Experian plc (EXPN) Earnings Call Transcript & Summary

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, continue that, and 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. [Operator Instructions]. But 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 has been consistent through up cycles, through down cycles, through broader technological transformation. And 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. And 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. And of course, nobody has a stronger track record of innovation in our space. And again, we'll be continuing in that theme by showcasing some demos of that today. Let's go to the next slide. Now to achieve $10 billion in growth, you have to have large accessible markets and headroom for that growth. And put very directly, we see AI as expanding our TAM. We've got 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. But we do see some tangible examples of how AI expands our total addressable market. And we've highlighted a few here that we've spoken about. And again, we'll be giving updates related to the progress of each of these initiatives going forward. First and foremost, we're using AI to disrupt existing spaces. Our health product, a Patient Access Curator is probably our best example of that. It's infused into our product in our end market. It's our largest scaled AI product in market across the health care system. We've also talked a lot about Agentic Commerce and creating new markets with AI. Of course, we've launched our Agent Trust coalition. This allows us to connect agents to humans so that Agentic Commerce can take flight. We're driving new use cases with our data and our capabilities and Agent Trust is a great example of that. It's also a moment where we're leveraging new distribution. And 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 is an accretive opportunity for us. I think it's 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're well through the digital transition and transformation. Again, we're well placed in that. It's also important to highlight that there's more consumer empowerment. Consumers have more options, more choices and smarter ways to find products, which we intend to fuel. And AI is also a moment where there's completely new sets of data that we can lean into. So in summary, we see billions of dollars of accessible further TAM in emerging AI use cases. And our job and what we'll showcase to you today is to not only explore those opportunities to be a frontrunner and built into the foundation of those markets as they develop. Let's go to the next slide. Now we have a long history of innovation across our business. As we've said, we operate in 5 key ecosystems from financial services, marketing, consumer services, health and auto. And in each of these 5 ecosystems that we serve, we have billions of dollars of potential to be realized through this new product innovation. Now in financial services, Vijay and Keith will speak about some of the enhancements and demo some of the capabilities that we've built specifically in financial services. But 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're looking for a competitive advantage. We're uniquely positioned to provide cash flow data and new scores, which incorporate cash flow, and we're doing exactly that. And how are we doing it? Well, we're leaning into the totality of the portfolio that we have to build capabilities that we're uniquely positioned to build. And 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 on the verification end market and offering. And 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 nonexclusive. 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. 1/3 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 Auto, Kelly Blue Book, Autotradercars.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. And 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. And AI requires data. It's a key ingredient needed to unlock the potential of this technology. And put simply, our data is becoming more important. Again, one of the largest global proprietary data sources in the world is very hard to replicate. It is most certainly a moat for us. And critically, it's diverse, it's broad and it's reinforcing. And 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. Now that data is secured from 12,000 furnishers, 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. But we also have longitudinal depth. We've got a time series of information. We've got 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've continued to build on this data estate. We recently announced the acquisition of [indiscernible] Data. This brings 20 years plus of e-mail intelligence into our ecosystem. It's got 10 billion e-mail addresses. It covers 98% of North America. And critically, we get 125 billion e-mail 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's also a moat that we will continue to build upon. Let's go to the next slide. And I want to dive a little bit deeper in financial services. Obviously, it's the roots of our business. And 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'll be demoing elements of our risk operating system 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're 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've also highlighted that we've recently launched [ RiskOS ]. 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 brought together. We're getting really positive early-stage client feedback. And then we're also beta testing with some key clients. We're 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've got a great installed base with Ascend, and we're building great innovation on top of it, which will power it forward. I also want to highlight our recent renewal cycle. So 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? And I can adamantly say, not only are they buying more with us, but they're 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. And not only did we renew at 100% success rate, but we did extend the contract duration by about 10% and over 4 years. So it's leading to a double-digit lift for us across contract value. And we're also cross-selling. So it's a land-and-expand strategy. We've got a 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. And lastly, I want to highlight, we recently had a landmark win within our Partner Solutions business. So this is a business that extends our white label capabilities from our consumer business directly to our clients' customers. And in this new deal, it's one of the largest and most important financial institutions in the U.S. It was a 5-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. And 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. And 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. And 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. So 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 Agent 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. And 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. And 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 appeal package for revenue cycle management staff, and it allows our clients to remove millions of dollars of costs in 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. Now 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. And 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. And we're engaging in these platforms and these ecosystems in a way that secures our position. And 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. Now 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 2 of the top 3 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 plug-ins that were previously announced. Additionally, it establishes our role. It builds us into a significant position in these ecosystems from which we can grow. And 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, 2 of the 3 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 experience 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've built so far. Through the CDNs that we've got into the coalition, we have more than 90% of the Internet covered. That's important because it allows us to enable good bots, good agents to move through the ecosystem uninhibited. We've made great continued progress in the key payment rails providers and the companies in the coalition to help bring Agent Trust to market. And today, I'm really pleased to announce that JPMorgan Payments, Merchant Services and Experian are launching an Agentic Commerce pilot with select merchants of theirs later this year, and we're going to be using Agent Trust. Now why is that important? Well, it's important because JPMorgan Payments enables 50% of the e-commerce market within the U.S. We are taking on real scale through the coalition that we're building, and we will be in pilot with our offering later this year. Now Patient Access Curator. We've updated you on some of the stats and some of the progress. We've had 100% revenue growth to date this fiscal year. We've got a strong pipeline with Patient Access Curator representing roughly 1/3 of our opportunity funnel. So it's 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'm really excited to announce that we signed deals to embed the Experian consumer marketplace into 2 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're really proud to be fueling that expansion with our partners. And last but not least, I did signal this at the beginning of the presentation, huge progress we've 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. So in all, you can see not only are we declaring where we're focused, but we're also making significant progress against each of these initiatives. More news to come, but we're really pleased with the progress that we've seen so far. Let's move to the next slide. I want to go a little bit deeper in Patient Access Curator. It is our largest scaled AI solution in revenue cycle management in health care. 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 health care industry in the U.S. is complex. You know that if you live in the U.S. It's filled with human processes. It's 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. And what Patient Access Curator does is it 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 health care provider. We've seen tremendous results with this product. It's decreased denials by as much as 30%, and it's also eliminated many of the contingency fees from third parties on the back end. That is significant to our health care clients. It matters. It makes a big impact, and we continue to see tons of headroom ahead of us for this product offering. Let's go to the next slide. All right. So I want to go a little bit deeper on the consumer business and talk about where we're headed and why we're headed there. So 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. And what we're doing is we're using a technological transformation to scale from a smaller and narrower business 5 years ago to a more diverse platform that we have today. And 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 subscaled. And we were monetizing one single event, credit education. That kept us contained within a narrow total addressable market. The way that we've defined the business today, we've truly scaled that product offering. We've 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've also scaled our partner services business. We've 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. And we've 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's been an enabler for growth for us up to this point. We're 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 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've 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. So we're 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 want to get the results that they seek in those ecosystems and then they'll look to control, enhance and improve their financial profiles directly with us. Let's go to the next slide. Now I'm really proud of the position that we've 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. And many of these products exist nowhere else, but they've 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's nothing like it in market. We've done similar things with insurance. We've innovated within our credit card marketplace with things like [indiscernible] decline. We've created an AI virtual assistant. We've also helped consumers in financial inclusion through products like [ Experian Go ]. Each of these products that we've built now give us optionality in terms of distribution and scaling this business going forward, given that we'll be engaging consumers in broader ecosystems. What has this created? Well, it's created a business that has really -- has had really strong growth, but it's 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. So obviously, we view AI as an accretive expansion opportunity that expands our market. Further, we think it's synergistic and is accelerated with broad distribution. And I want to show kind of 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're 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's 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've 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've 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. So we're making great progress in this strategy. It's 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 but 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. So I hope what you've taken from today is that we've got clear examples of progress happening across the business. We have had material advancement in our strategy. We've 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's 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're built out. We've got a great platform footprint across the end markets that we serve. We're cloud native. We've made that transition, which sets us up to play offense in this current market environment. And of course, we're going to continue piping world-class innovation through the capabilities and offerings that we bring to market. Truly, I believe there's significant headroom ahead of this business, and we view AI as an enabler for us to achieve our $10 billion ambition. And 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. So if you go to the next slide, please, Richard. So 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. But as you just heard from Jeff, now obviously looking at that flywheel across the organization with our direct-to-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've been on a journey over the last sort of 4 years. And a lot of this journey is driven by 2 things: the innovation we see about where we see the market going and also very closely listening to our clients. So 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 converge that platform because what we saw in the market was a change in the way that people are 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 and Experian being in a unique position to be able to do that. We've been on a scaling journey. So that's both migrations and winning new business. So as we brought that convergence story, that integration story to market, that's helped drive that scale, prove the adoption, as I say, cloud native and globally available in all the markets we operate. And of course, now we're in this sort of fourth generation, that GenAI transformation that we see huge opportunity built on the foundation that we had. I think it's just worth based on that, look at the time that we've 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 the -- we formed a strategy. We had the ability to execute on this strategy in what is a very complex space. We listened to clients' needs. We innovated and we've been recognized as leading in a number of areas. We've heard products. Jeff mentioned the Ascend 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 continue with that. And hopefully, what we'll show you today is how we think we can lead in the market around some of the GenAI capabilities that we're seeing and the traction that we're now beginning to see with our customers. So with that, if you could pop to the next slide. So where are we going? So we're 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. So 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. Now what's unique about Experian, we have capabilities that align completely across that customer journey. So 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, to help and support our financial service to cross-sell and how they grow and maintain that portfolio right through to payments and collections. And 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. And that's really important. This foundational level that we've built, the way that we're 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. But this is what sets us up really well for this AI world that we're in the middle of and what we're going to show you today. Next slide, please. So 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. And 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 the operational benefits, operational cost reduction. And 1/3 see improved risk management, being able to do more pricing precision to be able to optimize more and more in terms of their operation. And so they're seeing the benefits that they see that they can get from AI, but that's got to come together with that data and software. So it's great to have that ambition. But 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. So we need to see what is driving them in terms of what's stopping them get into production and making those real benefits real for them. Next slide, Richard. So we don't see the lack of ambition. So when you look into the data and speak to our clients and see what's going on, what's really going on here? Well, particularly in a regulatory world where obviously we operate, it's -- those regulatory constraints and the lack of trust where their experiments and how do they make those real to get those benefits. And it's a formation of a number of areas, the complexity of data integration, all the regulatory and compliance side of how do 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. And this builds to that lack of trust. So where they are playing with, say, agents and automation, driven by AI. If they are using it, it's in those very low-risk decisions. But as you can see, it's a very -- that's where the majority of people are spending their time. The majority is in that very low space in terms of making -- allowing that autonomy of our agents to make decisions. And 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're doing, their experimentation with agents and AI, and we're going to bring that to life shortly in a demo. So next slide, please, Richard. So 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've been on into enabling the AI agentic world for our customers. What you can see here at the heart of the picture are all is the core of the AI control plane that we call it. So all the security, all the identity, all of the guardrails, all the compliance guardrails, immutable logging, so logging that is there, can be assured and can be safely analyzed by security, compliance to be assure our clients, and we use this ourselves for our own use cases to make sure we're safe and we maintain that compliance view when we run these systems. We then have the layer, the semantic layer, the trust layer, we call it. This is where that we're 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. So 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. And those are at the heart, which we'll bring together within a spend, and we see that now evolving and growing since we sort of started this about 18 months ago. And on that journey from sort of right to left, we can see some of the things that we've been doing. We've 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 on our -- within this core platform and enables us to learn and understand that trust layer and we've got these in market. We've had them for significant periods of time. So we've learned a lot to make sure we're safe. We're starting to adapt our tooling. Clearly, in an AI world, the way that we've got to think about our software and that tooling has got to adapt and change to that world. So 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 going -- helping our customers easily and more effectively and much more productively get their AI models into production and model their compliance processes. And now we see -- 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 sort of GRC, that governance of control space. And AI is really opening that up for us. We're then looking at that expansion further with partner services and agents. You heard Jeff talk about the agent trust models. These are new TAMs built within the platform that can enable us to get into markets we've 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. And then one of the really interesting areas that we're now building and we're going to bring to life around client agents. So 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? Next. So building on that, and before I hand over to Vijay to bring it to life, this is -- 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 been had that capability of really getting to that real intelligence level. Agents can allow us to enable that. So 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 if you -- many of our financial institutions, the financial -- 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 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 3 things in mind. So first, fraud is moving faster than human teams can respond. The moment a bank 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 is 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. So it's really about us being able to monitor and detect patterns and fraud rings forming across institutions simultaneously before anyone else can see them. Well, and then third, what we're going to show you here is the agent operating system. But 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're 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. So with that, let's -- Richard, let's go ahead and start the demo. [Presentation]

What you've just seen in that short demo was a real-world problem that lenders across the world face. They launched 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. And finally, we've done this now with multiple customers. And what we see is that automation and that simplicity allows for a lot of benefits across their organization. And this is just one example because we're also doing it across other areas. So 3 things really made this possible. First is 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. And 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. So 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. So 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 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. So starting with some stats, and this is a recent stat from Gartner that the prediction is 25% of customer service interactions and banking will be handled by machine customers by 2029. Now 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 Agent Trust solution is an environment that is supporting that. So 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 5-layer system. At the bottom, we have our trust registry. This is a log of agents, AI agents that have meta data 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 Agent Trust token and our tokenization process. So 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. And it's very important that we provide this measurement or score within the process to ensure that both sides of the equation are validated and equal. And then the top is where we find to a human. So this is where it gets really pretty interesting because we're 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're going to show you the demo, but I wanted to show you this slide because it demonstrates just the simplicity. So the goal here and what we are building on is seamless integration for the consumer and simplicity across the entire process. And behind the scenes, when we show you the demo, you'll 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. So let's take a look at the demo. [Presentation]

So 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. So with our agent operating system, we have those capabilities, and we're translating that into solutions like Agent Trust. And there's a lot more to come on that front. Keith, over to you.

Thanks, Vijay, and I hope those 2 examples brought the breadth of the innovation that we're 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. So in terms of metrics, in terms of the platform, what's 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're seeing that momentum that I talked about on the sort of first slide and that activity, whether that's the transaction volumes increasing, number of capabilities and the time spent. The other is the engagement. So when people are using the platform, our clients using the platform, we see becoming intrinsic and embedded as a tool that they use day-to-day. On average, almost 1/3 of their time is using this platform in their day-to-day world. So 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're giving -- we're showing them that value, the value of the tooling and especially the value of our data. that they can drive their business forward. And next slide, please. And of course, listening to our clients as well. You see some quotes here from some of our customers about the approach, what we're 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 are tangible. That means that the value is there. Customers are seeing the value, sort of proving out the sort of the thesis that we started with in terms of this strategy. So obviously, really gratifying to see, but we think there's 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's an extremely important area for us. We've sort of been engaging with the analysts across the breadth of what we're doing. So what's really great to see is where 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. And remember, these analysts spend time with all of the competitors. They spend time with clients. And so it's great to see where we're positioned as leaders in innovation on all those awards that come through, and they're just getting more and more in the market. So having that client feedback, proof points of the benefits we're seeing and then in terms of the analyst feedback in terms of that direct comparison, their own views with their clients who obviously, they -- is their business model is gratifying to see. And then next slide, please. So one thing I hinted on the part 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 a really interesting platform partner strategy for us. So here, we recently announced ServiceNow at the end of April, where the puzzle we're 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 KYD, third-party risk management. There's a huge market out there that we're not even touching and we're 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're well done with conversations with other partners as well. But we're really excited about this partnership with ServiceNow, where we plug a number of use cases into their platform, and we call it sort of agent-to-agent platform integration, first of its kind. But we're also energizing their go-to-market motions as well. So their sales teams are motivated to sell our services. For them, they see the benefits of the enterprise workflows they're typically putting in around those sorts of use cases, having the ability to bring our intelligence adapters into those across those sort of 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 to the over 10,000 customers they have globally in those sort of big enterprise areas they play across industries from pharmaceuticals, retail, telco, energy, utilities, areas that we would never get to. So really strong value exchange between us and them and also making -- and making sure client outcomes are great. So we're super excited about ServiceNow, but we see this as the first of a number of partnerships that we want to do. And each of these platforms, these sort of big players in these spaces have different subtle in terms of the way they -- the use cases and the workflows they work in and really enables us then to tune the services we have into their market. So really excited about what Ascend and the agent operating system can open up for us in this area. So next slide, please. So lastly, just to finish off, a couple of key messages. Ascend isn't 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've seen today with the agent operating system and what our teams are building on it. So we feel that, that market leadership, we really feel that we can redefine that financial institution through a trusted Agentic world, and we can go beyond the boundaries that we've typically been operating in. So with that, James, let's end the presentation and I hand back to you.

Thanks so much, Keith and Jeff and there's quite a lot to unpick there. I think relative to last year, we don't really talk about AI that much and now it's embedded in almost every slide almost. Now we move to our Q&A section, and it's great to welcome Lloyd Pitchford, Group CFO, for this part of the session as well. We've got a few questions in, but Lloyd, start for you. I think just to pull together we've heard so far, quite clear in saying that AI is an accelerant. But if you put us in a historical framework, so to say, experience been through innovation cycles in consumer when you first pushed out Ascend through Sandbox, et cetera, et cetera, it seems like we're very much in another innovation cycle now. How 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 guys. It's great to be here again for another of these annual sessions. And I think if I view your question through the lens of the many years that we've been doing at 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. And 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. And 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. And 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 the 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 footforward innovating companies are choosing us to partner with. So 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 2 and a bit years on the second half of our midterm framework and a lot of upside opportunity to deliver on beyond that.

But for now at least, it looks like we should be still sticking to high single-digit organic, but with optionality at least everything which has been discussed so far could push us to the upper end of that.

No change to our midterm guidance. You wouldn't expect me to say anything different. But I think against the background of questions about is this a risk or -- is this technology change a risk or an opportunity? What you can see is we're very foot forward and particularly some of the most innovative companies are choosing us to partner with. And I think Jeff said it well. Our goal is to meet all of our clients and all of consumers wherever they are. And those distribution channels are really expanding at the moment, and we plan to be in all of them.

Great. Jeff, if I can go to you, and we'll talk through the consumer. I appreciate the announcement that there's going to be a native offering within 2 of the 3 [ LLMs ]. Can you talk through how you think that changes or evolves the revenue model of the consumer business overall? We're used to it going direct through the Experian App, but it sounds like that's going to change in the future.

Yes. Well, I think, James, it's 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's 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-- and there's 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've 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. And 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. And that's 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's 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've been very clear that to interact with certain product features with us, you'll 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. And so I think through the conversations and the announcements that are forthcoming, you'll see that it's a symbiotic relationship that we've established that we think is a growth enabler for the business as we meet consumers in new and accretive spaces where they're exploring their financial health.

Sounds great. And recently, consumer margins have been scaling pretty rapidly. But are we still on that trajectory?

Yes. I think none of our guidance has changed with respect to the consumer business. Again, we've got a diverse set of business models within the consumer business, whether it's partner, subscription, marketplace, et cetera. We've got real flex, real optionality. And really, I think the biggest enabler for us has been building the customer base that we've built and expanded and scaled. And that provides optionality for us. It provides optionality around investments we want to make. But we would expect and anticipate that these new channels that we're exploring have very attractive cost to acquire customers embedded within them. And 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.

We get quite a few questions on the broadening competitive environment perhaps in consumer, which sort of AI enabled. If we look at the current growth rate in consumer sort of across marketplace and premium, notwithstanding data breaches, is perhaps a little lower than what we've 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's your take on that?

No. I think when you unpack the growth in the consumer business, you mentioned, 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, that's been backed up by what we see from lenders and in particular, the lenders within our panel. I think those are the signals that we've picked up and that we see across the business, consistent with kind of onetime irregularities, particularly around the panel.

If we can move to Ascend. I think I'll start with what I hope at least is a basic question first. The way you have -- the way the demo is framed and the way you framed Ascend being an AI native actually, that means from a customer's perspective, it's going to be a human at your customer who is using agents which are built in and control within Ascend as opposed to the agents of the bank as such, be they created through copilots or cowork being connected to a sense? Is there a distinction there?

Maybe I'll take that, James. So yes, we'll look at various patterns. But effectively, the platform, that ecosystem, the agent operating system allows you to build your own agents within that environment, so 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. We will -- 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 we've got where we've got to so fast and ahead of the market. None of the competitors have got this capability today. And 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, it's regulated. There's production agents that we've drunk our own champagne as it were. And 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 bank financial services?

Firstly, it's available at the core part of the platform. So it's available where the platform is. Obviously, it's in early stages. And what we want to do is to make sure we have solutions out there. We're in an early adoption phase with many large organizations who -- that's probably all I can really say, we're starting to look to build agents with. But 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's a huge amount of that synthesizing of data where somebody is referred for a credit check or a fraud referral goes to using agents to synthesize all of that data to come up with recommendations for that agent, we see as -- we are seeing a huge, huge productivity benefit. And we have real agents live in production in some -- in 1 or 2 of our regions, looking at both credit and fraud use cases around those operations agents. And yes, that's real. So the intention, of course, is that we'll be rolling out and scaling that over the coming year. I think I'd add, James, if you look back and draw a line from where we've been to where we're going. What you're seeing here is waves of innovation on top of the Ascend platform. So some of the demos you see are things that we've been working on and we've had client engagement with now for a little while. The things that we're working on that we'll demo to clients at our conferences, client conferences in the U.S. and the U.K. in October and November are the next stage beyond this. And 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. And 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.