. We have constructed them from decades of hard data, much of which is no longer retrievable. We source them from our customer community, with over 40,000 customers contributing regularly. And in many cases, our own analysts and experts generate them internally. So that is sourcing. We then extensively cleanse and validate this data to ensure quality, for example, verifying its accuracy and completeness. Publicly sourced data is not reliable without this step. The third step, normalizing and mastering, means creating a single source of the truth, consistent from year to year and from security to security, factoring in corporate actions, for example, or restatements or perimeter changes. And then, concordance and tagging, which is a critical and differentiated step, This is where the universal symbology of the RIC or Reuters instrument codes and our use of perm IDs to tag each piece of data are so powerful. They allow full interoperability across the data estate and create logical semantic relationships between related data. For example, between a company and its directors or a bond it has issued. And the fifth step, distribution. Irrespective of technology platform, data format, or channel, the data we distribute to customers is consistent and authoritative. I'll talk more about our distribution strategy in a couple of minutes. So to summarize, for those who think AI models can scoop up so-called public data from the internet and displace us, That just does not reflect how this industry works and fundamentally ignores the non-replicable nature of the vast majority of our data. There's also been a lot of focus on our workflows business. We have driven a lot of change here over the last four years and now have our customers in a modern, modular, customizable platform where we enhance functionality week in and week out. And we're doing more and more. As we said at H1, it is not AI or a desktop. It is AI in the desktop, fully embedded in financial markets workflow. Workspace is now integrated with Microsoft Teams. We'll be launching Open Directory in the coming weeks and the full Workspace AI platform in the first half of 26 with agentic tools coming as well. You'll see all of this at the innovation forum in a couple of weeks. So let's look at our workflows revenue the same way we did for data and feeds. 50% of workflows revenue comes from traders who are deeply engaged with the platform to execute their roles. They need real-time data, a network community, and integration with a range of pre- and post-trade tools. Further, 20% of workflows revenue comes from ancillary trading services, such as trade routing and order execution and management. Another 15% comes from investment banking, where we have specialized content across deals, corporate actions and research, as well as integrated productivity tools. That leaves 5% of workflows revenue from wealth and 10% from investment management. These customers benefit from our unrivaled data, exclusive Reuters news and portfolio analytics. But in these groups, there are lighter users who are mainly doing desktop research and basic charting, perhaps like many people on this call. Whether someone is a power user deep in trading workflow or a lighter user, all workspace users will benefit from the significant AI and collaboration enhancements coming over the next few months. They will have the full functionality of some of the newer applications out there, but embedded in their existing workflow and based on data they can trust. Now, over the last couple of months, you can see the pace of execution on LSEG everywhere, delivering our data to where our customers are working as the partner of choice for financial markets data. This is no change in strategy. We have long provided data to and distributed data through our competitors and partners. For example, we are the number one data provider to Aladdin. The industry now has new entrants, building new applications and functionality, which we believe can expand our reach and drive additional consumption of our trusted high quality data. The economics of these deals support our growth aspirations through data licensing, new channels, and the potential for usage-based revenue over time. Rogo is a specialist provider of applications to investment banking and private equity. Customers with workspace licenses can access certain LSEG data sets through Rogo. The construct with Databricks is similar. These are attractive new distribution channels for our data. Just last week, we took a major step forward in our partnership with Microsoft, introducing certain data sets into Copilot for any Copilot subscriber and more valuable data sets, both into Copilot and Copilot Studio for LSEG licensees. This will allow customers to build their own agents working with our data. You should expect the list of partners to continue to grow as we look to distribute our data through other major channels. That's the fundamental premise of LSEG Everywhere. A key part of many of these partnerships has been our ongoing build out of MCP servers as we make more and more data sets available over time. Before I hand over to Matt, it has also been a very busy quarter in other parts of our business. Just to highlight a couple of significant developments. With Microsoft, we have fully replatformed our trade routing network, Autex, in Azure, with Autex now connecting 1600 brokers and asset managers via the cloud. As a result, it's faster, has much greater capacity, and is even more resilient. And we have executed the first transaction on our digital markets infrastructure, which is positioned to become an important new capability for trading and settlements. we're preparing to launch our private securities market. More on that at the Innovation Forum. And in Risk Intelligence, we have launched WorldCheck on Demand with all our critical data and insight now updated in real time. That takes me appropriately to our Innovation Forum in a couple of weeks. In the first part of the event, Map and I will cover our unique positioning, our end markets, and execution to date. Irfan Hussain, our CIO, and Emily Prince, our head of AI, will cover our AI strategy and engineering transformation. And then Ron Lefferts and Gianluca Biagini will talk about product strategy and monetization in DNA. We'll then have specific product walkthroughs and demos across the group. We're looking forward to showing you both the present and the future. And just to be clear, this is not a traditional capital markets day. Don't expect any new guidance or anything along those lines. So with that, let me hand it over to Map to talk about our Q3 performance in more detail.

Thanks, David. So just a few words on our financial performance. We have delivered another quarter of strong growth across the group. Organic growth for the quarter was 6.4%, with all divisions contributing well. We had a benefit of 30 bps from the ICD acquisition of last year and a headwind of 190 bps from FX, which together translates into our reported growth of 4.8%. Within DNA growth of 4.9%, workflows and data and feeds saw very similar growth to Q2, with only a slight impact from the new UBS contract that I mentioned at the H1 results. Analytics continue to grow strongly. The competitive environment is stable and we are excited about the product pipeline. Our expectation for pricing into 2026 is for the yield to be similar to the last three years in the 3.5% range. FTSE Russell, as I indicated at H1, saw slightly slower growth in subscriptions, with fewer account reviews in the period. But on the other hand, asset-based fee growth was strong as we lapped the loss of a contract last year. Risk intelligence had another strong quarter, driven by both world check and digital identity and fraud. So overall, these subscription businesses delivered 6.5% growth in Q3, ahead of our expectation of 6% for the second half of the year. ASV growth came in at 5.6%, a bit ahead of the 5.4% we had anticipated. Good sales momentum partially offset the expected impact of the final Credit Suisse impact wrapped into the new long-term partnership with UBS. As I have said before, I expect this to pick up again to 5.8% as we exceed the year. The market's business continued to grow well, though at a slightly slower pace than H1 as volatility was lower and comps got tougher. Looking at the two main lines, OTC derivative was up 9.2%, driven by continued strength in client clearing volumes in SwapClear. And fixed income was up 9.9% as TradeWeb continued to drive growth through its innovative trading protocols and an uncertain macroeconomic outlook. Elsewhere, we have seen the IPO pipeline pick up in the equities business with more to come heading into 2026. And we are seeing the final headwinds to growth in securities and reporting from the Euronext exit. Moving now to our delivery against guidance. we are absolutely on track and in some respects ahead of our original plan. Year-to-date organic growth is 7.3% comfortably within our guidance range, and this remains unchanged. On margin, the natural operating leverage in our business give us confidence to raise our margin guidance to the top of the range at around 100 bps improvement year on year. This is a big step up for a 9 billion revenue business and it factors significant ongoing investment in AI and new products. we are very confident of hitting our 2026 guidance of 250 bps over three years, taking us to 50% plus. Obviously, before the impact of the post-trade transaction, which I will cover in a moment. On CapEx, we will invest at a rate of 10% of revenue this year, as planned, and expect that intensity to come down in future years. 102 in the market have asked whether we will need to invest more in an AI future. The answer is clearly no. We have been investing at a double-digit CapEx intensity for several years, and we are now switching the mix over time from technology debt payback towards more investment for growth, obviously, including AI. And finally, we have good visibility of hitting our free cash flow guidance of at least $2.4 billion. And finally, let's look at how we are allocating this cash flow. Overall, we are deploying more this year than what we are generating. That reflects the opportunities we see in front of us. So we expect to spend around 3.5 billion versus free cash flow of 2.4 billion. We are financing the difference with new borrowings of 1.1 billion. Total dividends for the year are just over 700 million, representing a 35 payout of adjusted earnings. In addition, we are deploying 700 million net on the post-trade transaction announced today, where we expect returns to be very attractive. And finally, as David mentioned, you may have noticed that over recent weeks, we significantly accelerated the 1 billion buyback announced with the H1 result, and we have nearly completed it. Given our strong cash generation, low leverage, and the enhanced returns we believe we will generate at this share price level, we are today committing to a further $1 billion. This will start shortly and complete by the full year result in February 2026. We plan to execute $500 of this billion in-year. This is a further demonstration of the flexibility and optionality our strong cash flow generation gives us and our very active capital allocation decision making. Taking all this together, our leverage at the end of this year should be around 1.9 times EBITDA, so in the middle of our 1.5 to 2.5 times net debt to EBITDA range. Let's now look at the rationale of the transaction in our post-trade business that we announced this morning. First, A group of 11 leading global banks is taking a 20% stake in our post-trade solution business. The perimeter of PTS includes the recent acquisition, Quantile and Acadia, plus businesses we have grown organically, mainly swap agents. This transaction deepens our partnership with institutions that can benefit significantly from PTS services and allows them to help share its future and share in its growth. Second, we have agreed to alter the terms of the revenue share paid to the partner banks from Swapclear. Historically, and up to 2024, this sat at 30%, reflected in our cost of sales. We are taking this down to 15% for 2025, applied across the whole year, and 10% for 2026 and beyond. And finally, we are extending it from 2035 to 2045. Again, this is strategically important and it improves our economics at a fair valuation and extends the deep relationship with our partner banks into the long term. Daniel will cover the strategic value in more detail in a moment. But the financial effects of this transaction are very positive. The impact of reducing the revenue share from 30% to 15%, which again is retroactive across the whole of 2025, will add around 250 bps to the market's divisional EBITDA margin and 100 bps to the group margin this year. While obviously there are some financing costs, overall, this transaction is two to 3% accretive to EPS this year onwards. But beyond these financials, and even more importantly, we expect this transaction to accelerate the long-term growth in PTS. Let me hand over to Daniel to recap on the playbook that has been so successful. Thank you, Matt.

So I just want to take a couple of minutes now to highlight how and why Swart Clear has grown over the last 15 years and touch on the opportunity we see forward in post-trade solutions. So through partnership, both through the shareholdings a number of our key members have held in LCH and the revenue share in Swart Clear that continues, we have built a deep and wide global network that delivers significant value to all of its constituents. The scale shift in 15 years is extraordinary. The number of members, i.e. the banks, has increased by 3.5 times. And the number of clients, i.e. the buy-side firms, has increased by 200-fold, clearly demonstrating the network effect. Notional value registered per annum is up 10x at nearly 2,000 trillion. And we have become the global destination of choice for interest rate swaps in all currencies for clearing. This is why we are now inviting our partners in to post-trade solutions, because we believe we can do the same again, but for the uncleared markets. We built a near £1 billion annual revenue business based on cleared OTC instruments across SwapClear, ForexClear and CDSClear, all of which are leaders in their markets, and all of which are built on the strong foundations and the model of industry partnership. The uncleared opportunity is basically the same size as the cleared space. Our members and our clients want to manage the whole book in one place, bringing efficiency to their capital, the margin requirements, and materially simplifying and standardizing processes. We are uniquely placed to do that, given the assets that we've built and brought together under one roof. And with our proven track record of delivering real value through long-term partnership, Acadia and Quantile give us collateral and margin workflow tools and compression tools respectively. And swap agent and trade agent, both developed in-house, complete the current suite of services we call post-trade solutions. And we've got very good momentum to build on. Revenue in PTS is growing at double-digit pace. Volumes are up 70% and the network is expanding at pace. So bringing these 11 major partners closer and giving them a role in shaping the business, as well as a share in its growth, sets us up for long-term success. I'll now hand back to David. Thanks, Dan.

So just to recap, we have had another strong quarter of growth with year-to-date organic growth at 7.3% and all of our businesses performing well. We're executing at pace on our AI strategy of LSEG Everywhere as the AI partner of choice for financial markets data. And we are allocating capital effectively and proactively with an attractive strategic deal in post-trade and a further big step up in our buyback program. And now, Map, Dan, and I are happy to take your questions.

Peregrine? Thanks, David. As usual, please, can you limit yourself to one question and a follow-up after the answer? And with that, I'll hand over to Polly to manage the queue. Thank you.

Thank you, Peregrine. And if you would like to ask a question, please press star 1 on your telephone keypad to raise your hand and join the queue. If you would like to withdraw your question, simply press star 1 again. And if you are called upon to ask your question, please use your handset and ensure that your phone is not on mute when asking your question. And your first question comes from the line of Arnaud Giblard of BNP Paribas. Please go ahead.

Yeah, good morning. Could I start with the post-trade solutions? So banks are paying over 50 times EBITDA, nine times sales for their stake. Clearly, as you said, that comes with a significant commitment to put more business through that division. I'm just wondering, I mean, you gave a bit of detail, but if you could flesh out a bit more, what sort of commitments, the timeframes, what specific milestones we should be looking at for that business to grow and what perhaps to give us an indication of the potential size of that business in the medium term, from a revenue perspective. And my second, my follow-up would be on the distribution agreements with third-party providers. Quite a lot going on there. I'm just wondering how we should think about this because clearly there is a bit of a usage model you've talked about. So probably this increases significantly usage and therefore gives revenue upside. At the same time, if clients are accessing your data through a third-party vendor, then how does pricing in the long term look like if the interface is somebody else? Thank you.

Thanks Arnaud. Let me turn it over to Dan to answer the aspects of your first question. We're not gonna get into a lot of detail on what the revenue looks like over the medium or the longer term, but you can talk a little bit about how we're thinking about the construct. And then I'm happy to talk about the distribution agreements.

Okay, yeah. Thanks, Arnaud. Look, we're very strong believers in the industry partnership model, as you know. We've been using that, building that for a number of years on different services, and I think you can see the outcomes of that. Ultimately, we build core critical infrastructure for our major customers here over a long-term basis and around the basis of trust. We're very, very pleased that we've got our major partners around the table with us and aligned not just on economics, but also on the product roadmap, the governance and the product adoption of which we have a pretty high rate of adoption for all the products we build because of this model. I can't really be drawn on revenues. What I can point to is when you look at the, which was shared in the slide, that the gross market values, which essentially is a proxy for the scale of market risk and derivatives. If you look at these numbers come from the BIS, Independent Annual Surveys, The gross market value is about 17.6, and just over half of that is in the cleared space, but over half of that is in the uncleared space. So if you think about the level of risk of derivatives being transacted and risk transferred, they are very similar size. So we see the size of this opportunity very similarly as a result of that. And then in terms of milestones, we've got, as you can see from the press release, 11 major firms and important people at those firms making clear commitments to work with us to build out and deliver and adopt those services. So can't be drawn on specific roadmaps and revenues today, but very confident that we've got the right support from the right firms and the right people. And the network is much bigger than those 11. And we've already got very good momentum in that. So pretty confident on that.

And then on your question around these partnerships or distribution arrangements, I know the first point to make is that we've been doing this for years and we have been providing our data through partners And in some cases, as I mentioned, competitors for many, many years. And it's key when we do that, and this is a practice that we will, of course, maintain, is that we protect our own relationships with our customers. And so in these kinds of partnerships, basically the way they work is that although the initial origination of the relationship might come through one of the partners, the customer is then directed to us to establish the direct customer relationship with us. And we do that in a number of different situations and circumstances. protects us from being disintermediated through these kinds of arrangements. The other really important aspect that we're very focused on in these kinds of partnerships and distribution arrangements is protecting our data and making sure that our rights, our IP are protected even through any of these distribution channels. So obviously, the AI world is a little bit different, but we're still in a position to protect our data. And let me just give you one specific, I'll say, technical example. When we're distributing our data through an MCP server, because of that construct, we can control and monitor the access to our data. So in that construct, we're not at risk of a customer downloading all of our data, training their models on our data, and then not needing us anymore. This MCP server construct allows us to control that in a very successful manner. maintaining the relationship, protecting our data and data integrity. These are the kinds of relationships that we have managed very successfully for a long time. And it's great to see these new entrants and these new ecosystems because we think it will actually expand the market and the customer base that will be able to access our data. So we're really looking forward to this and excited about it.

Great. That makes sense. Thank you very much. Thank you.

Your next question comes from the line of Andrew Lowe at Citi. Please go ahead.

Hi, guys. Thanks very much for the colour on the revenue split by product in workflow and feeds. My question is on the data and feeds business. Specifically, how much of the historical revenue growth has been driven by pricing versus volume? Could you please also comment on historical pricing trends across these different groups? So, for example, it'd be great to know how pricing growth in real-time data compares to the other segments, including the 10% from public data sources. And it'd be great if we could hear a bit more about how much visibility you have on future pricing. And I've got a follow-up, but I'll wait until you've answered it.

Yeah, thanks, Andrew. So not going to break it down product by product, but as we've been pretty clear over the last few years, you've seen our pricing yield on an annual basis being that sort of three to three and a half percent zone. And then you've seen our data and feeds business grow exponentially. Usually more than twice that. So that gives you a sense of what's going on here in terms of pricing relative to just volume growth. And we've been doing a lot of innovation in this area as well in terms of new products, new distribution channels as well. But hopefully that gives you a sense on that.

Great. Okay. And then as a maybe a follow up to that. So are you seeing a pickup in demand for your tick history now that you've got sort of LLMs, which are cheaper and more widespread? And how important is that when you're sort of selling your forward looking real time pricing data?

So interesting question and tick history for everyone's benefit is a great data set that we have that goes back to the 90s and has tick by tick history for millions and millions of securities. And no one else has has it. It was all public data when it was released by the exchanges. But we are the only ones who have. stored it, maintained it, and made it easily consumable. I would say the technological changes make it easier to consume and access now than it has been over the last 20 plus years. And we certainly expect to continue to see it being a very valuable content set. Historically, it has been mostly used by quant shops backtesting their algorithms. But your question is a good one in terms of recognizing that with these models, you could see a lot more potential users accessing this huge data set to look for historical correlations and help that inform their trading on a go-forward basis.

Great. Thanks very much. Thank you.

Your next question is from the line of Russell Quelt of Rothschild. Please go ahead.

Yeah, good morning. I'd also like to focus these questions on the data and feeds business. Thanks for the extra disclosure on the revenue breakdown. So you disclosed that 55% of the data and feeds revenues come from pricing and reference services. And I believe you've gone from number six player there to number three player in the last couple of years, just behind Ice and Bloomberg. So my questions are firstly, number one, how have you done that? And what's your view on the main points of differentiation in your offering, which is helping you to take share? My second question is, do you believe you can be a number two player here? And if so, how? And the third question is a bit of a follow-on from Arno's question, but asked in a bit more of a direct way. Can you talk to your expectations of the size and cadence of the growth up list from the recent and future data distribution partnerships that you mentioned relating to LSIG everywhere?

Sorry, can you say that last, the third part again?

Yeah, sorry, a bit of a mouthful. So I was thinking about the data distribution partnerships relating to LSEC Everywhere, both the current ones you disclosed and then you said about future partnerships. So I was wondering how we should think about the size and the cadence of the growth uplift that comes from those partnerships, both the ones that have been announced and potential future ones.

Got it. Okay. Thank you. So your first question, how have we moved from number six to number three? it is investing in our content and investing in our distribution. And you have seen us over the last few years do a number of I would say pretty significant steps in a number of different areas. So for example, when we took on the Refinitiv business several years ago, it was very clear to us that, for example, talking to customers, they made it clear, fixed income evaluated pricing was a weak area, corporate actions, was a weak area. We have invested meaningfully in both of those areas and addressed those gaps. And we're now highly competitive in those areas. And so that has helped us move up the ranks. We have added new content in terms of a number of different areas ranging from I guess a good example is our inclusion of Dow Jones content alongside our exclusive Reuters news, alongside thousands of other news sources. So constantly investing in content in a number of different areas. And then on the distribution side, Over the last few years, we have made our content available through a number of different distribution channels. And whether that's in different cloud providers, whether that is there are some of our data sets, for example, they were only available in the U.S. for technology reasons. And we have now made those available on a global basis. So it's a number of things like that. But really, if I boil it down, content and distribution. Could we be number two? Sure. You know, and we aim not to stop there. We're continuing to invest in this business. We have great data, great content, adding to that content, expanding our distribution capabilities. And then in terms of, you know, I'm not in a position to give you any details. specific guidance on the growth uplift. What I can say is that we're not done yet in terms of the different partnership arrangements. We think this is a really exciting time in terms of new ecosystems, new AI functionality that will provide lots of distribution opportunities for us in as I mentioned earlier, into customer segments that might not have otherwise accessed our data. And for those customers that have historically accessed our data, this AI functionality enables them to access it in a, I'll say, a much deeper way. I mentioned earlier the 33 petabytes of data that we have. Historically, our customers have really only scratched the surface of the data and the content that we have. And the AI functionality is much more powerful in really consuming substantial amounts of our data. And then as we shift further down this road, we've talked in the past about evolving our model more towards usage-based and consumption-based pricing. So you put all that together, we are excited about what this opportunity holds.

Okay, and maybe just as a follow-up to that, you've just seen S&P with intelligence, you've seen BlackRock by pre-Quinn, you've seen MSCI by Burgess. So just wondering how you're thinking about your competitive position in private market data, and is this something you might look to add inorganically to the offering?

Yeah. So we have we already have a lot of private market data. And that includes what we have ingested organically. It includes what we provide from Dun & Bradstreet. The Dun & Bradstreet data, by the way, currently available on the workspace. but soon will be available through a feed, which I think is unique in the industry. We have our partnership with StepStone, which is enabling us to create, again, unique private asset product in our index business. And maybe the last thing I would say is we are not done in this space. And there's more to come in terms of our ability to provide incremental value add, and in some cases, unique private markets data. So I can comfortably say, watch this space.

Thank you. Appreciate it.

Your next question is from the line of Ian White of Autonomous Research. Please go ahead.

There's been a lot of discussion around the accuracy of general intelligence LLMs in financial services applications. What advantage can you derive here from your privileged access to your own data when it comes to the training and development of more accurate models? Or kind of put differently, is it realistic that general intelligence tool can match a model that has been trained on your specific data set when it comes to generating accurate results derived from your data? That's essentially my main question. And just as a follow-up, on the workspace rollout, which is now complete, what's the latest evidence you have regarding levels of customer satisfaction with Workspace versus the legacy desktop products, please. Thank you.

Yeah. Thanks, Ian. So on the accuracy question, you know, there has been a lot of discussion in the industry about, you know, a bunch of the product that is out there really, you know, maybe having some nice user interface, but not being remotely close to what this industry demands in terms of accuracy. And so I think that's probably right at this point for a bunch of the products that are out there that we have seen. We expect them to get better over time. I think in terms of our own approach, The advantage that we have is that we have the data. We have the highest quality and broadest data set that allows us to do the necessary training. It is scrubbed data. We're not training our capabilities on data. the internet. And so we avoid the garbage in garbage out problem that you see with a lot of these other models. And this gets back to the point I was making earlier that through the MCP server construct, we are able to control the access to our data. So we sometimes get questions from people worried about the fact that our data will be made too available and others will be able to, without compensating us, train their models on our data. And that's not the case in terms of the way that we make this data available for AI usage or AI consumption. In terms of the workspace rollout, we are very pleased with the outcome there. This was a big exercise over the past couple of years. We are seeing really good views on the simplicity, on the change in the user interface, on the speed. There are some aspects in terms of making the Some of the charting, even better. There are a few different things that we're continuing to work on, as I mentioned earlier, sort of week in, week out. And this is going to continue. And it's one of the advantages of this product and the technology stack that we have moved on to. Now, we've talked about how we've implemented 500 or so changes in each of the last two years. And that pace is continuing. So even though we have basically completed the migration, we still have more releases coming. I think we have two more releases coming. Big, broad releases coming this year. Yeah, more coming early next year. So it's a continuous improvement exercise, which I think is fantastic. you know, a great opportunity to continue serving our customers better and better and better.

Got it. Thank you. If I just, just to sort of play back and make sure I've understood on the first point, if anybody wants to sort of train a model on your data, that's kind of a licensable activity that you can kind of control through MCP and And the model that's not trained on your data specifically probably won't be very effective or will be less effective than something that's been specifically curated for that purpose. Is that a fair reflection?

I think that's fair. I don't want to claim that we have exclusive financial sector. In other words, I don't want to claim that in the financial markets, we're the only ones who have financial markets data. There is other data available out there. Ours is the broadest, the deepest, the highest quality. And so we are in an advantaged position. But you've seen companies train their models on public data coming off the internet. That's on the other end of the spectrum in terms of quality and accuracy. And then there are other data sets out there that you can use. They're just not as extensive and high quality as ours. Got it. Thank you.

Yep.

Your next question is from the line of Mike Werner of UBS. Your line is open.

Thank you, guys. And just two questions here, one main one and then one follow-up, please. I was just wondering, I mean, you talked a lot today and very helpfully about the new partnerships and LSAG everywhere. Just stepping back and when we think about the partnership with Microsoft and OpenAI and what you guys are doing there, What's the level of that engagement today versus 12 months ago? I think you used to talk about the number of software engineers that were operating on site on LSEG's premises that came from Microsoft. I was just wondering if you can give us an update there. And then as a follow-on to a couple of my colleagues' questions, when we think about these partnerships, particularly with the new ones with the AI engines and AI partners, Is there any delta or any difference in how you think about the pricing? I know you said you protect the IP, but when you're thinking about these new partnerships, is there any change in the way that users who want to consume that data, would they see any difference in pricing than your traditional customers? Thank you.

Yeah, got it. Thanks, Mike. So in terms of our partnership with Microsoft, if anything, the level of engagement is higher, and I would say meaningfully higher today relative to where we were a year ago. I know what you're referring to. We've talked in the past about having hundreds of our people embedded with their teams and vice versa. That continues, and if anything, higher level of engagement. And we talked today about a few other things that the market hasn't really focused on, but that we're building with Microsoft. Our Autex routing network, our digital market infrastructure. These are not the areas that the market has really focused on, but we are actively building them with Microsoft. And then, of course, our data as a service, our analytics, workspace being embedded in in Teams, all the interoperability with Excel and PowerPoint. We have lots of teams working across a lot of different areas with the Microsoft team. So couldn't be happier about the level of engagement there. And then just with respect to the pricing, You know, in some cases it's really simple. So for example, we talked about the partnership with Rogo. If you want to access our data in Rogo, you have a workspace license. You know, it's very straightforward. It can be a little less straightforward if we are providing our data sets our data and feeds data sets through some of these channels, but we have standard pricing for a lot of these. There may always be some negotiations around particular data sets or things like that, but we have standard contractual arrangements for these and standardized pricing for these. Thanks, David.

Yep. And before we move on to the next question, a reminder, if you would like to join the queue to please press star one on your telephone keypad to raise your hand. And your next question comes from the line of Hubert Lam from Bank of America. Your line is open.

Hi, good morning. I've got a couple questions. Firstly, on DNA, how should we think about revenue acceleration in the next year? So just given the upward momentum on ASB, should we think 6% or more could be achievable for revenue growth in DNA next year? Second question is, I guess, last results, there was concerns about intensifying price and competition. from a couple of your biggest competitors. Just wondering if you've seen any normalization in terms of pricing or was the competition we saw a few months ago a bit of a one-off? Thank you.

Sure. Matt, why don't you take the first question? I'm happy to take the second one.

Yeah, sure. So... On DNA, we indeed forecast a revenue acceleration next year. We haven't given precise numbers, but we have given one precise number, which is for our subscription business altogether, reaching 6.5%, circa 6.5% next year. And obviously, DNA in this number is playing its part, and it will be accelerating 26% on 25%.

And then on your second question, Hubert, first, just to remind people, when we talked about some of the competition dynamics at the half year, that was a very small number of cases, a couple in each of the different business areas. And I would say where we are today, we're not seeing that kind of dynamic. It feels like a very stable market environment at this point from a competition perspective. Great. Thank you. Thanks a lot.

Your next question is from the line of Ben Bathurst of RBC Capital Markets. Your line is open.

Good morning. My questions are on post-trade. Firstly, could you help us better understand how interrelated the two transactions announced this morning are, if at all? For instance, how different is the list of the founding members of Swapclear from the investing banks in post-trade solutions? And secondly, How significant is the decision to extend the revenue surplus share from 2035 to 2045? Was there always a presumption that that would be extended or was that kind of an incremental sweetness in the deal? Thank you.

Thank you. Thank you. Yes. So in terms of the constructs of the overall deal, there are 13 banks involved in the SWAT business today. And in the investment in PTS, there are 11 investing banks, just to be clear around that. decisions to invest in the new business ventures very much down to sort of individual circumstances of each of the banks there so not really appropriate to speak on behalf of those in the 13 that aren't in the 11 but what I'll say is you know super strong engagement across the industry level of participation in this and interest is very material from all the material players there so we're very very happy with that and in terms of the extension that you ask about yeah I think maybe different opinions on whether that would have been extended or not, but the fundamental point is this is something that's been in place since 2001. We're here in 2025. It was rolling to 2020. of the overall structure, those 11 banks that are investing in PTS will be extended for a further 10 years of 2045. So a 44-year enduring partnership between the major players in the OTC derivatives space on the sell side with ourselves there. So I think it's part of the overall construct rather than breaking it down into the exact sort of elements of the negotiations.

Okay, great. So if I understand it rightly, it's just those that are participating in post-trade solutions that will have the extension for 2035 to 2045. That's correct. Thank you.

And just to be clear, 25 to 35 remains all the existing 13. So existing 13 till the maturity of the existing arrangement and the extension of 10 years is to the 11 that are also investing in the post-trade solutions franchise of business. Great.

That's very clear. Thank you very much. Thanks, Ben.

Your next question is from the line of Julian Dobrovolski of ABN AMRO. Please go ahead.

Good morning, gentlemen, and thanks for taking my questions. I have two, maybe the first one regarding the Microsoft product development, such as Open Directory and Analytics API and some other things that they're trying to roll out together with Microsoft. Just wondering, are these offered broadly across all the tiers or restricted to premium users and as such used as an upsell vector? And then the follow-up, it's on ASV growth. Just wondering how confident are you regarding the, let's say, re-acceleration of this in the Q4? I think you've been hitting towards 5.8%. And can you please elaborate the impact of the UBS multi-year contract and the credits with revenue crystallization? And perhaps if you can see some leading indicators suggesting a bit of a rebound in ASV growth in the Q4.

Thanks, Julian. So I'll take your first question and Map can touch on your question on ASB. So on each of these different products, some of them, the different products that we have built in partnership with Microsoft, some of them are separate products that have separate pricing, separate licenses, separate arrangements. Some of them are embedded in existing products. And so if we talk about open directory and we talk about... what's coming in workspace, you'll see us charge for that over time really through price realization in the core product. I think then in some of the products that we have rolled out in analytics, the analytics API, for example, that's a new product and there's separate charging for that. And we've seen some of that in the uptick in the growth rates in analytics, for example. And let me just, I'll mention one other example where you can see this very clearly. The arrangement that we announced with Microsoft, we can have two weeks or so ago, where we are making our data, we're making some of our data sets available to all users of Microsoft Copilot. So if you have a Copilot license, You can be outside the financial services sector. You have a co-pilot license and you're doing something in co-pilot. You will get access to certain of our data sets. And that's an arrangement that we have with Microsoft. And then we have other data sets that you can license directly with LSEG. and then have access to them through Microsoft Copilot and Copilot Studio if you are building, for example, agents using our data. So that gives you an example where some of the pricing arrangements are embedded in existing products. Some of them are new, and we are charging incrementally for them.

Let me turn it over to you, Matt. Yeah, sure. So first of all, before I ask you a question, I'd like to point out that we have outperformed our previous guidance on ASV. Remember, in H1, we were expecting that the Q3 ASV would fall to 5.4% with 40 bps of impact of UBS. So excluding UBS 5.8, so comparable to Q2, and we posted 5.8 in Q2. 5.4% was what we were expecting for Q3. We actually outperformed this to 5.6%, so X UBS 6%, such an acceleration from the 5.8% we were at the end of Q2. And when I look forward for the end of this year, we're very confident into accelerating again to 5.8%. And here it's the same thing. It's 5.8, including of the 40 bps for UBS. So actually excluding it, 6.2%. So, you know, 5.8, 6, 6.2. That's basically the message today. Understood.

Thanks. Thanks, Julian. Your next question is from the line of Enrico Bonzoni of JP Morgan. Please go ahead.

Thanks for taking my question. I wanted to ask you, you now revised your EBITDA guidance a couple of times, even excluding the newly announced deal. So I just wanted to ask you, what are you doing particularly well or better than you expected that basically drove the consecutive revision in guidance? So that's my question. my first question and partially related to that just some small clarification so one you are clearly now spending um just over a billion to to um in source this additional revenue from so clear can you just clarify whether this will be capitalized and whether the amortization of that will be above or below the line so that's uh that's one question and um another related question to numbers You're clearly issuing some debt. You're guiding for EPS accretion in 2025. What about 2026? I know you talked about margin expansion for EBITDA in 2026. Can we say that we will also see a similar EPS uplift for next year? Thanks.

All right, so I begin with ABDA margin. So yes, just to remember for maybe those of you who didn't see it, we began with 500 to 100 bps of ABDA margin. a guidance for this year. We reduced it, then improved it to 75 to 100. And finally, we are now confident to reach 100. It's really an acceleration. So what we have implemented in the last two years at ELSEG is a full cockpit of cost discipline addressing all the different components of our cost base. So mostly people, we're talking a lot about people obviously, but it's true too for cloud costs, on-premise costs, travel expense and so forth and so on. And basically this acceleration is coming from the fact that what we have put in place is more efficient and is producing more results and quicker, if you want, than what I expected at the beginning of the year. The second reason So that's an acceleration. Second reason, which is more structural is, and maybe you remember what I was telling you at the earnings of 2024, the different automation solution that we have put in place at different places in the company. So in QAS, meaning our customer service, in our content ingestion, we were putting it in place and I was expecting to see the first materialization into savings, next year. And actually it's happening as early as this year. So that's the combination of the two. Now to answer your second question about the 1.15 billion that represents the alteration of the swap clear revenue share. So we're considering this as an acquisition. So we are creating an intangible asset, exactly as we would do as a traditional acquisition. And we are going to amortize it over 10 years below the line as the rest of our acquisition. And then your final question, which is the accretion. So accretion of 2% to 3% in 2025, because I want to be clear on the fact, I hope I was clear in my script, that this revenue share alteration is retrospective to the 1st of January of 2025. So it means that we benefit from the full accretion in terms of EBITDA margin that I have mentioned of 100%, and in terms of EPS, taking into account the financing cost, we said two to three percent in 25 and we'll have pretty much the same thing two to three percent in uh in 26. and your next question is from the line of Tom Mills Jefferies please go ahead oh good morning guys thanks thanks for the helpful call um I I think we've skirted around it a few times on the call I just wanted to

clarify that you are sort of reiterating you're expecting to deliver around 3.5% price increase on the 1st of January.

Absolutely, absolutely. We've just sent the price letter was sent in September. We are on the basis of the first reaction from this price letter and our experience. We are confident we will derive the same type of yield around 3.5% in 26 as the one we had this year in 2025. Excellent.

Thanks very much.

Thank you. And your next question is from the line of Oliver Carruthers of Goldman Sachs. Please go ahead.

Oliver Carruthers from Goldman Sachs. Thanks a lot for the presentation, and thanks for a lot of the incremental KPIs around DNA. I just have one quick modeling question on the FTSE Russell subscription revenues. I think you're calling out the more modest growth in subscription growth here in Q3 was to do with this mandate renewal cycle that you think is going to normalize next year. So just what's reasonable to assume in terms of the pickup and growth rate? I think you're running it around 5% on a constant currency basis year over year for Q3. And the reason I ask is if we go back to 2024 levels of around 10%, on my math, just add something like 70 basis points to your ASV, which is any parameterizing of that would be very helpful. Thank you.

Yeah, thanks, Oliver. So you're right. This year, a much quieter period in terms of renewals during which we would typically see incremental revenue associated with either regular price rises or bigger, broader business relationships and broader engagement. Now, I think, you know, hard to give you specific numbers as to what that's going to look like in 26 and beyond. You know, you've seen how this business has performed in years past in that kind of higher than mid single digit zone. So I think, you know, I'm probably pretty comfortable, and Matt, feel free to weigh in here as well. I think we're pretty comfortable in that zone, but I don't want to be giving you any sort of specific guidance on what that looks like at this point.

And there are no further questions on the conference line. I will now hand the presentation back to David Schremer, CEO of LSEG, for closing remarks.

Great. Well, thank you all. Thanks for joining us today. As I said up front, a little bit more substance in this one rather than a typical Q3 update. We hope you all have found it useful. And if you have any questions, you certainly know where we are. We'd be happy to take any further questions through Peregrine and the team. Thanks again.