Hello, everyone, and welcome back. I'm James Rose from Barclays Business Services team, and it's great to welcome back Experian to this forum. In these sessions throughout the years, Experian has showcased the evolution of its products and innovations across financial services, verticals, and consumer, and this year continues as we have some familiar faces presenting to us. Our agenda for today, we start off with Jeff Softley, North American CEO, to give an overview of strategy in North America. Then Keith Little, President in Software Solutions, and Vijay Mehta, Chief AI Officer, will update us on Ascend and other product developments. We then finish with a Q&A session with the team, and also Lloyd Pitchford, Group CFO, will be joining us for that. If you have questions, there is a Q&A button on your screen. Please send them in as we go, and I'll get right to them. Let's kick off. I'll hand over to Jeff Softley. Well, thank you, James. We really appreciate being in the forum. Good morning. Good afternoon. I'm excited today because today we're going to talk about how we're well-positioned to usher AI into the end markets that we serve and use it as a growth accelerant, not only for the North America business, but for the enterprise at large, particularly during a moment of significant technological transformation. I'm also going to offer some tangible examples of the progress that we're making today against those key strategic initiatives. Rich, let's move to the next slide. So in North America, we have a strong track record of growth, and I think what's important to call out is that growth's been consistent through up cycles, through down cycles, through broader technological transformation. Where we sit today, we see a clear path to a $10 billion business given our portfolio, the assets we have, and also the market expanding opportunities that we see present with AI. I want to be really clear about this. We see AI as an accelerant. We believe we have structural advantages. Some of those advantages include the unique and proprietary data set that we have, our platforms, which are ubiquitous in their end market positions. Of course, we're cloud-native, which sets us up well to be positioned for an AI environment. Of course, nobody has a stronger track record of innovation in our space. Again, we'll be continuing in that theme by showcasing some demos of that today. Let's go to the next slide. To achieve $10 billion in growth, you have to have large accessible markets and headroom for that growth. Put very directly, we see AI as expanding our TAM. We have the proprietary data, which I mentioned, as well as, and critically important, a trust layer that enables our clients, our partners, and the consumers that we serve to take advantage of this technology at scale. We do see some tangible examples of how AI expands our total addressable market, and we have highlighted a few here that we have spoken about, and again, we will be giving updates related to the progress of each of these initiatives going forward. First and foremost, we are using AI to disrupt existing spaces. Our Health product, our Patient Access Curator, is probably our best example of that. It is infused into our product and our end market. It is our largest scaled AI product in market across the healthcare system. We have also talked a lot about agentic commerce and creating new markets with AI. Of course, we have launched our Agent Trust Coalition. This allows us to connect agents to humans so that agentic commerce can take flight. We are driving new use cases with our data and our capabilities, and Agent Trust is a great example of that. It is also a moment where we are leveraging new distribution. Of course, a great example of this will be our consumer marketplaces. We see AI as creating accretive opportunities and use cases for consumers to find and explore financial products, and we intend to be in those spaces where consumers explore the financial products that are available for them, and we see the distribution as an accretive opportunity for us. I think it is also important to say that the secular trends behind these markets play to our advantage. We know AI creates more demand for compliant, explainable data and outcomes. Of course, we are well through the digital transition and transformation. Again, we are well-placed in that. It is also important to highlight that there is more consumer empowerment. Consumers have more options, more choices, and smarter ways to find products which we intend to fuel. AI is also a moment where there are completely new sets of data that we can lean into. In summary, we see billions of dollars of accessible further TAM in emergent AI use cases. Our job, and what we will showcase to you today, is to not only explore those opportunities to be a front runner and built into the foundation of those markets as they develop. Let us go to the next slide. Now, we have a long history of innovation across our business. As we have said, we operate in five key ecosystems, from Financial Services, Marketing, Consumer Services, Health, and Auto. In each of these five ecosystems that we serve, we have billions of dollars of potential to be realized through this new product innovation. In Financial Services, Vijay and Keith will speak about some of the enhancements and demo some of the capabilities that we have built specifically in Financial Services. I also want to highlight one of the other items here, which is cash flow. Lenders are looking for more data to make better lending decisions. Put bluntly, they are looking for a competitive advantage. We are uniquely positioned to provide cash flow data and new scores which incorporate cash flow, and we are doing exactly that. How are we doing it? We are leaning into the totality of the portfolio that we have to build capabilities that we are uniquely positioned to build. Our cash flow offering, it's fundamentally trained and built off of the data that we've collected through our Experian Boost proposition in our consumer business. It's one great example of how the broad portfolio in key foundational assets that we have can be used and combined to create innovation and game-changing offerings. We have more than 60 clients in our pipeline for cash flow. It's a key bet that we are making and a growth vector for us going forward. I also want to talk about verification. We've long talked about our focus in the verification end market and offering. I want to tell you today, we are very confident in delivering strong record count growth this year. As we've consistently said, it's a question of when, not if, a large payroll provider goes non-exclusive. I'm more confident than I've ever been that we will see substantial record growth this year. Further, we're confident in our ability to find alternative means to get to even richer and broader data sets that will accelerate our verification business. In our Consumer Services business, we've expanded into mortgage. A third of all house purchases in North America originate from our consumer member base. That gives us a great vantage point and position to create and tap into that value pool as we extend our product. In our Automotive business, we've made significant traction in our online marketplaces and our vehicle history products. We've shared, and we'll share again, that we've covered more than 90% of the online marketplaces within the U.S. They have shifted from a competitor into our vehicle history product. This includes all the providers that you would think about, the brand names such as Amazon Autos, Kelley Blue Book, Autotrader, Cars.com. That gives us a fantastic position to go after new value pools, specifically around marketing, as well as some other interesting ideas that we have to pursue now that we've got this broad market coverage. In all of these cases, our innovation is bolstered by the totality of capabilities that we can bring together across the enterprise. Again, we're unique in that we've got a position in B2C as well as a position in B2B. Let's move to the next slide. We've got one of the most proprietary and scaled data estates globally. AI requires data. It's a key ingredient needed to unlock the potential of this technology. Put simply, our data is becoming more important. Again, one of the largest global proprietary data sources in the world that's very hard to replicate. It is most certainly a moat for us. Critically, it's diverse, it's broad, and it's reinforcing. Underneath, identity underlies all of our data sets, enabling the most comprehensive view of a consumer possible. In our Financial Services business, we have more than 250 million consumers covered in our core credit database. That data is secured from 12,000 furnishers. It's 3.1 billion trade lines. We have 1 billion updates monthly to that data set. We have 24 years of history. It's bolstered by 67 million unique consumers in our Clarity business, our alternative finance business. Further, we have direct relationships with 18 million consumers who are directly contributing daily transaction-level data through our Consumer business and consumer permissioning. That gives us fantastic view and scope of view around consumers. We also have longitudinal depth. We have a time series of information. We have regulatory lineage, cross-domain linkages that allow us to bring credit, fraud, identity, and commercial data sets together. I also want to highlight that we have continued to build on this data estate. We recently announced the acquisition of AtData. This brings 20-years plus of email intelligence into our ecosystem. It has 10 billion email addresses. It covers 98% of North America. Critically, we get 125 billion email activity signals monthly from this data set. That is fantastic in terms of our ability to create innovation, both in credit fraud, but really across the whole portfolio, including Marketing Services and even the Consumer business. Data is and will continue to be a key strength of the business. It is also a moat that we will continue to build upon. Let's go to the next slide. Now, I wanted to dive a little bit deeper in Financial Services. Obviously, it is the roots of our business. I want to highlight some of the key progress, as well as some of the key developments that have occurred recently. First and foremost, we have to talk about Ascend. Again, we will be demoing elements of our Risk OS later today. Importantly, AI makes Ascend even more critical for our consumers and more critical in our portfolio. Our customers are seeking new capabilities from us. They want to co-create with us, and they are choosing us to fuel their long-term strategies, and also to serve as the foundation for the AI capabilities that they build across the credit life cycle and across their teams. We have also highlighted that we have recently launched Risk OS. This is an agentic way for our clients to pull the value out of the Ascend data that we have and the capabilities that we have brought together. We are getting really positive early-stage client feedback, and then we are also beta testing with some key clients. We are also expanding these agentic capabilities with Ascend into operations such as marketing. We shipped our first alpha client with an agentic marketing suite. This allows our customers to use agents to optimize their marketing campaigns and to create a closed-loop ecosystem that allows them to push new models in the market at speeds that they have not achieved through any other platform. So we have a great install base with Ascend, and we are building great innovation on top of it, which will power it forward. I also want to highlight our recent renewal cycle. I know often the questions we get is, how are clients engaging with you? What questions are you getting from them? Do you see them buying more from you? I can adamantly say, not only are they buying more with us, but they are also extending their duration of their terms. We just had a very large renewal cycle in North America. We had 100% renewal success in that cycle. Not only did we renew at 100% success rate, but we did extend the contract duration by about 10% and over four years. So it is leading to a double-digit lift for us across contract value. We are also cross-selling. So it is a land and expand strategy. We've got great footprint in Ascend, and we're using the product innovation and the capabilities that we're rolling out across the platform to expand across more parts of the credit life cycle and functions within our clients. Lastly, I want to highlight, we've recently had a landmark win within our partner solutions business. This is a business that extends our white label capabilities from our Consumer business directly to our clients' customers. In this new deal, it's one of the largest and most important financial institutions in the U.S. It was a five-year agreement. It was very strategic in nature. It opens up tens of millions of dollars of annual revenue for us, and it's a unique bundle. I think it really demonstrates our clients in this moment where they need to accelerate their business and maximize the value that they're pulling from this AI technology, they're choosing to lean in with us. The proof is in the contracts that we have with our clients and our customers. Longer, more capabilities, and we're really seeing growth, which I think is the best positive sign we could ask for. Let's move to the next slide. Okay, so we've talked about AI offering an unprecedented opportunity for us to go after new value pools. I want to share some of our biggest opportunities that we see AI enabling. Importantly, these opportunities are real, and we are making progress at pace. Within our Consumer business, we view AI as proliferating new use cases into new ecosystems. We will be the marketplace that powers many of those new capabilities in new ecosystems. We've got an announcement later today, which I'll share as we get into a few more slides. We want to be where consumers are, exploring their financial health, as well as exploring the financial products that would be a good fit for them. We see embedding our marketplace capability into these new ecosystems as a key way to advance not only our growth, but to access accretive growth for the overall enterprise. There's been new value pools that we're getting in on the ground floor. Within agentic commerce, we have launched a coalition around Agent Trust. Fundamentally, what this does is it allows agentic commerce to take off and solve some of the key fundamental problems that underlie a capability like agentic commerce taking off. Fundamentally, you need to know that there's a good human behind a bot. You need an ecosystem and a payment chain which allows those good bots to get through. You also have to have a protocol that addresses first-party fraud as well as third-party fraud. We've solved all those problems in the coalition that we've built with Agent Trust, and I'll give you a bit of an update on the progress that we're making with the coalition in a few minutes. Of course, within our Health business, we see many of the blueprints and capabilities that we've used to build our Patient Access Curator offering, which is an AI native product. We believe we can bring that blueprint into the appeals space with an automated appeals offering. We're going to use AI to identify and maintain payer policies, to triage denied claims, and to assemble supporting claims. This is a use case which is very bespoke, but also very solvable with AI. What this does is it creates an appeals package for revenue cycle management staff, and it allows our clients to remove millions of dollars of costs and significant time across the hospital staff. We see many of the signals in the development of this product that means that it can be as broad scale and as growth-oriented as our Patient Access Curator product, which again is driving accretive growth across the Health business. Let's go to the next slide. Today, what we also want to do is demonstrate some of the real momentum that we're making with tangible evidence of the potential of our role and our growth potential within AI ecosystems. Make no mistake, the largest players across these new developing markets are choosing us. They're putting our capabilities into their ecosystem where financial services needs are being expressed. We're engaging in these platforms and these ecosystems in a way that secures our position. I want to talk through some of the tangible examples that demonstrate the real progress that we're making. First and foremost, in the Consumer business, we've said our strategy is to meet consumers where they are. In earlier stages of our partnership with the LLMs, we and others launched our apps within the LLM ecosystems. That was great. That was a way to engage consumers. But the fundamental challenge with that approach is that many of these ecosystems are still working through how discovery works and how apps are accessed. But what those app integrations have done is they've provided good signals of value to us, as well as value to the LLMs. We are now moving into a step change in the level of partnership that we have with these platforms. Our consumer offerings are going to be natively embedded in two of the top three LLMs imminently. We have some announcements that are coming. Those will be announced very shortly. We view this as a big step forward in our strategy to meet consumers everywhere, and it is a step change from how the rest of the market is engaging via app plugins that were previously announced. Additionally, it establishes our role. It builds us into a significant position in these ecosystems from which we can grow. It protects our position while also establishing a very clear growth plan for us going forward. As I said, we will be making some announcements imminently, but you can see through the stats, two of the three largest LLMs will be embedding our financial services, our financial health capabilities from our Consumer business within their platform. But we're not just stopping at consumer. In our Marketing Services business, we're also working with the LLMs to become part of their ad ecosystem. We're enabling elements of our Marketing Services business to be built into the core of their ecosystem so that they can connect consumers to brands. We're in advanced conversations to bring Experian's solutions to enable some LLM marketing use cases, particularly for an LLM that is building out their ad business as we speak. Agent Trust. I mentioned this is a big growth priority for us. We view this as a significant share of e-commerce in the future. But for that to take place, it needs to have a safe set of protocols that enable agentic commerce to occur. We have made great progress in the coalition that we have built so far. Through the CDNs that we have got into the coalition, we have more than 90% of the internet covered. That is important because it allows us to enable good bots, good agents to move through the ecosystem uninhibited. We have made great continued progress in the key payment rails providers and the companies in the coalition to help bring Experian Agent Trust to market. Today, I am really pleased to announce that JP Morgan Payments, Merchant Services, and Experian are launching an agentic commerce pilot with select merchants of theirs later this year, and we are going to be using Experian Agent Trust. Why is that important? Well, it is important because JP Morgan Payments enables 50% of the e-commerce market within the U.S. We are taking on real scale through the coalition that we are building, and we will be in pilot with our offering later this year. Patient Access Curator, we have updated you on some of the stats and some of the progress. We have had 100% revenue growth to date this fiscal year. We have got a strong pipeline with Patient Access Curator representing roughly a third of our opportunity funnel. So it is making significant inroads in our Health business, and we see no signs of the growth slowing. In fact, we see much more opportunity to scale this even further. I highlighted a big part of our consumer strategy is to be everywhere that consumers are. Today, I am really excited to announce that we have signed deals to embed the Experian Marketplace into two top neobanks within the U.S., as well as a top 10 media corporation within the U.S. What this means is that we will be fueling some of the largest publishers as they seek to monetize their platforms with marketplace offers. We will be meeting consumers where they are across the broader internet ecosystem, and we are really proud to be fueling that expansion with our partners. Last but not least, I did signal this at the beginning of the presentation. Huge progress we have made in our Auto business. 90% of vehicle marketplace ecosystems are running off of our vehicle history report. That is an incredibly strong position to expand into new value pools from this point forward. In all, you can see not only are we declaring where we are focused, but we are also making significant progress against each of these initiatives. More news to come, but we are really pleased with the progress that we have seen so far. Let us move to the next slide. I want to go a little bit deeper on Patient Access Curator. It is our largest scaled AI solution in revenue cycle management and healthcare. We just closed one of our largest quarters of implementation in our Health business, and this product was a big part of it. So what does it do? Well, the healthcare industry in the U.S. is complex. You know that if you live in the U.S. It is filled with human processes. It is full of errors. It requires insurance and eligibility experts to navigate the assignment of the right insurance to the right consumer for services to be rendered. Patient Access Curator makes that process simple. It uses AI to analyze previously successful eligibility, and then it uses those chains to take what is today a sequential process, which is prone to error and also very drawn out, and it allows it to be front-loaded into a single call that takes less than 30 seconds to go back to a healthcare provider. We have seen tremendous results with this product. It has decreased denials by as much as 30%, and it has also eliminated many of the contingency fees from third parties on the back end. That is significant to our healthcare clients. It matters, it makes a big impact, and we continue to see tons of headroom ahead of us for this product offering. Let us go to the next slide. I want to go a little bit deeper on the Consumer business, and talk about where we are headed and why we are headed there. Our Consumer business has been both a large part of our strategy, a unique part of our strategy, but also a huge growth enabler for us in North America and enterprise-wide. What we are doing is we are using a technological transformation to scale from a smaller and narrower business five years ago to a more diverse platform that we have today. If you were to look at our business 10 years ago, it was a very narrow business. It was defined by one product, we had limited distribution, we had a few million paying customers, our revenue was sub-scaled, and we were monetizing one single event, credit education. That kept us contained within a narrow, total addressable market. The way that we have defined the business today, we have truly scaled that product offering. We have got more than 35 products that we offer to our consumers, but we also offer those products through a variety of different distribution means. Certainly our direct business, where a customer can become a member of our offerings that we offer through experian.com and our own channel, but we have also scaled our partner services business. We have embedded financial health and identity services in the top 10 financial services providers in North America. That was a considered decision for us strategically. We knew that scaling the distribution into our partner solutions business and our clients would aid in the growth of this business overall. We have been able to scale our revenue from under $ 800 million to its current state today at $ 1.7 billion while we expanded distribution. That was a key strategic choice for us, and it has been an enabler for growth for us up to this point. We are going to continue to lean into that. Our strategy is to be everywhere that consumers are. You can certainly tell that from the announcements around our embedding of financial health capabilities into the LLMs going forward. We want to put our broad capabilities, particularly around regulated use cases, in all the ecosystems in which consumers are exploring their financial health. We have got a strong brand, and this powerful distribution enables us to further extend our footprint. It also, we believe, grows our total addressable market as consumers engage in more spaces and are engaging directly with our offerings. We are well on our way to embedding our unique capabilities in some of these high-growth channels. We also believe this creates synergistic product opportunities, where consumers will want to port their financial profile into more ecosystems. They will want to get the results that they seek in those ecosystems, and then they will look to control, enhance, and improve their financial profiles directly with us. Let's go to the next slide. Now, I am really proud of the position that we have built in the Consumer business. In the last 10 years, Experian has built one of the most comprehensive and unique set of products to help as many consumers as possible. Many of these products exist nowhere else, but they have been used by millions of consumers through us. Obviously, Experian Boost is a great example of that. 10 years post the launch of that product, it is the most scaled offering, and there is nothing like it in market. We have done similar things with insurance. We have innovated within our credit card marketplace with things like No Ding Decline. We have created an AI virtual assistant. We have also helped consumers in financial inclusion through products like Experian Go. Each of these products that we have built now give us optionality in terms of distribution and scaling this business going forward, given that we will be engaging consumers in broader ecosystems. What has this created? Well, it has created a business that has had really strong growth, but it has also created an awareness of our leadership position around the Consumer business. Brands want to offer the identity and financial health capabilities that we offer directly to our customers, and they choose us. Let's move to the next slide. All right. Obviously, we view AI as an accretive expansion opportunity that expands our market. Further, we think it is synergistic and is accelerated with broad distribution. I want to show how some of this comes together. We made a concerted decision several years ago that the Ascend capabilities and our matching offer, Activate, would be running both under our Consumer business but also accessible and enabled in our B2B business. What are we creating? Well, we are creating a foundation that has a common platform in which our Financial Services partners and other partners can access audience through any engagement point through the Ascend capabilities, which is leading in class, because we feel like that is a flywheel that enables this business to become more important to our clients, but also to offer more value to consumers. I have to highlight, we have got deep integration of Ascend across our partners. 15 out of the top 15 strategic accounts for us in North America have Ascend installed inside their platform. Those customers can activate audiences across our Consumer business with a click of a mouse. This is the strategy we have been building to. Distribution simply amplifies this strategy and this capability going forward. Makes us more important to our partners and clients, but also it makes us more ubiquitous with the consumers that we serve. We are making great progress in this strategy. It is also highly synergistic in terms of the signals that we will pick up from this ecosystem that will offer key insights that we can pipe back to our clients to enable a better understanding of customer intent. Also future steps and actions that our customers will be taking, particularly as our clients go after prospecting and growing their customer base. All right. Let's move to the next slide. I hope what you have taken from today is that we have got clear examples of progress happening across the business. We have had material advancement in our strategy. We have declared where we want to go. We are making progress against the areas we want to go. Fundamentally, if I leave you with one thing, we view AI as expanding the capabilities, the need for our capabilities across more ecosystems. That is happening in practice today. Our differentiated data enables us to play to our strength. We form a critical role in these new ecosystems as they are built out. We have got a great platform footprint across the end markets that we serve. We are cloud native. We have made that transition, which sets us up to play offense in this current market environment. And of course, we are going to continue piping world-class innovation through the capabilities and offerings that we bring to market. Truly, I believe there is significant headroom ahead of this business. We view AI as an enabler for us to achieve our $10 billion ambition. With that, I will pass over to Keith and Vijay, who can walk us through some of the specific examples. Great. Thanks, Jeff, and hi everyone. Thanks for the time today. As I said, myself and Vijay will try to bring the platform AI story to life for everyone on the call. If you go to the next slide, please, Richard. Firstly, Ascend, a little bit of a look back, but just to show about the journey. Ascend is our core platform strategy, bringing together many of our capabilities, initially focused in the B2B markets. As you just heard from Jeff, now obviously looking at that flywheel across the organization with our direct consumer and that sort of flywheel effect of the exhaust data from one feeding the other to get better outcomes for everyone across the customer base that we have. As you can see, we have been on a journey over the last four years. A lot of this journey is driven by two things, the innovation we see about where we see the market going, and also very closely listening to our clients. If you look back where we start, we had a number of capabilities across analytics, decisioning, and we brought those together with fraud as well and converged that platform. What we saw in the market was a change in the way that people were integrating data, particularly in Financial Services, and how to make the best decisions, to have all the capabilities of bringing in the various data sources and the richness of the data sources we have to make better decisions when bringing people together. Making sure those capabilities are fully integrated, this drove simplicity and took a lot of complexity away from our clients. Experian being in a unique position to be able to do that. We have been on a scaling journey, so that is both migrations and winning new business. As we brought that convergence story, that integration story to market, that has helped drive that scale, prove the adoption, as you say, cloud native and globally available in all the markets we operate. Of course, now we are in this sort of fourth generation, that GenAI transformation, that we see huge opportunity built on the foundation that we had. It is just worth, based on that, look at the time that we have built this capability and the growth of it, as you can see through the momentum in client solutions, the transactions, the activity around this. You also see that we formed a strategy. We had the ability to execute on this strategy in what is a very complex base. We listened to clients' needs, we innovated, and we have been recognized as leading in a number of areas. We have heard products. Jeff mentioned the Ascend Analytical Sandbox, a big anchor product to one of the things we do. Just one of those industry firsts that we sort of lead the market and we continued with that. Hopefully what we will show you today is how we think we can lead in the market around some of the GenAI capabilities that we are seeing and the traction that we are now beginning to see with our customers. With that, if you could pop to the next slide. Where are we going? We are very focused on clients' jobs to be done. Ultimately, how do we show them the value of what we can do and really drive those unique assets that we have? We talk about it in terms of data and decision intelligence through the Ascend Platform. What you can see here are the typical customer journeys our institutions that we work have, from finding clients, managing through onboarding them, managing through the life cycle, right the way through their entire sort of journey within a financial service provider. What is unique about Experian is we have capabilities that align completely across that customer journey. Our marketing, prospecting, and ways of engaging those customers. Our ability to obviously originate affordability, eligibility, et cetera, to bring those clients on board into the ecosystem. Manage those customers throughout their life cycle. So help and support our financial service to cross-sale and how they grow and maintain that portfolio right through to payments and collections. Of course, have a huge range of identity and verification services and fraud services that underpin all of this with the rapidly changing world of that. All of that powered by Ascend and all of that driven by the proprietary data and the breadth of data Jeff mentioned, obviously focused on North America, but all of our data sources, wherever we are in the organizations we bring. That is really important. This foundational level that we have built, the way that we are integrated with our customer workflows, the unique view that we see in terms of the data that we can bring together to help drive productivity and performance for our customers becomes critical. This is what sets us up really well for this AI world that we are in the middle of, and what we are going to show you today. Next slide, please. Focusing on the AI opportunity. This is a study we did recently of over 800 financial services businesses across the regions we operate in to really understand what our clients are thinking, to get underneath it. What we see, the highlights effectively, they see over 70% looking at faster, better decisions, more real-time, faster, more throughput, drive automation. Almost half see operational benefits, operational cost reduction, and a third see improved risk management, be able to do more pricing precision to be able to optimize more and more in terms of their operation. They are seeing the benefits that they see that they can get from AI. That has got to come together with that data and software. It is great to have that ambition. What you then see is where are they on that journey? As you can see here, very much sort of stuck, almost 70% stuck in that sort of experimentation, proof of concept, early adoption phases. We need to see what is driving them in terms of what is stopping them get into production and making those real benefits real for them. Next slide, Richard. We do not see the lack of ambition. When you look into the data and we speak to our clients and see what is going on, what is really going on here? Particularly in a regulatory world where obviously we operate, it is those regulatory constraints and the lack of trust, where their experiments and how do they make those real to get those benefits. It is a formation of a number of areas. The complexity of data integration, all the regulatory and compliance side of how that we make this real and make this safe for our customers, that they can be auditable, compliant for their regulators, and be able to pass back those compliance checks. This builds for that lack of trust. Where they are playing with, say, agents and automation driven by AI, if they are using it is in those very low-risk decisions. As you can see, that is where the majority of people are spending their time. The majority is in that very low space in terms of allowing that autonomy of our agents to make decisions. This is the piece that is the step that we think we can unlock. Why do we think we can do that? We have data. We have data that we can build that knowledge. We understand control, we understand regulation, and we understand data, and we have some of the best data so that we can start to bring that auditability, the repeatability, and start to build and maintain and allow our customers to be able to trust what they are doing and their experimentation with agents and AI. We are going to bring that to life shortly in a demo. Next slide, please, Richard. What this has led to is our strategy, something we launched a few months back called the Agent Operating System. What this is about is evolving the Ascend platform from the journey we have been on into enabling the AI agentic world for our customers. What you can see here at the heart of the picture is the core of the AI control plane that we call it. All the security, all the identity, all of the guardrails, all the compliance guardrails, immutable logging. Logging is there and can be assured and can be safely analyzed by security compliance to assure our clients, and we use this ourselves for our own use cases to make sure we are safe and we maintain that compliant view when we run these systems. We then have the layer, the semantic layer, the trust layer, we call it. This is where we are looking at using that proprietary data to really power our agents, to create knowledge graphs, identity graphs, and that understanding of our data in ways that agents and AI can really consume that data in a safe way, but also in a really performant way. Whatever we allow our agents to do and all the control planes that you have at the core, we make the best decisions for our customers and really make them perform. Those are at the heart, which we will bring together within Ascend, and we see that now evolving and growing since we started this about 18 months ago. On that journey from right to left, we can see some of the things that we have been doing. We have obviously been in market with Experian Assistant, so using this to drive value for customers to help them find and understand our data, to drive insights, and very much what many organizations have done. This has really been built within this core platform and enabled us to learn and understand that trust layer. We have got these in market. We have had them for significant periods of time. We have learned a lot to make sure we are safe. We are starting to adapt our tooling. Clearly in an AI world, the way that we have got to think about our software and that tooling has got to adapt and change to that world. Looking at how we build the tools for the next gen views about how we design workflows, we bring in big data integration, how we build agents, how we map that against where organizations are currently on their maturity journey with AI in that operation model and how we bring our data to them in a way through MCPs and all the registries that you typically have. Then things get really interesting in terms of how we look in terms of new markets, either expanding existing markets or new TAMs. In this case, in governance and control, we recently launched a product around model risk management, so compliance and how we think about helping our customers easily and more effectively and much more productively get their AI models into production and model their compliance processes. Now, building on that, we see regulatory horizon scanning capability and drive that change management across what is a really complex area for our customers to evolve around that GRC, that governance and control space. AI is really opening that up for us. We are then looking at that expansion further, with partner services and agents. You heard Jeff Softley talk about the Experian Agent Trust models. These are new TAMs, built within the platform that can enable us to get into markets we have never been before. The platform, the flexibility of what AI can enable and MCPs and agents start to talk about distribution and partnerships in different ways that we've never been able to do before, at a much more rapid rate because we have that platform space, and I'm going to talk a little bit about that later. One of the really interesting areas that we're now building and we're going to bring to life around client agents. Where can we really bring that intelligence for our customers to really drive that productivity and performance for them, drive real automation, and we're going to bring this to life. Richard, if you just go to the next slide, please. Thanks. Building on that, and before I hand over to Vijay to bring it to life, we see this as transformational for our market. We've traditionally had years of working with our data, with our tooling and our software, but we've never had that capability of really getting into that real intelligence level. Agents can allow us to enable that. Here's examples of some areas that we're working with customers and in the early phases of that client adoption. Around the types of agents that we can build that can help our customers drive through and search for that performance, drive productivity, and really optimize their solutions. You can see here governance agents to help drive those compliance and governance processes people have. Fraud and ID agents, Vijay will bring that one to life. Marketing agents, not just offering insights, but starting to really think much smarter in terms of how target customers, manage customers, cross-sell to customers, drive insights, and then credit risk agents in terms of how we look at operationalizing. Many of our financial institutions, the operations teams, quite large, complex, looking at all sorts of different information and how you can synthesize this. We see huge opportunity in this space and something our clients are really excited about as we look into it. Now, to bring that to life, I'm going to hand over to Vijay to take you through a fraud example. Over to you, Vijay. Thank you, Keith. Now, before we roll the demonstration and take you through the actual solution, I want you to just keep three things in mind. First, fraud is moving faster than human teams can respond. The moment a bank, a lender launches a new product, a new credit card, personal loan, fraudsters are testing it within hours. By the time a human can analyze and review the different patterns, update controls, the attack has already scaled. The bank is losing money and losing genuine customers. Next, Experian sits at the center of the data that exposes these attacks. We have identity, device, address, financial behavior, data on hundreds of millions of consumers across the globe. It's not a single data set, and it's not anything that a single lender can really have the exposure to. It is really about us being able to monitor and detect patterns and fraud rings forming across institutions simultaneously before anyone else can see them. Well, then third, what we are going to show you here is the Agent Operating System. The Agent Operating System in this example is about the use case, the fraud agentic use case and fraud prevention. The operating system, as Keith mentioned, has a lot of components to it, but we wanted to demonstrate that how we are turning our proprietary data assets into advantage in real time, and not just an automated response, but a true pattern detection, and really solving a real-world problem. With that, Richard, let us go ahead and start the demo. In this scenario, I am the fraud and identity operations lead at a regional bank. We have just launched a digital campaign for a travel rewards card. Applications are surging, and so is the fraud. My team cannot keep up manually. This is how Experian helps us respond. This is the agent studio on the Ascend platform, the environment where the bank's fraud and identity agents are built and maintained. Think of these agents as highly trained specialists. Each one is preloaded with Experian's knowledge, our fraud topologies, our identity verification logic, our understanding of how attacks evolve. The bank does not start from zero. It configures agents that already know what fraud looks like and refines them to reflect its own policies and the specific threats it is facing right now. For our travel card launch, I need two things working together. An agent that can spot coordinated fraud rings across many applicants at once, and one that can monitor the live application flow and respond when pattern shifts. I will show you both. I will open up the network intelligence agent. Its job is to look across all the applications coming into the bank and find hidden connections between them. Individual applications can look perfectly clean, genuine name, plausible address, reasonable credit history. But when you look across hundreds of applications at once, patterns emerge. The same device appearing under different identities, a cluster of applicants whose contact details overlap in ways that real customers would not. IP addresses that suggest a single organized operation rather than an independent individual. Experian can see these connections because our data spans the whole market, not just this one bank. We hold device data, IP address records, identity attributes, and address histories, all of which sit within Experian's proprietary data assets across hundreds of millions of consumers and thousands of lenders. A fraudster who has tested attacks at three other banks before arriving here shows up in our data. The regional bank, looking only at its own applications, would have no way of knowing. Here I can set the threshold at which the agent raises an alert. In this case, when 30 or more applications appear to be part of the same coordinated cluster, I have adjusted this based on our current risk appetite, and I save it. My agents are now configured but not yet active. Before anything goes live, the platform runs a validation. It tests my configuration against our historical application data and comes back with evidence-backed recommendations. In this case, it has spotted an unusually high concentration of applications from a single email domain that I had not yet accounted for. It recommends switching from a fixed count to a percentage, and it shows me exactly why. I review the evidence, I approve it, and only then does the change go live. This step matters for a specific reason. Banks operate under strict governance, risk, and compliance GRC frameworks. That means every change to a fraud or credit control must be explainable, must be approved by a human, and must leave a complete audit trail that stands up to regulatory scrutiny. This is where Experian's role is distinctive. We do not just supply the data or the model. We supply the governed deployment path. Experian brings the trust, governance, and regulatory track record built over decades of working inside regulated financial institutions. That means a lender can deploy an AI-driven agent into a live credit or fraud decision, knowing it will hold up by examination from a regulator. Because the controls, the audit trail, and the explainability are built in, not bolted on afterwards. Nothing goes live without that human approval. Every change is logged. Now that the agents are live, this is the monitoring dashboard. On the left, what is being watched. In the middle, what is happening right now. On the right, what the agents are recommending. I will start a live analysis, and let's watch what happens. As the agents detect fraud patterns, in this case, a cluster forming, where a group of applicants are sharing device and identity characteristics that suggest a coordinated attack, the system surfaces a recommended response. I review it and approve it. That updated control is live within minutes. Think about what this replaces. Previously, the bank's fraud analyst would need to notice something unusual in the data, pull a report, and analyze the patterns, write up a proposed rule change, get it approved through a governance process, and then push it to production. That process would have typically taken days, by which point the fraud ring has either succeeded or moved on to another lender. With Experian's Agent Operating System, the same outcome, a targeted evidence-based control change happens in minutes with a full audit trail and without the bank needing to expand its fraud team. The analyst is still in the loop, but their job shifts from doing the detection manually to supervising an agent that never stops watching. Because the agents are drawing on Experian's cross-institution data, they are catching patterns that the bank's own data alone would never reveal. After approval, I can see the full audit trail, exactly what changed, when, why it was recommended, and who approved it. What Experian has built here is something that did not previously exist for most lenders at this speed. A closed loop between data intelligence, automated recommendation, human approval, and live deployment with a complete record that satisfies the bank's internal governance and crucially, its regulators. Previously, a bank running manual fraud operations would have fragmented records across spreadsheets, emails, and policy documents. What the Agent OS does is it creates a single, searchable, time-stamped audit trail of every control decision, which reduces the burden on how compliance teams, and it means the banks can operate and demonstrate exactly how each decision was made. What you've just seen in that short demo was a real-world problem that lenders across the world face. They launch new products, and almost immediately, there is a fraud ring that is attacking. What we've designed is the Experian Agent Operating System to help ensure that that doesn't happen because we've unified our data assets and created a mesh or a knowledge base that allows for that linkage and real-time responses. The bank was able to approve more genuine customers. They were able to reduce their loss, and they were able to do this all without adding additional headcount. Finally, we've done this now with multiple customers. What we see is that automation and that simplicity allows for a lot of benefits across their organization. This is just one example, because we're also doing it across other areas. Three things really made this possible. First, it's speed and the patterns we were able to detect, making it evidence-based so we can explain it. Second is precision. This is where our advanced AI techniques come in and our ability to process data, look at clusters across different areas and different types of workloads. Then third, it's trust. Because we have that regulated proprietary data set that is validated and high quality, we're able to validate and test things that others aren't able to do. The same platform can extend across multiple areas. It's not just account opening. The Ascend platform can look at account takeover, transaction fraud, really the full customer life cycle. That's really what brings this to life. It's not just the data, not just the technology, but the ability to connect it all together in a way that a regulated lender can actually deploy it. Let's move to the next slide. Now, building on that theme of agentics and how we're leading the charge in the space, Jeff talked a bit about our Experian Agent Trust solution, and I'm going to take you through a bit of the details and then show you a brief demonstration of how it actually looks. Starting with some stats, this is a recent stat from Gartner, that the prediction is 25% of customer service interactions in banking will be handled by machine customers by 2029. My belief is that it's going to be much higher, and if we took the same survey next month, it would increase pretty rapidly. We do know that agent transactions are increasing, and consumers and businesses are becoming more and more comfortable with the exchange of information and the exchange of money. What we have with our Experian Agent Trust solution is an environment that is supporting that. Consumers are able to safely delegate shopping, payments, renewals, and financial decisions because we are providing the trust layer. Next slide, please. Without getting too technical, it's a five-layer system. At the bottom, we have our trust registry. This is a log of agents, AI agents, that have metadata and other behavioral aspects and attributes that we keep track of. The next layer is our partner ecosystem. Jeff mentioned this, but we're building a vast partner network, that includes everything from Visa to Bose. So it's on all sides of the entire process. The third area is our Experian Agent Trust token and our tokenization process. This is where we really get into some of the advanced algorithmic aspects of the solution. This allows us to create a tokenization scheme and bind that into various control sets. The next layer above that is our trust score. We are experts in building scores. It is very important that we provide this measurement or score within the process to ensure that both sides of the equation are validated and equal. Then the top is where we bind to a human. This is where it gets really pretty interesting because we are able to take the tokenization, combination of the trust score, the advanced tech in our partner ecosystem, and then delegate authority back into an agent. Next slide, please. Now, we are going to show you the demo, but I wanted to show you this slide because it demonstrates just the simplicity. The goal here and what we are building on is seamless integration for the consumer and simplicity across the entire process. Behind the scenes, when we show you the demo, you will see a lot of the telemetry and some of the details that are happening. Do know that the handshakes and all the security posturing is handled behind the scenes to ensure that we are providing that layer of trust. Let us take a look at the demo. [Presentation] As you can see in that demo, our goal is to build on top of our platform capabilities, be fully agentic, and provide that trust layer. With our Agent Operating System, we have those capabilities, and we are translating that into solutions like Experian Agent Trust, and there is a lot more to come on that front. Keith, over to you. Thanks, Vijay, and I hope those two examples brought the breadth of the innovation that we are doing in Experian, obviously leveraging Ascend and those foundations, but that innovation that we can spin off in that sort of the opportunity that AI gives us. If you go to the next slide, please. In terms of metrics, in terms of the platform, what is important here, we have obviously ranges of metrics. We spend a lot of time analyzing, finding out what our customers are doing. But these are really around those core areas about the activity. Are we seeing the activity growth? We are seeing that momentum that I talked about on the first slide, and that activity, whether that is the transaction volumes increasing, number of capabilities, and the time spent. The other is the engagement. When people are using the platform, our clients using the platform, we see it becoming intrinsic and embedded as a tool that they use day to day. On average, almost a third of their time is using this platform in their day-to-day world. We get very embedded and very deep into the workflows of our customers, which is extremely important for us strategically, and also shows that we are showing them that value, the value of the tooling and especially the value of our data, that they can drive their business forward. The next slide, please. Of course, listening to our clients as well. You see some quotes here from some of our customers about the approach, what we are looking at. We asked Forrester to do an independent survey with a number of our customers to make sure to see what the benefits they were getting, which were tangible. That means that the value is there. Customers are seeing the value, sort of proving out the thesis that we started with in terms of this strategy. Obviously really gratifying to see, but we think there is more with AI particularly. We think we can fuel that and give more productivity and performance for our customers. Next slide. Obviously, we spend a lot of time with analysts, and it is an extremely important area for us. We have sort of been engaging with the analysts across the breadth of what we are doing. What is really great to see is that analyst feedback. Obviously, a whole range of logos on here. But the important thing is firstly the breadth, back to the uniqueness that we have in Experian, that breadth of software capabilities for our customers and the amazing data that we have, the breadth of that proprietary data, plus the software to help engage. You remember, these analysts spend time with all of the competitors. They spend time with clients. It is great to see where we are positioned as leaders in innovation on all those awards that come through, and they are just getting more and more in the market. So having that client feedback, proof points of the benefits they are seeing, and then in terms of the analyst feedbacks, in terms of that direct comparison, their own views with their clients who obviously it is their business model, is gratifying to see. Next slide, please. One thing I hinted on when I was talking about the Agent Operating System sort of strategy was the partnering part and how the platform and particularly with AI, enables really interesting partner strategies for us. Here, we recently announced ServiceNow, end of April, where the puzzle we are looking at is we feel that many companies in the world, particularly regulated, but even beyond regulated, big industries, all require services that Experian has. Think of identity verification, hiring processes. Think of KYB, third-party risk management. There is a huge market out there that we are not even touching, and we are never likely to touch, obviously, with our focus on Financial Services. So who can best help us reach those areas we were never going to go after? ServiceNow is the first example. We are well down with conversations with other partners as well. But we are really excited about this partnership with ServiceNow, where we plug a number of use cases into their platform, and we call it agent to agent platform integration, first of its kind. We are also energizing their go-to-market motions as well. Their sales teams are motivated to sell our services. For them, they see the benefits of the enterprise workflows they are typically putting in around those sorts of use cases, having the ability to bring our intelligence adapters into those, across those identity verification, third-party risk management. Solves problems for their clients, helps them in terms of how they grow their business, and helps us get that distribution over 10,000 customers they have globally in those big enterprise areas they play across industries from pharmaceuticals, retail, telco, energy, utilities, areas that we would never get to. Really strong value exchange between us and them, and making sure client outcomes are great. We are super excited about ServiceNow, but we see this as the first of a number of partnerships that we want to do. Each of these platforms, these big players in these spaces, have different subtle approach in terms of the way the use cases and the workflows they work in. Really enables us then to tune the services we have into their market. Really excited about what Ascend and the Agent Operating System can open up for us in this area. Next slide, please. Lastly, just to finish off, couple of key messages. Ascend is not just a technology solution, this is a growth story. We believe that we can unlock trusted AI at scale for our clients and customers, for our financial institutions. Ascend is evolving into an AI native foundational product to innovate from, as you have seen today with the Agent Operating System and what our teams are building on it. We feel that market leadership, we really feel that we can redefine that financial institutions for a trusted agentic world, and we can go beyond the boundaries that we have typically been operating in. With that, James, end of presentation and hand back to you. Great. Thanks so much, Keith and Jeff and Vijay. There is quite a lot to unpick there, I think. I think relative to last year, we did not really talk about AI that much, and now it is embedded in almost every slide almost. Now we move to our Q&A section. It is great to welcome Lloyd Pitchford, Group CFO, for this part of the session as well. We have got a few questions in, but Lloyd, a starter for you, I think just to pull together everything we have heard so far. Quite clear in saying that AI is an accelerant, but if you put us in a historical framework, so as to say Experian has been through innovation cycles in Consumer when you first pushed out Ascend through Sandbox, et cetera. It seems like we are very much in another innovation cycle now. How do you frame where we are relative to the medium-term guidance which is out there at the moment? Well, thanks, James, and afternoon, everyone, and morning. It's great to be here again for another of these annual sessions. I think if I view your question through the lens of the many years that we've been doing this presentation, what you can see is a long history of enhancing our data assets, really mining actionable insights inside those data assets, and distributing those enhanced insights to ever greater embedded ecosystems. You can see each year we're pressing forward with enhancements across each of those bits of our value chain. What we've seen with technology, when technology change has come, it's allowed us to generate more data, to see more data, but also to accelerate the ability to identify actionable insights. We think AI is no different from that. You can see how quickly we've moved to be able to deploy this tooling on top of our platforms. Each one of our businesses, as you know, is on a journey from a capability to a product to a platform, and enhancing the platforms that we're developing with agentic and AI capability enables us to add more value to clients, and to ultimately be able to provide more of our data into their processes. The value cases, I think, to our clients are getting clearer. You saw that last year with our renewals across our largest clients. I think Jeff's slide that he presented shows you that across all of these areas, the largest, most foot forward innovating companies are choosing us to partner with. All this gives us a lot of confidence into the future. We clearly have very large and expanding TAMs that we're looking to grow into, and a lot of confidence that we'll continue to deliver over the next two and a bit years on the second half of our midterm framework, and a lot of upside opportunity to deliver on beyond that. For now at least, it looks like we should be still sticking to high single digit organic, but with optionality at least that everything which has been discussed so far could push us to the upper end of that, maybe. Yeah. No change to our midterm guidance. You would not expect me to say anything different. I think, against the background of questions about, is this technology change a risk or an opportunity, what you can see is we are very foot forward and particularly, some of the most innovative companies are choosing us to partner with. I think Jeff said it well, our goal is to meet all of our clients and all of the consumers wherever they are, and those distribution channels are really expanding at the moment, and we plan to be in all of them. Great. Thanks, Lloyd. Jeff, if I can go to you, and we will talk through consumer. I appreciate the announcement that soon there is going to be a native offering within, I think, two of the three big LLMs. Can you talk through how you think that changes or evolves the revenue model of the Consumer business overall? We are very used to it going direct through the Experian app, but it sounds like that is going to change in the future. Yeah. Well, I think, James, it is important to highlight our strategy and what our strategy has been really over the midterm with the Consumer business. We took a key decision that we wanted to embed our capabilities within our financial services partners. We view that as reinforcing to our consumer offering at scale. It is critical to say that our brand shows up adjacent and within some of the largest financial services brands, and the offerings that they provide to their customers. There is real value in that. So, we have a few different models, and those models are tried and tested. One of the models in which we have integrated with partners is to enable our membership to be accessible within broader ecosystems. We got a great example of that through the partnership we did with Chime, which is one of the largest neobanks within the North America market. Within that partnership, consumers can access their credit information within the Chime experience. They can also permission data for Boost. All of that is on the table as we explore these new high growth channels for us. In that instance, the monetization is quite direct in that it creates a relationship directly for us in our direct-to-consumer business as consumers interact with membership capabilities in broader ecosystems. That has produced some of the lowest cost to acquire customers historically across our business. As well as a clear view of what the lifetime value is of the customers acquired through that model. We also have other models that exist in the business, and that has been tried and tested, and that looks more like our partner solutions offering where clients pay us to enable core capabilities within their ecosystem. We have been very clear that to interact with certain product features with us, you will need to create an account directly with Experian. Critically, I would say, the LLMs do not want to get into regulated spaces. They understand our role and the value that we deliver within regulated spaces. I think through the conversations and the announcements that are forthcoming, you will see that it is a symbiotic relationship that we have established, that we think is a growth enabler for the business as we meet consumers in new and accretive spaces where they are exploring their financial health. Sounds great. Recently, consumer margins have been scaling pretty rapidly. Are we still on that trajectory? Yeah. I think none of our guidance has changed with respect to the Consumer business. Again, we have got a diverse set of business models within the Consumer business, whether it is partner, subscription, marketplace, et cetera. We have got real flex, real optionality. Really, I think the biggest enabler for us has been building the customer base that we have built and expanded and scaled. That provides optionality for us. It provides optionality around investments we want to make. We would expect and anticipate that these new channels that we are exploring have very attractive cost to acquire customers embedded within them. We believe we got significant lifetime value creation enabled through the partnerships that can really help continue to scale the business into its next and continued growth cycle. Great. Thank you. We get quite a few questions on these broadening competitive environments, perhaps in consumer, which AI enables. If we look at the current growth rate in consumer across marketplace and premium, notwithstanding data breaches, it is perhaps a little lower than what we have come to expect. Do you see any signs of that being linked to a changing competitive environment or market share in originations, for example? What is your take on that? No, I think when you unpack the growth in the Consumer business, you mentioned there, James, we got a challenging comp in the breach component of the business. The trends that we see within Consumer, when we look at monthly active users, et cetera, globally we've been consistent in our monthly active users. So we see consistent pacing and trending. We have had some specific lender exposure elements and/or specific verticals within Marketplace where we've seen lower activity. Again, we think that's been backed up by what we see from lenders, and in particular the lenders within our panel. But I think those are the signals that we've picked up and that we see across the business consistent with kind of one-time irregularities, particularly around the panel. Okay, thank you. If we can move to Ascend, and I think I'll start with what I hope at least is a basic question first. The way the demo was framed and the way you framed Ascend being AI native, essentially, does that mean from a customer's perspective, it's going to be a human, your customer, who is using agents which are built in and controlled within Ascend, as opposed to the agents of the bank as such, be they created through Copilot or coworker being connected to Ascend? Is there a distinction there? Maybe I'll take that, James. So yeah, we'll look at various patterns. But effectively, the platform, that ecosystem, that the Agent Operating System allows you to build your own agents within that environment. So it allows customers to build agents within that customer, doing whatever they want those agents to do, consuming resources and data from ourselves. And obviously, the examples we're bringing to life, you saw those various personas and you saw the demo that Vijay talked, is really to bring it to life for our customers, because this is very new. People are talking about the agent-human interaction. Obviously you saw the human in the loop controls within place. But effectively the platform ultimately is capable of those integration patterns so people can build their agents, which is what we want our customers to build their agents on our platform. And we see that as something popular because where we've got to and so fast and ahead of the market, none of the competitors have got this capability today. So that's what we're seeing in customers at the moment. They want to engage. They want to see, they want to build agents, test out agents, and see how they do. And obviously compliance and that trust layer is so super important and obviously going to test that perspective. And what they really like and resonate with is, we build for our direct-to-consumer business which is regulated. There's production agents that we've drunk our own champagne as it were. So they like that. That gives them confidence and again, helps that engagement. Okay. Could you give us some guidance as to when you would expect this product to be rolled out a bit more broadly across the banks or financial services? Mostly it is available at the core part of the platform, so it is available wherever the platform is. Obviously it is in early stages and what we want to do is to make sure we have solutions out there. We are in an early adoption phase with many large organizations, that is probably all I can really say, we are starting to look to build agents with. There are some, I guess low-hanging fruit agents, for want of a better word. I mentioned the operations agent, which is if you think about case workers within fraud or within credit teams within our customers, there is a huge amount of that synthesizing of data where somebody is referred for a credit check or a fraud referral it goes to. Using agents to synthesize all of that data to come up with recommendations for that agent we are seeing a huge, huge productivity benefit. We have real agents live in production in one or two of our regions looking at both credit and fraud use cases around those operations agents. That is real. The intention of course is that we will be rolling out and scaling that over the coming year. I think I would add James, if you look back and draw a line from where we have been to where we are going, what you are seeing here is waves of innovation on top of the Ascend platform. Some of the demos you see are things that we have been working on and we have had client engagement with now for a little while. The things that we are working on that we will demo to clients at our conferences, big client conferences in the U.S. and the U.K. are in October and November, are the next stage beyond this. The early client reaction is the opportunity for very significant improvements in operating efficiency and productivity for them. If you think about the promise of what AI can do in terms of productivity, every CFO out there is being asked how it will improve productivity. We're a route to that productivity gain for our largest, most complex clients. The promise of agentic workflow in these heavily people-intensive areas, offers a very material value creation opportunity for our clients that we're racing to deliver. When it comes to capturing that value and trying to monetize this product and innovation you've got, how are you going to do that through the contract structures you currently have? Keith? Yeah. I guess we see the value is increasingly to our customers, how we think about that. Ultimately, we're going to have consumption, is going to be a part of that as we move to more consumption-based models, and we're working through how we want to do that. It's really about the value that our customers see driving from that sort of intelligence that we're bringing. Again, we see significant opportunity for the value for our clients, which we feel we can obviously monetize in a couple of ways. Obviously consumption-driven. You saw Vijay and the example he gave, the way that the fraud agent consumes data, and the way it acts in terms of synthesizing that data to drive that productivity at speed. Yeah, we see huge value to our customers and therefore, we feel that monetizing that gives us some good opportunities. From a potential cost standpoint, it is perfectly plausible that once you unleash agents, at least, then you could get quite a lot more volumes coming through the system. With agents within Ascend, does that come with a fairly high incremental cost in terms of your tokenization usage? The broad question is, do you expect this to be a high return on investment product for you? I will take that, Keith. We expect it to be a very high return on investment. Exactly how clients use it and engage with it, and exactly how that use scales different factors of production, including tokens and cloud usage, is still to be proven out. But you would imagine that we are well adept at learning into our new products on top of variable cost. We have got a lot of telemetry in the system to make sure that we can hone that. The potential value creation for our clients of using some of these is really very material. Obviously, we will make sure that we get our fair share of that value creation. To carry on the theme of this conversation, but come at it from a different angle. I think it is fair to say there is still quite a bit of concern in the broader market around AI, as well as potential opportunities. AI lowers the barrier to entry for coding of software. But are there any signs that your customers are less interested than they were before in the analytical tools, that they would just prefer to have data from you, and then they can push it through their own systems? I will maybe kick that off and then pass to Jeff. The proof of the pudding you saw last year was our largest, most complex clients are buying more and contracting for longer. Everybody, as I just mentioned, is pressing for productivity improvements in their business, and we are a route to those productivity improvements. A lot of the value case for the things we do includes labor takeout, but also enhancing the top line. The fraud case that you heard about, fraud is ramping rapidly on the back of AI-enabled attack vectors. Being able to defend against AI-driven fraud with AI is a key driver of conversion and loss protection for the banks. Again, we are a route to enable them to do that. All of the engagement we are having with clients is really heavily in the acceleration of adoption. But, Jeff. Yeah, I think the most critical data point is we see clients leaning in in their contracts with us. Again, longer terms, more comprehensive in nature. That's the strongest signal that we're picking up from the market. I think if you think about the key folks we're interacting with across these organizations, they've got pressure to adapt AI into their capability set to realize the benefit associated with it. We think we can make a strong case that we are the fastest path to enable that, particularly when you see the capabilities in interoperability we can bring together with the demo that Vijay offered. If a route for a client is build elements on my own and hope that they're compliant and take on the burden of explainability. Build out within their own ecosystem versus take an installed platform that already exists inside their organization and is used and adopted at scale across many functions across the credit life cycle. They're gearing that direction because they want speed, and they also want to know that elements of enabling AI inside their organization are going to be enabled by Trust. That's the sort of relationship we have with clients. I think that I'd just add, if you think of what software is for us, it's a delivery mechanism of actionable insights. If you think about the thousands of users who sit on the Ascend platform, we're harvesting the signals of all of the use of the platform across that ever-increasing set of clients. Those signals are available essentially to enhance the product for everybody. We get a much broader view than anybody with a self-built product could ever have. Software really isn't the product. The product is the actionable insights that sit, that are delivered on the product. Great. Thanks so much for that. If we can move to Experian Agent Trust now. Great to see that there's announcements coming out soon about JP Morgan being involved. What stage is this offering currently at, and what's left to happen? What are the major hurdles that still need to be overcome before it can potentially scale quite rapidly? Sure. Well, I think the backdrop for us, James, is we believe agentic commerce will be a significant share of e-commerce in the future. As we've demoed, that was a demo, but we have bought Bose headphones through Agent Trust. We've run payments, and the tokenization through the full payment ecosystem end to end. We have some extra headphones around if you would like to buy one, or if you want one. I think the key for us in the JPMorgan Merchant Services pilot is that this is an organization that has 50% of e-commerce businesses enabled through their platform. We will be doing a pilot with them. We expect that pilot to launch this holiday season. I think that gives you a sense of some of the immediate traction that we think we can secure with Agent Trust in market. Now, of course, with any new capability like agentic commerce, there will be different adoption curves. Some of that's going to play out over time. But again, I think the signal to pick up through the inclusion of JP Morgan Merchant Services in the coalition and in the pilot is that again, the organization that provides merchant services for 50% of e-commerce in the U.S. believes that this capability is relevant, needed for their customers and also pilot worthy in a really important season, the retail season this year. It sounds like you've got a big focus on it and you're very excited about it. From an analyst modeling perspective, how excited should we be about it? Well, obviously we need growth to occur in adoption of agentic commerce. I think it's critical for us to get embedded and enabled, and we do have multiple monetization opportunities across the offering. There's elements that we highlighted, such as a trust score which we think is a highly valuable part of the coalition. It's essentially the flag that determines the risk around an agentic commerce coming through the full payment chain. We also know that it's a key loss point for many retailers is fraud. We think we'll take a commensurate position relative to the role that we're going to play in enabling agentic commerce. But again, we think we need the behavior to grow, the usage to grow. The good news is I think we got clear line of sight to landing with some live examples, again, in this calendar year through the pilot which I think will be a fantastic position for us to hold. I think it's very unlikely that one standard drives the entirety of agentic commerce, but we think that this is a key standard that has the backing of some really important brands across the full ecosystem chain in payments. Again, we think this will be one of the scaled ways in which agentic commerce will be enabled in the future. I was just going to ask about what else could potentially coexist with this offering. I mean, Mastercard seem to have their own version of this to a certain extent. What's your view on the competitive environment for this product? Yeah, I think we'll end up with a Venn diagram, James, of overlapping capabilities that have different concentration focal points across different parts of the ecosystem. I know there's been a lot of news around Mastercard. There's ongoing discussions with them as well. They're interested in integrating elements into Agent Trust. So I think everybody's placing a few bets. There's very few people who are placing a single-threaded bet around how agentic commerce scales. I think most people recognize that there's going to be different solutions for different ecosystems at play. Thank you so much. If I can jump back to Keith and the distribution partnerships you mentioned. We know about the ServiceNow. It sounds like there's more to come. Again, the question on degree of monetization, how that would work with a partner as opposed to if you had a direct contract, and to what degree could it expand your customer base, so your addressable market versus what, the sort of core base you have access to yourselves. Yeah. Obviously, we're not disclosing any numbers, but we see a material growth. When you look at the numbers, you look at the products, you look at the way that they're structuring their go-to market mechanism, the way they're being energized and motivated to sell our products as part of their suite, as part of their services. We're very excited about the sort of materiality there. You can look at the customers they have. I mentioned they've whatever, about 10,000 customers. What's interesting about ServiceNow is they very much focus on those big enterprise players, so they don't go to necessarily the long tail type customers like some of their competitors. The way that they operate their sales motion is very impressive and we're just really pleased to be aligned to them. So looking for some yes, material success, but we will see. That sounds good. On a completely different topic, there's been quite a few tweets recently in regards to the mortgage market, and there's been some today. The one from Mr. Pulte today says that he's having meetings with the bureaus this week to discuss tri-merge, bi-merge, even going to single reports. It's very clear he wants to get the cost of mortgage down for consumers. What's your response to those comments so far? So I'll maybe kick off and pass on to Jeff. Clearly, what you've seen over the last a year or so is a desire by the regulator to introduce more competition in the school market, and we welcome that. As you've seen with the announcement that we and our direct competitors have made in terms of pricing for VantageScore adoption, we're really supportive. We think that's the best route to lower the cost for consumers in North America, in the housing mortgage origination market. So we've been very supportive. We don't comment on individual interactions with the regulators, as you might expect, but we continue to be in active dialogue. I think if you look back over the last number of years, there have been a number of studies that have been done across lots of different agencies on different models. The conclusion that's been reached to date is that the benefits of consumers in the round are best served with the tri-bureau model, giving the best chance for as many consumers as possible to participate in the housing market. We think that's right. There are clearly other models that have been discussed, and we'll be in active dialogue with the agencies as discussions continue. I think as you know, it's a relatively modest bit of our business overall. When you started to see some of the price escalations, what, four years ago, it was about 3% of our overall revenue, this mortgage profiles in the U.S. Given some of the price rises, it's about 5%. About half of that 5% is just the pass through of the score royalty. A fairly modest overall piece of our business, but clearly an important one, and an important one to end consumers who are looking to purchase a house. We take it very seriously, interact with regulators in good faith, and I am sure that we will be an active participant in the progress to score competition with VantageScore. Jeff, anything you wanted to add? No. I think you covered it, Lloyd. That is great. Thank you very much. That is all we have got time for in terms of Q&A. That brings us to the end of today's session. I want to say a huge thank you to the Experian team and all the work that goes into their presentations. I will hand back over to Lloyd to close us out. Thanks, James, and thanks to the Experian team for the demos and the presentations. For investors on the call, hopefully you can see another wave of innovation and strategic progress, and the pace that we are executing on some of the strategic opportunities that we have, the embedding of AI into our tool sets, the expansion of the partnership and distribution opportunities across some of the new platform providers. Across it all, some of the largest and most complex and most innovative companies are choosing us to partner with in some of these areas, which I think is a really good signal. We look forward to updating everyone on current trading. This is more a strategy and product session, but we will update on current trading at our half year results in November. Given the waves of innovation we have, we are already working on the things that we might be able to show this time next year. The innovation engine continues. Appreciate everybody's time and attention.