London Stock Exchange Group plc (LSEG) Earnings Call Transcript & Summary

Good morning everyone, and welcome to LSEG's H1 results presentation. Thank you for joining us. As usual, I'm joined by Map, our CFO; and Peregrine Riviere, our Head of IR I'll give you a few highlights of the first 6 months and then hand over to Map to talk through the numbers in detail. After that, I'm going to spend some time talking specifically about our progress in DNA and our deep engagement with customers as they adapt to an AI world. And then, of course, we will be happy to take your questions. It has been a great first half. We achieved organic revenue growth of 8.4%, with strength across the board. Subscription growth accelerated to 6.3%, and -- our EBITDA margins improved very strongly, and we're raising guidance to the top of the 80 to 100 basis point range. The top line and margin improvement delivered 17% earnings per share growth. an exceptional growth of 37% in free cash flow per share. We made record returns to shareholders, around GBP 2.6 billion across dividends and buybacks and are back in the market as of today, with our next buyback tranche. This performance and the presentation we're going to share with you today show just how deeply we are engaged with customers across a wide range of data and multiple products increasingly involving co-development of agents and delivered via both existing and new infrastructure. This engagement demonstrates our deep institutional partnerships, the trust in our data, and our engineering expertise. Demand for financial data and analytics is as strong as ever. In fact, segment spend has more than doubled in the last 17 years, while industry headcount has fallen by a quarter. the value of data has decoupled from the number of people using it. I'm going to talk upfront about our markets businesses because my progress update later will focus exclusively on AI and the DNA business. Remember that markets is 40% of LSEG revenue. All our menus have had an exceptional 6 months. Following a very strong Q1, we've seen solid follow-through in Q2. We comping a pretty extraordinary prior period in 2025 as well. These platforms are not just about volatility. Almost all of them have strong underlying growth drivers, too. And we have invested in them over the years to expand their reach access new asset classes and develop new protocols to meet customer needs. To highlight a couple of really notable performances, SwapClear and equities, both maintained very strong momentum from Q1 into Q2. We Total interest rate swap notional cleared was up 29% across H1 and equities average daily volume on the LSEG was up 34%. Some may think that whether our markets business does well is just a function of market volumes, but LSEG markets has been doing great for the last 5 years, showing the strength and consistency of execution and the growth drivers we have aligned the business with. Annual growth has averaged almost 10% over this period, and it's also been consistent. There have been strong years and really strong years, but no weak years. We fully intend to maintain that momentum and we're investing by it. In the last 6 months, we've done our first private securities market transactions, including 2 high-profile U.K. unicorns this month. We've launched DISH, our platform for real-time settlement, which bridges on chain and off chain. And in post-trade solutions, we launched Trade agent. We just announced our MOU with HSBC to support the U.K.'s first digital Gilt instrument and LSC24, our 24.5% equity trading platform. We'll do a deep dive on our work on the digitalization of market infrastructure, covering all of this in early December. And this all translates into our all-weather model. On this slide, we've shown our organic revenue growth over the last 6 years compared to the change and volatility in a number of measures, which could be seen as drivers of our business. GDP growth, market volatility, equity or debt issuance, for example. As you can see, particularly on the right-hand axis, these measures can bounce around a lot, but you wouldn't know it to look at our revenue growth. The message is clear, solid and accelerating subscription growth, plus attractive market exposures across multiple asset classes generate strong and consistent top line growth. irrespective of the external environment. Plus whichever way you look at it, the gradient of growth from left to right is clearly trending up. And now, let me hand over to MAP to take you through our very strong financial performance in more detail.

Thanks, David, and good morning to all of you. As you heard from David, we delivered an exceptionally strong financial performance in the first half. Organic revenue, up 8.4%, adjusted EBITDA up 14%, adjusted EPS up 17% and free cash flow per share, up 37%. I will now walk you through the building blocks of that performance, starting with revenue growth. Organic revenue growth accelerated to 8.4%. And with a 1.5% headwind from FX, reported revenues grew 6.9%. All 4 divisions made a strong positive contribution to that growth as we see on the next slide. D&A was up 5.1%, FTSE Russell and Risk Intelligence, both grew between 9% and 10%. Taken together, the subscription businesses accelerated growth to 6.3%, well on track for our 2026 target of 6.5%. Markets had a very strong half, growing 12%. We I will now talk through each of these divisions in more detail, starting with DNA. Workflows continued its good performance, growing 2.8% Workspace users are responding very positively to the AI tools introduced in the first half, driving additional engagement with the platform. We continue to expand the power of Workspace integrating FX or more deeply working towards more seamless Tradeweb integration and expanding initiatives like Open Director. Growth in data and feeds is accelerating, up 7.5%, driven by our continued innovation and the demand in its supporting across both our real-time and pricing and reference data. I will come back to this on the next slide. Finally, Analytics grew 6%, with good demand for our yield book and [ lipa ] products and supported by 33% growth in usage of our analytic API. Increasingly, customer engaged with our DNA product as a similar solution as part of our LCC data access agreements or LDA, these enterprise-wide agreements now drive 18% of DNA revenues, up from 16% at the end of last year. Our largest customers benefit from access to our solution at scale and in return, they give us many years of visible revenue and growth. Returning to data and feeds, customer appetite for our data continues to grow extremely fast. Roughly half of our revenues here come from our retail services, where our strengths across the latency spectrum position us as the provider #1 globally by some way. We continue to see rapid growth in the volume of data on this platform, up 70% year-on-year in June. With that big spike driven by global fund flows, and some big market transactions and up fourfold in 10 years. Demand for historic pricing data continues to grow strongly, too with 39% annual growth in Tickistory usage over the last 2 years. appetite for our cloud-based solution here is particularly strong. Turning to FTSE Russell. We continue to see strong demand for our flagship equity indices and benchmarks and good momentum in new products. Subscription revenues grew 6.2%, and we expect this to accelerate to high single-digit growth in the second half. Asset-based revenue performed well, up 15%, driven by higher asset prices and strong inflows. During the half, we launched 52 new ETF, up 24% from H1 2025. We also announced the introduction of the Russell 9000 index series, expanding the Russell framework from U.S. to global equity markets. Moving to Risk Intelligence that delivered another good performance, up 10%. The demand for World Check was the primary driver of growth, although digital identity and fraud was also very strong with volumes up more than 20% in H1. Looking now at the KPIs we introduced at the start of the year. As a reminder, these give additional insights into our 3 subscription businesses, DNA, FTSE Russell and Risk Intelligence. Starting with retention, which rose slightly in the half at almost 93%, that speaks to the value we provide to clients as well as a long-term nondiscretionary nature of most of our services. Gross sales of GBP 482 million continued to be strong, increasing 11% compared to June last year. And lastly, the new product vitality index, which is a very healthy 25%, highlighting the high level of innovation across our businesses and customer receptivity to our new or enhanced products. These are the building blocks of our growth that feeds to ASV growth of 6.1% as we exited Q2 up from 5.9% we reported at year-end. Our Markets division performed exceptionally in H1, particularly given the incredibly strong prior year comparator. Tradeweb and our OTC derivative businesses grew double digits. And our FX business also had a strong performance, growing 8%. For simplification, we show equities on this slide with some other market activities, but the equities business grew 12% in H1, driven by strong secondary market activity. We are also seeing traction building across recent initiative with an encouraging pipeline for our private securities market. Looking at the whole P&L now. You can see our combination of top line strength and focus on cost discipline and efficiency is delivering good operating leverage throughout the P&L. As I already mentioned, revenue growth of 8.4% translates into 14% growth in EBITDA, 17% growth in operating profit and 17% growth in EPS. All that on an organic constant currency basis. Taking a closer look at cost on this slide. The 2.5% fall in cost of sales reflects the change to the SwapClear revenue share agreement at the end of last year. This revenue share was at 30% in H1 2025 and is now at 10%, excluding this, cost of sales grew 8.6%, in line with revenues. Operating expenses grew well below our revenue growth at 4.6%. Our cost equation looks at labor cost as a percentage of total income that continues to improve, falling from 30% to 28.1%. It is supported by our workforce in sourcing program, through which we are internalizing more of our talent and improving our agility and efficiency. As we continue to execute on that program, 77% of our headcount is now internal. We double click on the EBITDA margin expansion on the next slide. After adjusting for FX, the improvement in margin is 260 bps. 140 bps of this relates to the change we made to the SwapClear agreement last year, leaving 120 bps on of underlying margin expansion in H1. As you can see, this performance derived mostly from a disciplined management of the group labor cost helped by the strong market performance in Q1 that flowed to the EBITDA. On the 120 bps, I assess the group operating leverage at circa 80 bps and the slowdown to the market activity at 40 bps. So all in all, that delivers an H1 underlying margin of 52.4%, a very strong margin progression from the 49.8% in H1 last year. Let me now walk you through our margin expectation for the rest of the year. As you may have read in the RNS, we are raising our EBITDA margin guidance from 80 to 100 bps improvement to around 100 bps improvement in constant currency. Given the strong margin performance in H1, that implies a year-on-year slight decline of about 50 bps in EBITDA margin in H2. This is due to the mathematical impact of the swap tier revenue share change, which in 2025 was all booked in Q4. That creates a 70 bps headwind in H2. Aside from that, we expect to make continued strong underlying progress in operating leverage in line with H1. And we budgeted in H2 around GBP 25 million of one-off costs to accelerate the continued transformation of the group. Turning now to net finance expense. You can see that adjusted net finance expense was GBP 149 million this half. up from GBP 66 million in H1, 2025. Last year figure benefited from GBP 35 million of gain from a bond repurchase and the end of hedging instrument. The underlying increase was just under GBP 50 million and is mainly driven by the impact of higher global interest rates. Rates have typically been 300 basis points higher as we have refinanced over the last 12 months. We expect net finance expense to be similar in the second half, so a full year expense of around GBP 300 million. On the next slide, our tax rate is consistent with the 24% to 25% range we guided to, and that remains the right range for the rest of the year. Through that combination of top line strength, cost discipline and operating leverage, we delivered first half adjusted EPS of GBP 2.45 per share. You can see the strength of this performance for yourself with first half EPS up 17% year-on-year and representing 15% compound annual growth over the last 3 years. The significant allocation of capital to buybacks has seen EPS growth consistently outstrip profit growth. Now turning to nonunderlying items. This continued to reduce as expected with the amortization of intangible assets relating to the Refinitiv acquisition 5 years ago, the [ Manian ] onto cash flow, which grew very strongly, up 29% in H1 to GBP 1.2 billion. Large cash items like working capital and CapEx were unchanged year-on-year. So the big increase in our cash flow simply reflects our increased EBITDA, converting directly into our equity free cash flow. This is a cash-generative nature of our business model in action. And then ongoing buybacks means this 29% growth in free cash flow translates into a record 37% growth in free cash flow per share. We continue to be very active in our allocation of cash, which you can see on this slide. We returned GBP 2.6 billion to shareholders in H1, GBP 2.1 billion via buybacks and GBP 500 million through dividends. We pushed particularly hard on the buybacks, given the dislocation we saw in our share price for much of the first half. We plan to execute a further GBP 1.4 billion in share buybacks by the time of our full year results in February 2027. And just today, we have kicked off the latest tranche of this buyback. With our results today, we announced a 17% increase in our interim dividend to 0.55 per share. consistent with our progressive dividend policy. Shortly after the period end, we reached agreement to acquire a further roughly 1% on of LSEG Group from minority shareholders for GBP 70 million. We expect that to complete in the second half. We ended June with net debt to EBITDA of 2.1x in the middle of our stated leverage range. We are very confident of delivering on all our financial guidance for 2026. At Q1, I said the very strong market performance meant it was likely our full year revenue growth would be in the upper half of our 6.5% to 7.5% guidance range. With strength continuing, we are formally raising guidance for revenues to grow between 7% and 7.5% this year. As explained earlier, I'm also raising our margin guidance and expect a full year improvement of around 100 bps and we are on track to deliver full year capital intensity of around 9.5% of total income and equity free cash flow of at least GBP 2.7 billion. So in conclusion, we are executing well on our strategy, and we are very confident of delivering on all our promises for 2026, aided by the multiyear contractual visibility and growth of our FDA agreements and the deep partnership we have with our customer. We are also confident in our medium-term delivery as laid out on this slide. Now I will hand back to David to talk more about our strategic progress, particularly in AI.

Thank you, MAP. A really strong financial performance in H1. As I mentioned at the start, I'm going to talk about how we are becoming an increasingly critical partner to our customers in data and analytics and how that is playing out in our customer engagements. First, a quick recap. The basic ingredients for AI are data, compute, i.e., chips and data centers and the model. What we can all see over recent months is that compute is an arms race, but ultimately driven by supply and demand. The model landscape is also shifting. Cheaper models are often open weight and are closing the performance gap on frontier models. Businesses will orchestrate and optimize. And as for data, data is more important than ever, making LSEG the enduring partner of choice in an AI world. 90% of our data revenues come from real time or data that is proprietary. We have always had unmatched global reach, as well as breadth and depth of data. We have, for decades, been embedded in customer workflows and are becoming more embedded, providing regulated, integrated and secure solutions. Our data is structured to optimize AI performance, driving repeatable and deterministic outcomes. And now we have added massive new distribution through our partnerships across the AI ecosystem. We are becoming an increasingly critical partner for the industry, much more than just a data provider. We are partnering with customers to design and implement multifaceted AI strategies with our data at the center of them and engineers from LSEG, Microsoft and AWS helping to deploy them. Our customers are facing complex challenges in adopting AI into their processes and workflows and the landscape is evolving rapidly. Let me highlight why LSEG is so well placed to help our customers navigate these challenges. First, regulation. The industry is already heavily regulated, and the pipeline of new regulation is growing day by day. In the appendix, we've produced a summary of the various regulations that govern the use of data in the financial services industry. It gives you a good sense of the regulatory weight and complexity our customers face. This is a core capability for us given our decades of experience supporting customers to manage regulatory risk and change. Next, cyber risk. The latest models are highlighting cybersecurity vulnerabilities in seconds. LSEG is already deeply embedded in the processes and systems of the world's biggest financial institutions and brings a critical market infrastructure mindset to the provision and protection of data, resilience and security are nonnegotiable. On IP protection. Customers are concerned about the risk of co-mingling their data in a multi-cloud or frontier model environment or giving away their thinking through their prompts. We have worked with customers confidential information for decades. They know we'll provide them our trusted data and work with their confidential information in a secure environment. Similarly, on AI sovereignty, global businesses need to maintain flexibility to use different models in different markets. Our open approach, model and platform agnostic meets that need, whether customers prefer to use an orchestration platform, combining multiple models or individual leading models, market by market. Accuracy, I think, speaks for itself. You all have experienced the limitations of even the best LLMs when based on Internet data, answers that are often incomplete inconsistent or made up. With our accurate, auditable and semantically linked data, you are getting the same output time after time. And finally, of course, token costs and ROI. A number of companies have spoken about the challenges emerging here. We can make a big difference in helping customers manage token spend. Partly, it's about being model-agnostic. So customers aren't using frontier models or simple prompts. And partly, it's the way our data is structured and presented to models, which reduces superfluous information and repeat tool class. Our Head of AI, Emily Print's recent log on this topic is worth a read for more detail on this. In summary, some have been too quick to project the rapid consumer adoption of AI chatbots where the dramatic impact AI has had on coding onto the enterprise AI space. As we've said before, our sector moved slowly. Given the range and complexity of issues to address, this is a marathon, not a sprint, and LSEG is the best running partner. Next, I want to give you a sense of how AI solutions are evolving. You may remember, we showed a diagram like this at the Innovation Forum last November. This framework continues to evolve. We've also shown on the right-hand side, the customer considerations at each level of the framework to tie into the previous slide. A couple of key points. One thing that hasn't changed, LSEG's trusted content from data, indices and analytics is a key foundation. On distribution, we are seeing larger customers, in particular, choose to leverage our existing distribution to bring data into their own AI stacks with MCP as an add-on in specific use cases. And then in the consumption layer, we are seeing a blurring of lines and an increasingly hybrid approach. Workspace is stretching beyond the core user interface. Customers are now looking to access it via the Microsoft Teams app, which will allow deep interoperability with Open Directory and other Microsoft products. And we're also working with some customers on what the software industry refers to as a headless approach, enabling them to access the intelligence and content of Workspace in any environment and UI-- you'll see that clearly from the case studies. Some customers are taking that hybrid approach to AI adoption, combining our UI with their own solutions and third-party platforms. To take stock on our progress with AI-ready data and product, let's start with MCP, where interest continues to be strong. We've engaged with over 200 customers on MCP since launch late last year with a good spread by geography, customer type and channel. Usage is really ramping up as customers, both humans and agents engage with the data. We saw tool calls increased nearly 5x from May to June, we were adding a lot more data over the next few months, which is a key ask from customers. And it is not just DNA. We're rolling out MCP access across the group, the FTSE Russell fixed income sandbox, which we demoed to you last year, is available via MCP and we're getting some good lead generation out of it. Broader FTSE data is coming soon. In our markets business, MCP will be a key interface or LSC24, which we announced last week, as we see agents playing a greater role in trading in the future. Now MCP is an important new distribution channel. But I should emphasize, it represents around 1/3 of our current AI-related commercial discussions. Although there's been a lot of focus on MCP as an AI channel, AI usage of our product is accessible by more than MCP. You'll see that shortly in the depth and breadth of our customer engagements. Turning now to Workspace. We have seen a very strong pace of development, both in AI and more widely. Our AI search tool is now generally available, rolled out to all Workspace customers during July. Although we have not marketed it widely to customers yet, we already have 17,000 active users with these numbers growing every day. For the deep research tool, which many of you have tried, the number of users has quadrupled from Q1. Both search and deep research are built on leading models. We're adding more data and enhancing workflows on both tools. We also have a third AI product in Workspace, company intelligence. This is actually the grandchild of meeting prep, the first prototype that came out of the Microsoft partnership and our customers really like it. We're seeing users pull 3,000 or so detailed company reports per week from multiple underlying sources. You can see examples of feedback on the right here, but we have much more and we get plenty of feedback asking for additional functionality, which just helps us make the product even better. But -- as you know, Workspace is way more than the AI tools we're building. It remains a critical workflow tool for traders and a rich source of community and data. And the impact of the enhancements we are making continues to scale. In H1, we've integrated the vast majority of FXL functionality into the platform, driving a 10% uplift in engagement. We've invested in the messaging function, which has 40,000 monthly active users. 1,000 customers are piloting our new private markets data sets. In H2, we'll be rolling out interoperability with Tradeweb. That work went into production this month. And as I mentioned earlier, Workspace is also breaking out of its traditional UI as we make its data, intelligence and tools available in customers' own environments as well as the Microsoft ecosystem. There's real product momentum with Microsoft. The Workspace app is already available in teams, offering all of the AI functionality of the main desktop and deep interoperability between the 2. It will shortly be available in copilot too, which is significant given the 1.5 million copilot users in our top 50 customers. Open Directory rollout is also continuing with over 20 customers onboarded. We're now using it as the default communications platform for new Tora OEMS customers with 3 signed up, and we'll make it interoperable with LSEG Messengers 40,000 active users in H2. So we've made significant investment and progress on the product side. The pace of innovation across LSEG is at its fastest for many years. This table lays out how we are monetizing this investment and this is likely to continue to evolve. We are out in the market with this framework today. In fact, customers are demanding it. While we are primarily focusing on adoption. Some customers really want to understand what the cost will be as they are signing up. For use of LSEG data in AI applications, the basic commercial model is an additional use case license. This is consistent with how we charge for data on any new or additional use case. Where customers take a bulk feed or stream data, we don't have instant visibility on usage. That's the category on the far left column, where customers are accessing data via API, either directly or through our MCP, that will attract an additional usage-based charge, as AI and MCP drive cross-sell, we expect customers to take additional data sets over time as well. For our Workspace AI tools, we're taking a slightly different approach. AI search is included in the Workspace subscription with the value reflected in the annual price review, but will also be subject to a fair use policy, reflecting a certain number of prompts per month. Above that, there will be additional usage-based charges. We are positioning deep research as a premium add-on with usage linked tiers. As you would expect, our pricing structure reflects our costs. These new products and use will drive additional cloud costs for LSEg. On the AI-ready data, we incur some data platform fees. And on the Workspace AI functionality, we incur token costs. These costs are fully factored into our midterm margin guidance. Let's look at how we are working with customers to implement their AI strategies. The first case study is a global bank with a long-standing enterprise agreement for LDA. We're working with them on multiple fronts, which will involve our own forward-deployed engineers. The customer is building a couple of platforms for different user groups that combine their own data with our data. One of these will help relationship managers prepare for meetings, bringing their own internal regulatory and product data together with LSEG News and Market Data. Another will help the banking and capital markets teams access deal intelligence and client-related news flow. We're also supporting them with MCP access to news, fundamentals and ownership for their wealth advisory business. As per the previous slide, we will monetize this through the AI license and the MCP capability license, including tiered pricing or consumption. Case Study 2 features our work with the sovereign wealth fund plan. We already provide them with significant foundational data to support investment management insights. Our new collaboration goes much further. We are combining our entity, symbology and ownership data with the customers' own data and other sources to underpin 3 specific use cases. a risk intelligence agent to identify emerging threats and potential portfolio impacts, a counterparty agent to help risk managers identify credit risk factors and a C-level dashboard, bringing together a number of sources of data and intelligence in 1 place for portfolio monitoring. We're delivering data both via MCP and directly through our existing API. And again, the commercial model reflects is, note that there is a separate and additional AI license for risk intelligence. And the third, a long-standing industrial customer, which may surprise some of you. We're helping them build FX hedging workloads, combining multiple data sources and AI and also providing treasury insights from structured and unstructured content. This example highlights the potential that our AI and data have for all companies, not just financial institutions and shows how supercharged distribution and usability can open up new markets for LSEG data. We picked 3 case studies. I could have shared a lot more of similar depth and breadth. They all demonstrate the value we're bringing to customers, the longevity of our relationships the importance of our trusted data in a highly regulated sector, our open and flexible approach and our platform agnostic stance to distribution. While these examples do leverage MCP, this is not just simple plug and play. These are complex, sophisticated and multilayered solutions and reflecting on the whole AI disruption story. The market has been debating these topics in great detail for the last 12 months and having what we could call the terminal value debate. In the appendix, we have addressed 5 common misconceptions about the future of our business in an AI world. You've heard us make many of these points in meetings and Q&A, but we have pulled them together in one place as a reference source. So to wrap up, financial performance is very strong with 8.4% organic revenue growth, accelerating subscription revenue growth, strongly improving margins, and 37% free cash flow per share growth. We're driving an unprecedented pace of innovation across the business. We will come back later in the year with a deeper dive on that innovation in markets. And we have returned GBP 2.6 billion or over 5% of our market cap to shareholders in H1 alone, with more to come in H2 starting today. But just as importantly, you'll notice today the clear shift we are driving in the AI debate based on what we are seeing day to day on the ground with hundreds of customers. AI and financial services can drive enormous value, but it comes with significant challenges for our customers. We are the trusted partner to help them address those challenges. We have the infrastructure, the data, the trust, the regulatory expertise and the institutional history. LSEG is even more valuable in an AI world. And now we will be happy to take your questions. Peregrine?

Thanks, David. [Operator Instructions]. Operator, over to you.

[Operator Instructions]. Your first question comes from the line of Andrew Lowe from Citi.

It's been a year since the AI disruption narrative really took hold. Could you please provide a little bit more color and specific examples about how LSEG has been affected by AI during the period. What are the biggest changes versus your expectations 12 months ago, both positively and negatively.

Thanks, Andy. So Really, the biggest issue by far has been dealing with the perception of the impact of AI versus the reality of the impact of AI. And really more recently, over the last couple of months, I think it's fair to say the level of understanding about AI's potential, what it's good at, what it's not good at. That has matured a lot. I think people now recognize that a frontier AI company is not a data provider, not directly providing what we do. In fact, it's now well understood that for an AI company to generate value for enterprise customers, it actually needs a high-quality provider of data like us. Over the past year, there has been speculation that AI would wipe out large parts of our business. And in fact, it's just the opposite. AI has enhanced the value of AI has increased the need for, and therefore, the value of our data because our data is verifiable, it's auditable and it's proprietary. And if you look at our performance, our performance demonstrates exactly that. If you compare where we are today versus a year ago, our new sales are 10% higher. Our retention is better. Our subscription revenue growth has accelerated to 6% and I'm sorry, from 6% last year to 6.3% now. So we're seeing more consumption of our data than ever before. We've got new distribution channels and new products. that we didn't have a year ago, and we're getting great traction with them with thousands of users. And we are more closely engaged with our customers than we were a year ago. We're creating value from that engagement. So -- that's why we talk about LSEG being a lot more valuable in an AI world. I think it is fair to say the world is moving faster today than a year ago, and it has been a challenge for our people to keep moving faster to really integrate Newtec into our products and processes and meet customer expectations in this really dynamic market. But I think we're really rising to that challenge very well. and I expect us to do that more and more and better and better going forward.

Your next question is from the line of Hubert Lam of Bank of America.

So going back to MCP. So how much can MCP add to growth going forward? Is MCP monetization incremental to that 7% subscription revenue target you offer next year? And if so, do you see upside to that now that MCP monetization is starting.

It's MAP. So I think we've said very clearly in Q1, and we are reiterating that our priority for this year and for the second semester, is to concentrate on usage. Our clients are still very much trying MCP very different use case. And for us, the most important is to make sure that we have the setup, which is the most powerful and valuable to them. So MCP for sure, will be monetized. And by the way, we are already sending some invoices because the client actually ask us to have a price framework for the rest of the year. But it's minimal. And we will see that more in 2027, but certainly, it won't move the needle in 2026.

It could move the needle in '27 then?

We'll discuss -- I mean, clearly, it's part it's part of the acceleration of our subscription businesses. So clearly, it's going to be 1 more engine to this acceleration.

And maybe, Hubert, the other point I would just add. Yes, the other point I would just add as we just went through in the presentation, is important, but it is really about 1/3 of the commercial discussions that we're having with our customers. So there are other aspects to this as well.

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

Just a question on the subscription businesses. we saw 6.3% revenue growth in the first half of this year. You guys are guiding to, I think, 6.5% for the full year. So we need to see another, let's call it, 30, 40 basis points of acceleration in the second half. So I was just wondering what you see the confidence that you'll get to what will get you to that 50 basis points of acceleration? And then just to clarify in your answer before, when it comes to subscription revenue growth, and the 50 basis points of acceleration in 2027. My understanding is that MCP and the like would be incremental to that, not included in that. But if you could just confirm that, that would be helpful.

So first on 2026, yes, you might -- your maths are right. So 6.3 in the first semester, acceleration to 6.7 million in the second semester. And as we said, circa 6.5 on the year. So we're very confident to reach this 6.5% for the year, fundamentally for 2 major reasons. One is that we had gross sales, which were at record [indiscernible], if you remember, in Q4 last year, and these gross sales are executed not only at the beginning of the year, but for some of them, in the second half of the year. So it's something that we already know. So it's giving us a good visibility on the installation pipeline over the coming quarters. And the second reason is that we have improve massively, as you've seen in David's presentation, our product lineup, not only for DNA, but for the 3 subscription businesses. So we have a far better product lineup. So the combination of better product and the pipe that we know is going to be executed in H2 is giving us this confidence. As for 2027, you want to comment David?

Sure, happy to. So Mike, with respect to 2027, the way this will play out is that we will see slow, steady adoption of these products and therefore, the revenue associated with that. So we don't expect and you shouldn't expect a big spike at any point. I think we've been really consistent about that in terms of how this business -- this industry works. But you have seen us very consistently turning the dial up over the last several reporting periods. You can hear MAP's confidence in terms of what this year will look like for subscription revenues, and we expect that to continue going forward with that kind of slow, steady adoption curve, if I can put it that way.

Your next question is from the line of Benjamin Goy of Deutsche Bank.

Also a question on the MCP Connector, please. I noted that the share of direct connections to LSEG has moved up again rather than via the LLM, just wondering whether it -- now the sales force is in place and you're pushing the product more directly? Or what is driving that? And yes, if that is a strategic target for you?

It's not something that we are pushing. It's really customer demand, and this is how we see the market evolving. There are some customers who want to access our data through MCP. And then there are other customers who may want to access some of our data via MCP and some of our data through other channels. They may want to take it through a regular API. They may want to access it in, for example, a Snowflake or Databricks environment. And we're just seeing this market continue to evolve and continue to develop. And this is, in many ways, one of the strengths of LSEG everywhere. We are in a position to serve our customers across the different channels they want to use to access our data. As I mentioned earlier, MCP is that channel in about 1/3 of our commercial discussions right now. And then to your point on direct versus other providers, that's also what we're seeing in the marketplace. In other words, a number of our customers are choosing to go direct instead of using 1 of these model channels. So this will continue to evolve. We'll continue to share with you all what we're seeing in the way that our customers want to access our data. But from our perspective, it's all good.

Your next question is from the line of Arnaud Giblat of BNP.

Just another question on MCP usage, 202 clients. It's a big number. I'm just wondering if if you could give us a bit of an indication as to what share of revenues these clients who are representative of your revenue base? I assume it's the largest clients who are adopting. And if I may, a quick follow-up. You highlighted OTC revenue growth being really strong I'm just wondering if you could pick out which areas are seeing within OTC seeing trocar contribution to that growth.

Sure. So I'll touch on the MCP question then MAP can answer your question -- your second question. It's actually all over the math in terms of the customers that we are seeing access our data via MCP and via these other channels that I'm talking about. And we have seen a number of our very large customers doing some interesting things, and we have mentioned this in one of the case studies. We're also seeing a lot of smaller funds, hedge funds, asset managers that are really interested in the product and accessing our data in this way. It's also really interesting to see -- it's not fully transparent to us, but we can tell pretty much which users of the data are humans versus agents. And it's very interesting to see the -- we've been -- I think you all asked us on one of the prior calls, what the differences were in terms of consumption of our data by agents versus humans, take this as Anec data. This is not scientific. But what we see so far is that agents tend to consume roughly 10x, roughly 10x the amount of data that humans do through the MCP channel. So I think it continues to evolve. And maybe the last point I would just reiterate is that MCP is, at this point, just about 1/3 of the AI access and the AI commercial discussions we have. So important, a great new distribution channel but part of what we're seeing and part of the opportunity set that we are taking advantage of with our customers.