Good afternoon and welcome. I'm Mark Kelsey. I'm the CEO of the Risk Division, and I've had a career in RELX now for over 40 years, and I've been CEO of Risk since 2012. The last time I presented to you was 2021, and today, you'll see the continued evolution of the business since then. Last time, the focus was on Business Services, and today, we're gonna focus on our Insurance business, which will be covered by Bill Madison, CEO of Insurance, with a case study in auto insurance by Shweta Vyas and in property insurance by Cole Winans. And finally, you'll hear about our technology approach from Vijay Raghavan, and then I'll come back and run a brief Q&A. This chart shows where Risk fits within RELX. Risk represents around 35% of RELX revenue and about 40% of the profit. Our trailing twelve-month revenue to June was GBP 3.1 billion, or about $3.7 billion. The business is already 99% electronic, and by geography, 80% of our revenues are currently from North America. By type, you can see it's close to 40% subscriptions, and the remainder is what we call transactional. But the majority of that is under long-term contracts with some form of volumetric billing, and less than 5% come from one-time transactions. We serve four different business segments within the Risk division. We have a strong position in each segment, solving critical problems for our customers. Across our different segments, we help our customers assess, predict, and manage risk. Starting at the top right, s is the largest part of Risk, representing almost 45% of revenues. The business is based around assessing consumer and business risk. We are a clear market leader in both physical and digital identity, and we help our customers assess the risk of doing a particular transaction with a particular individual or device at a particular point of time, whether that risk is fraud, compliance, or credit or business risk. Bill is going to take you through insurance, which is our focus today. In government, which is around 5% of our revenue, we do something very similar to Business Services, but our customers are in the U.S. state, local, and federal government. And finally, in specialized integrated services, which represents just over 10% of divisional revenue, we provide data and analytics solutions in strong growth specialist markets such as commodities and aviation. The long-term growth fundamentals remain strong for Risk. We've continued on a strong and consistent trajectory with the average underlying revenue growth of 8%. While there will always be some fluctuations across the cycle, our main business segments have average growth rates roughly in line with the division average, and any fluctuations tend to cancel it out over time. We're not only a high revenue growth business, but also a high margin, and a key factor in this is our scale and the ability to reuse our unique data assets in each of our key segments and across different problems we solve in those segments. This is also true of our technology and linking capability, which we leverage to manage cost growth below revenue growth. We operate in some very large, attractive markets with structural growth driving the green component of this slide. But our innovation engine is the main driver of our consistent growth, and we continue to innovate, to develop increasingly sophisticated analytics and decision tools that deliver enhanced value to our customers. What you can see here in orange is that the main driver of our growth is the introduction and rollout of new products, and we define new products as those launched in the last five years. This is the typical adoption cycle period to roll out across the whole customer base. Let me now tell you how we do this. As a business, we have four key capabilities that allow us to continually add more value to our customers. The first is deep customer understanding. That deep customer understanding enables us to establish what it is that our customers are trying to achieve, how that is evolving, and how we can help them solve their problems. The second key capability is our leading datasets, and we have an incredible position here. We continue to grow not only the depth and breadth of our data assets, we're also adding different types of data, connected cars, geospatial, behavioral data. Our third key capability is advanced linking analytics. Linking is fundamental to the value we bring to customers. We use the same linking technology across all of our data. This allows us to connect these vast amounts of disparate data points to create one unique view of an individual or a business with world-class accuracy. And it also allows us to leverage our data to solve different problems in different subject segments. We layer this linking capability with sophisticated analytics and algorithms. That then allows us to provide customers with scoring models and attributes and diagnostic tools, which critically enables them to make better decisions. And finally, our technology platform. We have a fast, scalable platform that allows us to ingest more and more data and plug in new AI technologies, and allows customers to connect to our solutions seamlessly. Our strategic objectives are to continue to innovate and develop sophisticated analytics and decision tools that deliver enhanced value to our customers. To focus on organic growth, supported by selective acquisitions. Sustain strong underlying revenue growth in the high single digits for a long time to come, another decade or more. To manage underlying cost growth below underlying revenue growth, and continue to deliver strong cash flow and return on invested capital. You'll now hear from Bill on how we do this in insurance, and then from Vijay on how we use technology as a key enabler of this strategy in insurance and across Risk. Thanks, Mark. I am Bill Madison. I'm the CEO of Insurance. Spent my entire career, 30+ years, within the insurance industry. I was part of a startup in the late 1980s that became ChoicePoint, which was acquired by RELX in 2008. I became the CEO of the insurance business in 2011. After all these years, I can honestly say that I'm more excited about the market today than I've ever been at any point in my career. We're in a great position to continue to help our customers make informed decisions through the better use of data and analytics. Insurance is just under 40% of the Risk division's revenue, with 12 months trailing revenue to June this year of GBP 1.2 billion, or approximately $1.4 billion. About 75% of the revenues are from U.S. auto insurance market. We continue to find new ways to serve auto carriers' needs by addressing market challenges, innovating and adding new predictive data sets across the insurance workflow. The remaining revenues are from our adjacencies, where we are replicating the success that we've had in the U.S. auto market. Since I last presented to you in 2015, we have continued to grow our solution set in U.S. property, life, and commercial insurance. Outside of the U.S., we have focused on growth in targeted geographies, the U.K. being the largest. Finally, as you can see, most of the business is transactional revenue, but it is tied to long-term contracts with volu metric elements. There are very few one-time transactions. The markets that we operate in are large in scale and have attractive long-term growth drivers. U.S. auto insurance is the largest sector, with $278 billion in direct written premium in 2022. Property, life, and commercial are also sizable sectors, each with direct written premium of between $130 billion and $200 billion, with lower transaction volumes than in the auto sector. We serve most of the leading corporations in the insurance and automotive industries. Our coverage includes nearly all U.S. auto insurers, automotive manufacturers that account for over 70% of U.S. new car sales, nearly all of the top U.S. property, life, and commercial carriers, and U.K. insurance carriers that account for 97% of property casualty direct written premium. Now, let's focus on what we do to help our customers. Simply put, we give insurance carriers a more holistic view of the risks associated with an insurance transaction, whether the transaction is associated with a person, a vehicle, or a property, so the carrier can appropriately price the risk. In addition, we streamline and remove consumer friction in the insurance process, whether it's buying a policy or submitting a claim, by pre-filling the carrier's requested information and streamlining workflows, thereby reducing processing times and costs. We enable carriers to improve their operations by identifying fraud, acquiring and retaining the right consumers, and automating processes. Ultimately, we use data and analytics to help insurance carriers do what they do better, faster, and cheaper. We support over 2 billion transactions annually across the insurance workflow for a small transactional fee, with a total fee representing significantly less than 1% of a carrier's direct written premium. How do we do this? Mark spoke to you about our four key capabilities. Let me tell you how they apply to insurance. First, it starts with deep customer understanding. We have long relationships with our customers, and many of our employees came from the insurance industry. As stated, I have been in the industry my entire career, and many of our employees have as well. We are deeply integrated into our customer workflows, which gives us intimate knowledge of their business needs. Second, leading data sets. In addition to the vast public records on identity that we use across risks, we have extensive data on motor vehicle records, also known as MVRs, which includes information on car registration and traffic violations. We have also established unique insurance contributory databases. To be a customer of these offerings, you must contribute all of your information affiliated with that solution. Our two most prominent databases focus on prior claim activities and current policy coverage. In every market we enter, we establish similar contributory solutions. In the last five years, we have launched or expanded six new contributory databases, which gives us 12 in total across the U.S. and U.K. insurance markets, and we have more under development. These contributory databases are very difficult to replicate, giving us a strong position with our customers. Ultimately, we've become the trusted custodians of our customers' data, which is a critical requirement throughout the markets we support. We also continue to expand into new types of data, like vehicle knowledge, telematics and connected car data, vehicle build and history data, property intelligence, along with geospatial data. Third, we apply advanced linking and analytics on top of these differentiated data sets to deliver decisions to our customers at their point of need. The foundation of our analytics offering dates back to the early 1990s and continues to evolve as we help our customers execute on their growth strategies. AI has played a critical role in advancing our position from being a content provider to delivering decision tools at the point of need across the insurance workflow. It's all about taking our core offerings and making them better. AI has and will continue to play a critical role in this journey. Our real competitive advantage is the ability to turn our unique data sets into insights, and you will see this in the example that you'll hear about later today. Finally, our technology platform. We have created a platform to deliver our solutions to our customers through a single point of execution. Our customers don't often code to an individual application. They code to our platform, to a decision system, which provides data-driven intelligence to support their business strategies. This is incredibly powerful. As we launch new solutions, due to this platform, it is easier for our customers to quickly implement these solutions into their workflows. This slide shows how these capabilities come together to enable our customers to fully assess risk and make better decisions. Over 90% of our solutions we deliver are machine to machine, directly into the workflow of our customers. This means a carrier can automatically pull the right data and risk scores to make critical decisions in real time. We excel in innovation. Here you can see the outcome of this innovation engine. You can see in the bars the vast number of solutions we have introduced over the years. I should point out that the solutions in red represent new offerings introduced to the market at that time. The innovation continues to drive growth across our business. Let me be clear, our growth does not come from price increases, and very little comes from acquisitions. Our growth primarily comes from organic development based on a deep understanding of our customers, their growth strategies, and developing new solutions to help them execute on their areas of focus. Now, let's look at how we apply this discipline in our largest segment, U.S. Auto. This chart shows the key components of an insurance carrier's workflow, from acquisition to contact, all the way through processing claims. Our core business is in risk assessment, which is in the middle of this chart, helping our customers with their quoting and underwriting processes. We help carriers understand the risk associated within the policy, so they can price the risk appropriately. Years ago, carriers struggled to collect basic information about a consumer's insurance coverage, their policy history, and their claims. They had to use manual processes that were very labor-intensive, and it took days, sometimes weeks, to complete a transaction. First, in 1987, we launched C.L.U.E. Auto, which was the first contributory claims history database for the auto insurance market. By collecting and linking claims data across the contributing carriers, we were able to report for the first time, the entire claim history associated with the consumer and their vehicle. Since then, we have gone deeper into the underwriting process. After C.L.U.E. Auto, we expanded and created more solutions that were ultimately integrated into the quoting and underwriting process to enable greater precision in pricing policies. 15 years ago, a carrier may have had five pricing tiers within an auto policy. Today, thanks to our data and analytics offerings, carriers can segment risk across 100 or more pricing tiers. Because of this development, over 85% of U.S. consumers that have personal auto insurance coverage are paying lower premiums, thanks to our solutions. We continue to innovate, adding things like telematics data and information about the vehicle's safety features to provide carriers additional insight to help them further segment risk and better price an insurance policy. We have also expanded our solutions across the insurance workflow. At the point of contact, we have streamlined processes to reduce onboarding friction with the consumer. Historically, for a consumer to obtain an insurance quote, they must identify a lot of information about their cars, their current policy coverages, violation history, and all the drivers in the household. Our pre-filled solutions populate the application using data that already exists in our databases, allowing the carrier to interact with the consumer more effectively and prepare a quote much faster, significantly reducing the application dropout rate and improving efficiency. Even earlier in the insurance process, we have launched new solutions that help carriers better identify prospects. The insurance industry is spending over $5 billion a year on marketing and advertising to consumers. We help our customers optimize their marketing spend, and we reduce consumer friction once the consumer starts their shopping journey. At the end of the insurance workflow, we help carriers improve their compliance and claim processes. Claims are a critical component of profitability for an insurance company. Roughly 50% of the insurer's FTEs are focused on claims, so optimizing the process has a direct impact on their bottom line. The claim processes today are siloed, manual, prone to error, and costly, with 33% of consumers who have a claim saying they switched or considered switching carriers as a direct result of their experience. We have a wide suite of solutions to help carriers automate the claims event, reducing errors and improving decision-making, taking several days out of the claim process, thus reducing the likelihood of consumer shopping with a different carrier. Now, let me turn it over to Shweta to walk through an example of innovation within U.S. Auto. Thanks, Bill. As Bill mentioned, the core of our business is in underwriting, and we continue to innovate here to enable carriers to make better risk decisions and to make existing processes better. Historically, insurers have relied on motor vehicle records, or MVRs, for the state to understand a person's driving history. The challenge with this is that MVRs are often incomplete or there's a time lag. MVRs are also costly for carriers, and there have been significant increases in fees over the years across many states. To solve this challenge, in 2019, we launched our Driving Behavior 360 solution, which aggregates violation data, court records, public records, and other proprietary data across 45 states, soon to be 49 states. That's over 4 million data points that are getting updated in our database every week. We apply analytics to link the data and to build scores and insights to give carriers a more complete picture of a person's driving history, faster and at a lower cost. This solution allows carriers to effectively match a consumer's price for insurance to their true risk. By using our solution, a carrier can identify 15% more incidences over just using state MVRs, while saving up to 25% in costs compared to buying the MVR directly from the source. The market reaction to DB 360 has been very positive. We've seen significant growth as we've continued to launch new states and drive adoption of the solution, and we expect this to continue for many years to come. Back to you, Bill. Our approach to serving our adjacent markets is very similar to our US Auto business. We continue to innovate organically and serve carriers' needs using proprietary data sets and analytics. The workflows within these adjacencies are very similar to auto, and we're focused on expanding our solution suites across the various steps within that workflow. Here we continue to innovate organically while expanding types of data and our AI-based analytic capabilities to provide a more holistic view of the risk. I should also point out that we have supported this strategy through our acquisitions of Flyreel in the property market in 2022 and Human API in the life market earlier this year. US Property is currently our largest adjacency. I will now turn it over to Cole Winans, our Vice President and General Manager of our Property Insurance business, to provide deeper insights into how we are innovating in this market segment. Cole, over to you. Thanks, Bill. I'm Cole Winans. I was the founder and CEO of Flyreel, which was acquired by Risk last year. I've been the General Manager of the Property Insurance business at Risk since earlier this year. Property insurers have been experiencing significant claims losses. The severity of claims rose 37% between the first half of 2019 and the first half of 2022. This is due to a rise in catastrophic events and the increasing cost of repairing damages. These claims losses have outpaced the rise in insurance premiums. When underwriting a new policy, carriers rely on a manual and cost-intensive process. In attempts to manage their profit, they're selective on where they perform inspections. Between 10%-20% of homes are typically inspected when underwriting a new policy, with even fewer being inspected when a policy's renewed. Finally, these inspections don't always capture the property characteristics that insurers need to properly assess risk. So often, carriers don't have a good understanding of the risk across their book of business. We're addressing this challenge through the combination of data and artificial intelligence. At Risk, we've aggregated significant intelligence on a property's building characteristics, claims history, and ownership. We've supplemented this with aerial imagery, which helps us better understand a property's footprint and condition, particularly the roof condition, which is often an area of large claims losses. And finally, with the acquisition of Flyreel, we've added a detailed understanding of risks within the property and on the home's exterior. Leveraging advanced analytics, we can now score the risk of a property for a carrier as they're underwriting a new policy, as well as help carriers analyze risks within their existing book of business. Let me show you one example of how this works. To solve these market challenges, we've introduced Total Property Understanding, an end-to-end AI-powered workflow that enables carriers to select the properties they should invest time and resources into inspecting, as well as capture data on these properties at scale with an AI assistant that holds the hand and guides homeowners through their own inspection process. And finally, AI that amplifies the abilities of the underwriting teams and the underwriting workforce by automatically flagging risks for them, as well as hazards in the inspections for the underwriters, enabling them to act on this data more efficiently at scale. Let's see it in action. What we're seeing here is a recording of the homeowner experience. Here, you'll see them interact with an AI assistant that is guiding them through and holding their hand through the process of taking various photos and videos of key areas of the home. We're committed to delivering a world-class experience to our users. The experience is simple and intuitive. We like to say: "If you can send a text message to a friend or family member, you can now inspect your own home." And we're seeing the impact of our commitment to user experience with a 95% homeowner satisfaction rate and upwards of 70% completion. But now, let's look at what's happening behind the scenes. And what we're seeing here is our computer vision models processing the imagery and videos captured from the homeowner's walkthrough. Now, keep in mind, this is fully automated. There's no one on the other end of this. We've developed proprietary computer vision models that automatically detect over 200 property attributes to improve the underwriting process and risk management altogether. Our AI is automatically identifying materials, condition, risks, and hazards. It even has the capability of servicing risk and recall information for appliances that often cause losses, like hot water heaters and refrigerators, washing machines, as well as recalled circuit breakers that can lead to deadly house fires. On the exterior, we'll identify trees that pose a risk to the roof, analyze the condition of shingles to determine whether they're curling and could lead to a leak. Again, all of this done entirely with artificial intelligence. Using our technology, our customers are able to deliver a world-class experience to their customers while gaining access to more comprehensive data than ever before to improve business outcomes. But we don't stop there. At Risk, we're committed to going above and beyond, and while it's not a market requirement, we saw while scaling our solution that sometimes homeowners inadvertently capture themselves or loved ones in images and video. And what you'll see here, or what you won't see, are my two baby boys playing in their sandbox as I scan my own home. We've developed our own proprietary and patented method for face blurring to go above and beyond for our users and the market, honoring their privacy. We're proud of the work we've built and to have the opportunity to present these capabilities to you today. These are just a few examples of the innovations occurring at Risk. Back to you, Bill. So thanks for that, Cole. So to wrap up, we operate in large, attractive sectors with growing demand for data and analytics solutions. We have a strong innovation engine and a proven track record delivering quantifiable benefits to our customers through organic development. We continue to leverage our four key capabilities. That is, deep insurance expertise, robust and comprehensive data assets, advanced analytics, our single point of execution technology platform, and we have a long runway for continued growth in our core U.S. auto business and in our adjacencies, and we are confident that we can continue to capture that growth for many years to come. With that, over to you, Vijay. Thank you, Bill. I'm Vijay Raghavan. I'm the Chief Technology Officer for the Risk Division. I've been in this role for 12 years, and I've been with RELX for over 20 years. I'm also the Chair for the RELX Technology Forum, which works across the RELX divisions. Mark briefly touched on our core capabilities, and I'd like to walk through our data, analytics, and technology approach in more detail. Let's start with what we mean by technology at RELX. You have seen this slide before, but it is an incredibly important one. It demonstrates how we get from data to specific, actionable insights that help our customers make decisions. We often talk about big data and about our AI/ML tools, which are at the heart of what we do. But the essence of this diagram is that big data itself is not of much value to our customers. This slide represents how our technology transforms big data into small, actionable data sets that add value to our customers' decisions. What this slide shows on the far right is that our solutions are deeply embedded into our customers' workflows to help them automate their decision-making. At Risk, over 90% of our transactions are machine to machine, so it is incredibly important that the answers that we deliver to our customers are highly precise and accurate, and seamlessly integrated into our customers' operations. It's useful to understand the evolution of our technology over the past 30 years. We have a long history of using advanced technology and analytics within Risk. We first created our big data technology in the 1990s, long before big data was a buzzword. We then created a proprietary machine learning-based linking technology in the mid-2000s. We first started talking to you about big data and our usage of analytical algorithms back in 2011, and around that time, we open-sourced our HPCC big data platform because we wanted to take advantage of contributions from the community to accelerate the pace of innovation. This paid off. By around 2015, while we had been using AI and ML techniques for a while by this time, we started sharing externally how we have woven AI and ML tools and processes into the fabric of our data and our technology, not just to build better products, but also to make our modelers and data scientists more efficient. So what is the role of technology at Risk, and by extension, at RELX? At a fundamental level, we are the enablers of the innovation engine you've heard so much about today. We are focused on helping the business execute against our growth plans by investing in the right technology capabilities to enable our teams to innovate quickly and efficiently with the right tools, and to ensure that our systems are flexible, reliable, and scalable. Given the nature of our business, it is the role of technology to make sure that we have highly secure environments that protect our customers' data and our IP, and to adapt to changing regulatory requirements. An integral part of technology's role is to continuously automate and optimize through the improvement of our processes and our tools. Technology is a real source of competitive advantage for us. At the heart of that is our people. We have over 3,000 technologists at Risk, at Risk, with deep experience and expertise in big data and AI and ML techniques. This is roughly a third of Risk's employees. These are highly innovative teams who are motivated to use technology and analytics to improve outcomes for our customers and for ourselves. As Mark and Bill have said, our data is the foundation of our business. We continue to evolve our data sets, expanding the breadth, depth, and type of data. Our technology and our data assets go hand in hand because our investment in each helps improve the other. First, we have by far the largest public records data in the U.S. that we've been collecting for 30 years. In the U.S. alone, we have over 10,000 data feeds being ingested into our servers, with hundreds of millions of records added daily. Second, are our vast contributory databases. One of our core skills as a business is implementing and enhancing our contributory databases. This is, again, something that we have refined over many years, and we have it down to a science. These are unique data assets to us, and they put us in an incredibly privileged position in terms of the value we can create for customers. We continue to add more contributory databases to our businesses, as Bill spoke about in the context of our insurance business. Our third type of asset is our digital intelligence. You heard a lot about this from Rick Trainor in 2021. This is data that we have on devices, digital identities, email addresses, and consumers' transactions online. We expanded into digital data in 2018 with the ThreatMetrix acquisition and have continued to add to our digital data assets via subsequent acquisitions and organic development. Fourth, and finally, the most recent addition to our data assets is our machine-generated data attributes. This includes our data on how consumers are interacting with their devices, such as real-time data on airline schedules and telematics data, and images of properties. You heard about this as Flyreel. We layer advanced analytics on top of our data to cluster, link, and identify patterns to improve our solutions and our processes. This is what we call extractive AI. Our linking and superior processing techniques enable us to create leading, highly accurate solutions with fast cycle times and at lower costs, which we strive to improve every year. We use a variety of technologies, including open-sourced, third-party, and proprietary solutions, and a variety of analytical techniques. Given the plethora of available tools and techniques, it is important to choose the right tools for a given problem. We have become adept at selecting the right technologies and the right content sets to solve specific customer problems in each of our businesses. We are constantly evaluating new tools to evolve our approach to support better, faster, cheaper innovation. In that context, generative AI is the latest evolution of available AI tools. In our legal division, generative AI is a big step forward because the business is centered around text-heavy content sets. For risk, we have been using extractive AI for decades on our proprietary data sets to provide machine-to-machine answers for our customers. We see generative AI as having a smaller impact on our customer-facing products. There are opportunities, though, to use generative AI to give us greater scale to innovate, use cases like automated code generation, process automation, and knowledge extraction from our internal repositories. This is where we as a business are focused, utilizing generative AI to enable our innovation machine to help us launch more products faster. Our technology platform, vast data assets, and AI/ML tool sets enable us to create significant value for our customers by predicting fraudulent behavior to assist our customers or establishing the creditworthiness of consumers, or assessing driver risk or property risk, as you've heard about today. We also predict flight delays and enable frictionless access to social benefits. The list goes on. These are just a handful of the use cases we serve using our technology and data assets. With that, I'll turn it back over to Mark. Thank you, Vijay. To summarize, we have leading positions in large, highly attractive markets with structural growth. Our solutions help our customers solve critical and complex problems to better assess, predict, and manage risk. Our organic innovation engine is the main driver, leveraging our four key capabilities: deep customer understanding, leading data sets, advanced analytics and linking, and technology. This combination gives us real competitive advantage. Our objective is to continue to deliver strong underlying revenue and profit growth for a long time to come. With that, I think we're ready for questions. We will now begin the question and answer session. To ask a question, you may press star, then one on your touchtone phone. If you're using a speakerphone, please pick up your handset before pressing the keys. To withdraw your question, please press star then two. At this time, we will pause momentarily to assemble our roster. Our first question comes from Nick Dempsey with Barclays. Please go ahead. Yeah, good evening, guys. Three questions, if I can, please. So the first one, at the beginning of the presentation, Mark pointed to managing underlying cost growth below underlying revenue growth at the risk division. I guess in recent years, we've watched the guidance be for underlying operating profits to be in line with underlying revenue in terms of growth. So does that suggest there's an ambition at some point to achieve more margin improvement in the total risk division? Second question, it was interesting to hear your offerings in property insurance. Is it fair to say that in U.S. property, Verisk Analytics has the most powerful data set, just as you do with Clue in Auto? So are you offering something adjacent to Risk that misses what they do in this area, or are you in fact directly in competition with Verisk now? And then the third question: over a long period of time, as cars become much safer, and then we have a large number of driverless cars, how do you think about the risk to the volumes that drive your auto insurance business? Okay, so I'm gonna take the first one and the third one, and I'll give the second question to Bill. So we start with our kind of underlying revenue growth being above kind of cost growth being below underlying revenue growth. It's. If you look at our Risk business, we've got incredible scale in data and technology, and we've got a core skill in innovation, but we've also got a core skill in process innovation that's incredibly important, and we constantly look to do things, as Vijay said earlier, kind of faster, better, cheaper. So it's. And we invest in our new product development. We've got great momentum, and our challenge to ourselves and our strategy is to have our cost growth below our revenue growth. So by definition, that's gonna edge the margin up. We're talking about small differences, but it's but over time, it depends on portfolio actions, but over time, a small incremental change. That will that will happen with the numbers, but it's but small is what I'd say. But yes, I do see a change there. Bill, over to you for the second question. Yeah. So let me make sure I understand the question itself. It sounds like it was more affiliated with innovation, and technology and the inclusion of data sets and the position that we have within the market. If that's the case, that's exactly what we're doing right now. You saw Cole's presentation on a information gathering platform driven by the consumer, with the inclusion of AI into that application, which is a great position to be in. Now, with the inclusion of data sets and knowledge about the risk, the two coming together really sets us apart in how the true evaluation of our property risk is going to be done going into the future. So we're extremely excited about that. That technology really rounds out our strategy. We've always had a strong position on the property side, but now with the inclusion of the Flyreel investment, the two coming together really sets us up well for the future. Thank you, Bill. So, Sam? So sorry, just to come back on that. I was kind of asking about your competitive positioning versus Verisk Analytics in that property area, where I understand that they have the leading data set. That was really my question on the second one. Yeah. So from our perspective, you know, we're doing a great job. We have an incredible data set associated with that. I can't, really can't speak to our competitors, but we do feel as if the combination of the two, with the data sets that we have and have had in the market, with the inclusion of the AI tool that we just talked about, is really what's gonna set us apart. Okay. So if I pick up the third question around autonomous and cars is, we're very excited by the kind of, the advance of technology in cars. What you're seeing is the, the crashes are going down, but the severity and the cost to repair is going up, and that's really affecting profitability of our, our customers. And on the things like ADAS front, we've launched some great products where we're getting data from OEMs and others, and, and providing the market with how you compare a Renault with a Ford or a GM car for all the different ADAS features. So we normalize it, we standardize it, and that's going down really, really well as a module for our customers. We're very excited by the telematics exchange that we've got, so some... The fact that electric cars are coming in, and we're giving insurers information on how people move from a petrol or diesel car to electric car. So, I guess what we're doing is we're bringing kind of clarity to the market. So, and the other issue is, I think, what's driving the long structural growth here is that the more complex the market is, the more technology is coming in, how they're all interacting together is driving the structural size of the market, and it's also driving, in a big way, the amount of data in the market. And data is a real core strength of us when we kind of standardise stuff, normalise stuff, and take it down to those models, and Bill talked about his 700 analytical models. Well, that's just playing to our strengths in data. We do see this as a big driver of our growth going forward in the structural growth and the products we're launching on that one. Thank you. Thanks, guys. Our next question comes from Adam, Adam Berlin with UBS. Please go ahead. Hi, Mark. Good evening. Can you hear me okay? Yeah, yeah, loud and clear. Thank you, Adam. Good. I've just got a couple of questions. The first is, you talked a little bit today about the M&A you've done just in the last five years and how that's created new data sets for you. Can you talk a bit about where the pipeline is in the moment? Are there still assets you need to bring into the portfolio to sustain the growth or kind of are we at the end of that process? Just to help us understand. And the second thing I wanted to understand was, with the transactional revenues, can you talk a little about the billing cycle, how that works? So, you know, does an insurance company use a certain amount of data over a quarter, and then you send them a bill, and then how many days do they pay you? Can you just talk about the working capital and how that, how that flows through for us? We'd really, really appreciate that. Thank you. Okay, well, I'm gonna take the first question, then pass the second one on the transactional revenues to Bill. So, when we think about our acquisition and M&A strategy, I mean, our strategy is incredibly clear. It's about organic growth, but it's, we've got tremendous opportunities in our core markets, our adjacencies, and we've got great momentum. But from time to time, we do look at acquisitions, and it's, to support our growth, to accelerate our growth. And, and, and the key question we ask ourselves is: Are we the natural home? And very often acquisition will bring data, it'll bring technology, it'll bring competency, it'll bring talent, but it's a nd probably our best example recently, in recent years, you talked about was ThreatMetrix that ticked all those boxes. And that combined with Emailage acquisition and the organic stuff we've done now has given us a wonderful position in that digital fraud and identity market, and we talked about that in the 2021 seminar we did together. So, it's. And I think going forward, we have no clear strategy on acquisitions. What we're looking for is what might accelerate our growth. So there's nothing we need at the moment that we're looking on, that we need to acquire. We're in control of our own destiny. We've got great growth. All of our markets are offering real opportunity. So at the moment, we're not looking for a particular thing, but we're always looking at acquisitions. We're always looking at the startups and evaluating them in lots of partnerships. And as you know, the acquisition of ThreatMetrix and Emailage both came from partnerships. And when you really get to know a customer, you can see the real benefit in being the natural home. So at the moment, we've got nothing particular on our agenda. We're always looking. Of course, we're looking, but it's but nothing in particular in the near-term horizon that we absolutely need for our business. We're very self-sufficient. Thank you. Bill, over to you on transactional revenue. Yeah, on the transactional revenue, it's always, it's always a good question in terms of, you know, the cycles, how the market buys, intelligence about the risk, and it is per transaction. And, you know, we're within the workflow, and the transaction is affiliated with that. Our contracts typically are multi-years, 3-5-year cycles, and it's really done through the working with the carrier, understanding their strategy, where they are today, where they're going in the market, that really sets the foundation of that event, the agreement that we have between both organizations. It is a monthly billing process, based on the transactions that they order over that 30-day period. That's great. Can I, can I just ask you a question, Mark, about fraud and identity as well, while we have you? Is that okay? All right. Can you just talk a little bit about on the fraud and identity side? Obviously, there's a lot of players with different offerings, credit card companies, payment companies, obviously, startups. Can you just talk a little bit about how you're differentiated in the fraud and identity market? Is it just through ThreatMetrix, or are there, there are other things you've got that stands you apart from all those competitors in that area? Thank you. Okay. So, I mean, the key thing that stands us apart and differentiates us is the sheer scale and the critical mass that we've got in ThreatMetrix is the fact that we've got 9 billion devices, we're monitoring 3 billion kind of physical identities, digital identities. It's the scale is two or three times the nearest competitor, and it's one of those models that the more you get, the stronger you get, and the stronger you get, the more you get. So, competitive, we've got a wonderful position with ThreatMetrix. We're constantly about adding to it organically, but it's around behavioral. The EmailAge acquisition brought us emails in vast numbers. I think we're tracking about 3 billion different emails, but it's so it's the scale that gives us the real competitive advantage on, on fraud and identity, and we are the clear market leader. When you then combine that with the, the physical data we have, that puts us in a wonderful position, and we talked that through last time in the 2021 seminar we did, and that position is still exactly the same. We have real competitive advantage in that combination of digital and physical fraud identity. Thank you. So have you now got a value proposition which combines the device data and the individual consumer data together so that you can do risk scoring using both data types, or are you still in the process of bringing that together? We have got that. In early phases, yes, we have got that. Yeah. And that's a core strength of our business, how we bring the two together. Thank you. Thanks very much. Again, if you'd like to ask a question, please press star then one at this time. Our next question comes from Tom Singlehurst with Citi. Please go ahead. Yes, thank you very much. Thank you very much for the presentation. It's been fantastic, so, much appreciated. I've got the dreaded three questions, if that's okay. The first one is, I normally, and I might have missed it, but normally you take an opportunity to say that your, your growth is 100% volume driven, and it hasn't, you know, been driven by pricing. I'm just interested on the question of pricing. I presume it's still largely a volume game, but, you know, can pricing become a lever that you pull over time? And if not, why not? That's the first question. Second question is on cyclicality. Obviously, relative to some of the other professional information businesses which are gonna be driven more by the interest rate cycle, you're not gonna be driven by that. I completely understand it. But are you, y ou know, in the background, is there anywhere where you see sort of cyclicality within the services that you provide? Or just to make sure that we don't get caught out by something suddenly happening and catching us off guard. And then maybe on the same theme, finally, privacy. I know that what you do is, you know, very endemic to certain key markets, and it's not necessarily governed by the same rules as sort of more consumer-facing marketplaces. Can you just talk about what protections you have to safeguard consumer privacy and make sure that you're compliant, and we don't have a nasty surprise on the privacy side? Thank you. So I'm gonna take the first two, and then I'm gonna pass the privacy one to Bill. So we think about price versus volume. So it's price is not a driver of our growth at all. Bill talked about it quite a lot, and we have a core skill innovation, particularly insurance, but across the group, but particularly insurance, that when we launch a product or we price it at the beginning, and we price it to the value we're creating to the customer, we then don't change that price. So and then we get our growth from rolling that product out across the customer you sold to and getting to more and more states and getting more and more customers. But it's and then you get growth from launching new products. What that's reinforced in the insurance business and in risk is, everything is about the cost of innovation, because we don't put the price up, which is easy. You've got a real cost innovation in the DNA of the business, and that's incredibly important. If you look at slide 19, I think it was slide 19, which is Bill's chart on innovations, and internally, we call that Bill's CV or Bill's resume, but it's. He was there at the beginning when it was $30 million. You only get growth by launching those products, and if you look at the products in red, it's in the last five years, we've launched more products than any other time in our history. So it's, and when Bill and I look at our innovation pipeline going forward, it's equally strong. It really reinforces that that cost of innovation in the DNA of the business, which is important. So, the second question is around cyclicality. So, and our long-term strategy is all about organic innovation. We've got large, attractive, structurally positive markets, but it's but we're not immune from cyclicality, so it's a kinda key one. So, but I think the key thing is, we're in big markets, take the insurance spectrum right across, or take fraud and identity, or compliance. They don't go down when things are tough. If anything, there's an argument they get stronger, and it's and we're providing our customers complex solutions that are credible to them, and we're deeply embedded into the workflow. But it's a typical cost, as we pointed out, is significantly less than 1%, but has a massive impact on their kind of core business. But it's a nd then, the point you're getting to is some of our markets operate slightly differently. Insurance does operate on a different cycle. So in the 2009 cycle, in the recession, insurance actually grew very strongly, and there were two key reasons for that. And the first is when consumers are under pressure, one of the first things they do is they shop their insurance, and they try and switch, and that puts the activity up. And the second reason why it grew very strongly in 2009, is 'cause the insurance business had a great track record of launching new products. And you remember that chart we showed, the green and, green and the orange, and it's, and the orange is critical. If you look back in that period of time, we used to get three or four points of growth in the orange. We're now getting five percentage points of growth. So, so, so that's what we're doing now. And then in more recent times, when the economy tightened in the second half of 2022, we saw the Business Services transactions just slow down a fraction, the growth. Still growing, but just a fraction slower. But at the same time, in H2 2022, we saw the insurance market picking up, and again, that's the consumers shopping their insurance when times are tough. But it's a nd what also happened is they actually shopped a bit more. So when we get to where we are now, we've got to the second half of 2023, Business Services was lapping a softer comparator, and we're seeing that nicely pick up again now. But it's and then insurance, obviously lapping a tougher comparator, it's still got the shopping about the same level, it's held, but the switching activity is still higher, and that's 'cause the carriers are pushing their price very aggressively, but being under pressure. So insurance is currently trading a little bit above the division average, and Business Services a little bit below the division average, but still very, very strong. And there's nothing hidden we can see at all. Cyclicality, I mean, no company is immune, but we are very resilient in a cycle. So, so very comfortable on that cyclicality point. Bill, Bill, over to you on privacy. Yeah. So, yeah, on the privacy question, I mean, it's a great question. It's front and center to our business model. So we've got to think about the protection of the consumer, but the, the proper use cases associated with the data assets as well. So, everything that we do, part of the value proposition we bring to our customers is we really provide that intelligence, that structure, that process, that allows the data assets that are used as part of underwriting a risk, making those available to the consumer. So in order to kinda do that and what should be done in that whole process, we have to understand regulation, but more importantly, we also have to educate the regulators of what data is being used and how it's being used in that complete transaction by the insurance industry. We take a lot of time and effort on the education side, educating the trades and the insurance industry, as well as the regulators, in terms of what we're doing with the data, how the industry is using it. A better way to describe it is data for good, and how it's impacting consumers in a very positive way. Thank you. Thank you. Our next question comes from Carl Murdock-Smith with Berenberg. Please go ahead. Hi. Thanks very much. Fantastic presentation. You've, you've given us lots of reasons not to worry about AI and not to worry about transactional revenues. To ask a very open-ended question, Mark, what, what does worry you the most, kind of in, in terms of when you look forwards at, at the Risk's future, what are the things that you're most obsessed about in terms of the downside? And then secondly, coming back to Tom's question, about price increases and your kind of reticence to, to engage with the idea of price increases. Why is that? And I suppose, who do you perceive as your biggest competitor when you're launching these new services? Is it another provider or is it just adoption? Is it, is it the fact that you're trying to launch and push new, new innovation and new products through? Is that adoption really the, the greatest competitor of sorts that you face? Thank you. Okay. If I take the second question first about price increases, we have a strong culture, I said, of core skill in innovation in the DNA of the business. That's incredibly strong, and it's a nd I think we'd like to try and capture all the transactions and roll it across every customer, thinking about when Bill launches a product. So it's, we don't wanna get into changing the prices halfway through, so it's, we've got incredibly strong NPS scores with our customers, but it's a nd we don't feel we need to put prices up, but it's, and that focuses the whole of our effort then on that core skill innovation and many, many opportunities we can do. So price is not something we're looking to put up. But it's a good question when you ask about launching products, 'cause the process we typically go through is the core team we have are incredibly close to their market, deep customer understandings, and when they go through an ideation session, but it's with a big insurance customer, we start talking about a concept and we get some interest, but it's t hen the way it works is, if the customer is really interested and the two-flow of information is going well, they'll do what they call a retro or batch, but they'll test it on some historical data. But it's and once that test is done on a file, it can be a small file or a big file, it gives a very clear return on investment. So typically, we'll get a three or four or five percentage point increase. The Driving Behavior 360 at 15% was off the scale, but 3% or 4% or 5% increase in uplift is a meaningful test. And that will give them a very clear return on investment for how that would affect their infrastructure and their customers, but it's versus what the cost is gonna be. And then when they get through that stage, they might do a second test. This takes a few months to go through, but it's, and then they typically roll it out into one state, 'cause by definition, insurers are cautious about risk in their very nature. So it's, and then when it's in one state, they'll test it all again, then try it in maybe five states and roll it out. But it's, in that process, in 99% of the cases, we're not talking to another customer, co-competitor. It's all about how the customer is sitting with their infrastructure and how the returns are to them. So it's not a competitive kind of situation you get in other markets. It's very much around innovation and the value to the customer and really understanding what they do. So, from that perspective, it's not a competitive position. It's much more a customer relationship. Is it a compelling return on investment? Can you prove it? Can you test it? And that's the process we go through. So you're quite right, we don't see competitors in that particular part of the cycle. Thank you. And the other question about kind of AI, Vijay summed it up very well. We are 90% kind of machine to machine, and we're using kind of generative AI as a real opportunity to drive our efficiency. In terms of what keeps me up at night, it's a nd we've got a very, very strong business. It's very nicely balanced, it's very diverse. It's got four sectors that are all got great opportunities for growth, but it's so from that perspective, I mean, clearly, we'll always worry about info security, and Vijay and I and the whole of the team, that's our number one priority, and we're very, very focused on that. We're trusted by our customers with their data. So that's probably the single most important thing that we all do, but it's b ut from my perspective, it's nothing no one thing is keeping me up at night, but it's b ut I've got a career of 40 years in RELX, and it's my philosophy has always been, my focus has always been, I never relax. But it's I think if you relax, then think bad things happen. You've got to always be on the edge. But my view would be, as long as we're focusing really well on our customers, we're paying attention to our customers and staying close to their needs and how they're changing, the business will be good, and that's how I tend to think about it. Thank you. Great. Thank you very much. Yeah. Maybe time for kind of Our next question. One, one more question now, maybe, from a time point of view? Our next question comes from George Webb with Morgan Stanley. Please go ahead. Hi, and thanks for the presentation. Just one question on my end. So from a geographic perspective in auto insurance, you mentioned predominantly exposure in the U.S. and perhaps some in the U.K., if I heard correctly. So I wonder if you can talk a little bit about international and how you think about your ability to perhaps build a similar auto insurance business to what you have in the U.S. elsewhere, and if so, how you think about go-to-market strategy around that. Thank you. So I'll, I'll take that question on kind of international, and it's a nd I'll kind of take it from a kind of a risk perspective. When I came into the business in the end of 2012, the risk business was 100% focused on the U.S., but it, it was a world-class business, but it wasn't competing on the kind of international stage, if you like. And what we did as a management team was we worked on building a 10-year roadmap, but it's a nd in, and in the early part of that journey, we felt that insurance and Business Services probably had an equal kind of opportunity to go forward. So, and what we've kind of really learned in the last five years is that the opportunity in Business Services is much, much bigger than we originally thought, and it's primarily because of the global products that are available, but it's not a country by country approach, it's the global products. And that view was partly influenced by the acquisition of ThreatMetrix and that digital capability. So what we've been doing in the last five years is really accelerating our kind of focus and our resources in building on that global scale in Business Services, and it's going incredibly well, but it's much, much bigger than we thought. Now, on the insurance side, we've still got a good opportunity, but it's probably not quite as big as we originally thought right at the very beginning, but we've got a country focus. We're in a few countries, but the U.K. is the main country. And we tend to view the opportunity in insurance now as more like one of the verticals, like kind of property or commercial or life. So it's not something you can roll to every country, because all countries operate very differently, and insurance is not an opportunity for global products where you roll them out. You need that deep domain data and position. So we're still very excited by insurance international. Relatively smaller compared to Business Services, but it's but still a nice growth market, growing very fast, and it's nice to learn new things in new geographies that you can then bring back to the U.S. There's lots of benefits in doing it, not just financial benefits, but that's the kind of view we've got, a kind of international in insurance. That's really helpful. That's really helpful. If I could just tack one very final question on I mean, just in terms of why you kind of found out that the insurance international perhaps wasn't as big as you thought. I mean, what was driving that? Many different factors. It's when you think about it, there's when you think of our four key capabilities, I mean, I mean, data is a key one you need when you go abroad. You can take technology, but you can build local talent, but it's many of the markets, markets around the world don't use data in the same way, the data is not available in the same way, but it's a nd then the other one is just the sheer competitiveness. In many countries, they're not as competitive as the U.S. market, and we thrive when it's a very competitive market where people are looking for that competitive advantage all the time. So that was the kind of, that was kind of key criteria. But we're delighted with what we're doing in the U.K. It's growing very nicely, but it a nd same with China, but it's just not as big, not as big to find as many countries like that. But it's, and it comes back to when you look at our auto business, it's got tremendous opportunities. When we're not going abroad because we're, our U.S. opportunities are smaller. If anything, the U.S. opportunities are getting bigger. So it's all kind of relative to each other. Really helpful. Thank you. Yep. Okay, so I'd like to now bring this to an end. Thank you, everyone, for attending. It's been really good, and see you next time. Thank you.