RELX PLC (REL) Earnings Call Transcript & Summary

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 going to 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 how Risk fits within RELX. Risk represents around 35% of RELX revenue and about 40% of the profit. Our trailing 12-month revenue to June was GBP 3.1 billion or about USD 3.7 billion. The business is already 99% electronic. And by geography, 80% of our revenues are currently from North America. And 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 bidding, and less than 5% comes from one-time transactions. We serve 4 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, Business Services 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 Industry Data 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 continued on a strong and consistent trajectory, with a 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 these out over time. We're not only a high-revenue growth business, but also 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 5 years. And 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 4 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 data sets, 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 to 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, solve different problems in different [ subsegments ]. We load 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-plus years, within the insurance industry. I was part of the startup in the late 80s that became ChoicePoint, which was acquired by RELX in 2008. I became the CEO of the Insurance business since 2011. After all these years, I can honestly say that I'm more excited about the market today than I have 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 USD 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 volumetric elements. There are very few one-time transactions. The markets that we operate in are largely scaled 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 and 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. And 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 4 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 workloads, 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 Risk, we have extensive data on motor vehicle records, also known as MVRs, which includes information on car registration, 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 2 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 5 years, we have launched or expanded 6 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 have 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 in 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 90s and continue 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 [ quote ] to an individual application, they [ quote ] to our platform through 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 that a carrier can automatically pull the right data and risk scores to make critical decisions in real-time. We excel at 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 has 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 process. 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 are 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 5 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 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 their 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'll reduce this friction once the consumer starts their shopping journey. And at the end of the insurance workflow, we help carriers improve their compliance in claim processes. Claims are a critical component of profitability for an insurance company. Roughly 50% of the insurers' 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 consumers 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, from a 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 develop 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 the consumers' price per 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 U.S. 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 are 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. U.S. 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. And in attempts to manage their profit, they're selective on where they perform inspections. Between 10% to 20% of homes are typically inspected when underwriting a new policy, with even fewer being inspected when a policy is 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 the 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. So 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 their 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. So 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 are 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 walk-through. 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 a capability of servicing risk and recall information for appliances that often cause losses, like hot water heaters and refrigerators, washing machines, as well as recall 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 are 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 2 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 4 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 at RELX for over 20 years. I'm also the chair of 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 advantage. You have seen this slide before, but it is an incredibly important one. It demonstrates how we get from data to specific actionable insights to 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 much value for 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. And this paid off. And 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 their expansion 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. And 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 with deep experience and expertise in big data and AI and ML techniques. This is roughly 1/3 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, 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've heard a lot about this from Rick Trainor in 2021. This is data that we have on devices, digital identities, e-mail 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 in 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've heard about this as Cole demoed Flyreel. We layer advanced analytics and 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 cost, 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 from 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. With 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 for establishing the creditworthiness of consumers, for 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. So 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 4 key capabilities: deep customer understanding, leading data sets, advanced analytics and linking and technology. And this combination gives us real competitive advantage. And our objective is to continue to deliver strong underlying revenue and profit growth for a long time to come. And with that, I think we're ready for questions.

Our first question comes from Nick Dempsey with Barclays.

Three questions, if I can, please. The first one, have -- at the beginning of the presentation, Mark pointed to managing underlying cost growth below underlying revenue growth of the Risk division. I guess in recent years, we've watched the guidance before underlying operating profit 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 C.L.U.E. in auto? And 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 going to 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. If you look at our Risk business, we've got incredible scale in data and technology, and it's -- 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 -- 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 going to 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 happen with the numbers, but it's smaller, I'd say. But yes, I do see a change there. Bill, over to you for the second question.

Yes. 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 and 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.

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.

Yes. So from our perspective, we're doing a great job. We have an incredible data set associated with that. I 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 going to set us apart.

So I'll pick up the third question around autonomous cars is -- we're very excited by the kind of the advancement of technology in cars. What you're seeing is that the crashes are going down, but the severity and the cost of repair is going up. And that's really affecting profitability of 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 providing the market with how you compare Renault with a Ford or a GM car for all 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. And the fact that electric cars are coming in and we're giving insurers information on how people move from a petrol or a 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 there is that the more complex the market is, the more technology is coming in, how we are interacting with it 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 standardize stuff, normalize stuff and take it down to those models, and Bill talked about 700 analytical models. Well, that's just playing to our strength in data. So 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.

Our next question comes from Adam Berlin with UBS.

Just got a couple of questions. The first is you talked a little bit today about the M&A you've done in the last 5 years and how that created new data sets for you. Can you talk a little about where the pipeline is at 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 help me understand. And the second thing I wanted to understand was with the transactional revenues, can you talk a bit about the billing cycle, how that works? So does an insurance company use a certain amount of data over a quarter and then send them a bill and how many [ days do ] they pay you? Can you just talk about the working capital and how that flows through to Risk? I'd really appreciate that.

I'm going to take the first question and 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 the key question we ask ourselves is, are we the natural home? And very often, acquisitions will bring data or bring technology, it will bring competency and bring talent. But it's -- and probably our best example recently -- in recent years we talked about, was ThreatMetrix that ticked all those boxes. And that, combined with Emailage acquisition and organic stuff we've done there, has given us a wonderful position in that digital fraud in [ identity ] market, and we talked about that in the '21 seminar we did together. So -- and I think going forward, we have no clear strategy on acquisition. 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 a 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 start-ups and evaluating them, 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?

Yes. On the transactional revenue, it's always a good question in terms of the cycle is how the market buys intelligence about the risk, and it is per transaction. And we're within the workflow, and the transaction is affiliated with that. Our contracts, typically, are multiyear, 3- to 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 at the order over that 30-day period.

That's great. Can I just ask you a question, Mark, about fraud and identity as well whilst we have you? Is that okay?

Okay.

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 companies, payment companies of the start-up. Can you just talk a little bit about how you're differentiated in the fraud and identity market? Is it just through ThreatMetrix or there are other things you've got that set you apart from all those competitors in that area?

Okay. So I mean, the key thing that stands us apart and differentiates us is that 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 physical identities -- [ digital ] identities is -- the scale is 2 or 3 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 competitively, 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 in e-mails in vast number. I think we're tracking about 3 billion different e-mails. So it's the scale that gives us a real competitive advantage on fraud and identity. And we are the clear market leader. When you then combine that with the physical data we have, that puts us in a wonderful position. And we talked that through last time in the '21 seminar we did, and that position is still the same, we have real competitive advantage in that combination of digital and physical fraud identity.

So are you now -- 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?

Yes, we have got that in early phases, yes, we have got that, yes. And that's the core strength of our business how we bring the two together. Thank you.

[Operator Instructions] Our next question comes from Tom Singlehurst with Citi.

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 normally -- and I might have missed it, but normally, you take an opportunity to say that your growth is 100% volume-driven, and it hasn't been driven by pricing. I'm just interested on the question of pricing. I presume it's still largely a volume [ gain ]. But 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 going to be driven more by the interest rate cycle. You're not going to be driven by that, I completely understand it. But are you -- 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 very [ endemic ] to certain key markets, and it's not necessarily governed by the same rules as sort of more consumer-facing marketplaces. But can you just talk about what protection do 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?

So I'm going to take the first two, and then I'll 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 on it. And we have a core skill innovation, particularly Insurance, but across the group, particularly Insurance that when we launch a product and we price it at the beginning and we price to the value we're creating the customer, we then don't change that price. So -- and then we get our growth from rolling that product out across the customer we're selling to and getting to more and more states and getting more and more customers. And then you get growth from launching new products. And what that's reinforced in the Insurance business in Risk is everything is about the course of innovation because we don't put the price up, which is easy. You've got a real course of innovation in the DNA of the business, and that's incredibly important. And if you look at this slide, I think it was Slide 19, which was Bill's chart on innovations, and internally, we call that Bill's CV or Bill's resume, but it's -- and 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 5 years, we've launched more products than any other time in our history. So -- and when Bill and I look at our innovation pipeline, going forward, it's equally strong. So it really reinforces the course of innovation in the DNA of the business, which is important. The second question is around cyclicality. So it's -- 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 kind of key one. But I think the key thing is we're in big markets. Take the insurance spectrum right across or take fraud entity or compliance, they don't go down when things are tough. If anything, as an argument, they get stronger than some. And we're providing our customers complex solutions that are critical to them. And we're deeply embedded into the workflow. And a typical cost, as we pointed out, is significantly less than 1%, but it has a massive impact on the kind of core business. And 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 a recession, Insurance actually grew very strongly. And there are two key reasons to that: And the first is when consumers are under pressure, one of the first things they do is they [ stop ] their insurance and they try and switch, and that puts the activity up. And the second reason why it grew very strong in 2009 is because the Insurance business has a great track record of launching new products. And you remember that chart we showed, the green and the orange, and it's -- and the orange is critical. And if you look back in that period of time, we used to get 3 or 4 points of growth, in the orange. We're now getting 5 percentage points of growth. So that's what we're doing now. And then in more recent times, when the economy tightened in the second half of '22, we saw the Business Services transactions just slowed down a fraction of growth, still growing, but just a fraction slower. But at the same time, in H2, '22, we saw the Insurance market picking up. And again, that's the consumers stopping their insurance when times are tough. But it's -- and what also happened is they actually stopped a bit more. So when we get to where we are now, so we've got to the second half of '23, Business Services were 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, is still got the [ shopping ] about the same level is held, but it's -- but the switching activity is still higher, and that's because the carriers are pushing their price very aggressively, being under pressure. So Insurance is currently trading a little bit above the division average, and Business Services is a little bit below the division average, but still very strong. And there's nothing hidden. We can see it all, cyclicality. I mean, no company is immune, but we are very resilient in the cycle. So very comfortable on that cyclicality point. Bill, a bit over to you.

Yes. 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 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 kind of do that, what should be done in the 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. So 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, and a better way to describe it is data for good; and how it's impacting consumers in a very positive way.

Our next question comes from Carl Murdock-Smith with Berenberg.

Hi. Thanks very much. Fantastic presentation. 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 does worry you the most kind of in terms of when you look forward? At 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 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 the fact that you're trying to launch and push new innovation and new products through? Is that adoption really the greatest competitor of sorts that you face?

Okay. I'll take the second question first around price increases. We have a strong culture, as I said, a core skill of innovation in the DNA of the business that's incredibly strong. And it's -- and 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 we don't want to get to change their prices halfway through. So we've got incredibly strong NPS scores with our customers, but it's -- and 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 of 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 asked about launching products because the process we typically go through is that 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. And then the way it works is if the customer is really interested in it and the two flow of information is going well, they'll do what they call a [ retro or batch ], where they'll test on some historical data. But it's -- and once that test is done on a file, it could be a small file or a big file, it gives a very clear return on investment. So typically, we'll get a 3 or 4 or 5 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 versus what the cost is going to be. But some -- and then when they get through that state, they might do a second test. It takes a few months to go through, but it's -- and then they typically roll it out into 1 state because by definition, insurers are cautious about risk in their very nature. when it's 1 state, they'll test it all again, then try it in maybe 5 states and roll it out. But it's -- in that process, in 99% of the cases, we're not talking to another customer -- 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 more -- much more of 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. 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 -- and we've got a very, very strong businesses. It's very nicely balanced. It's very diverse. It's got 4 sectors that are all got great opportunities for growth. But it's -- and 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 #1 priority. 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 we all do. But from my perspective, there's nothing -- no one thing is keeping me up at night, but I've got a career of 40 years in RELX, my philosophy has always been, my focus has always been, I never relax. But it's -- I think if you relax, I think bad things happen. You've got to always be on your 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.

Our next question comes from George Webb with Morgan Stanley.

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 could 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 U.S. elsewhere? And if so, how you think about go-to-market strategy around that?

I'll take that question on kind of international. And I'm going to 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. 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 is we worked on building a 10-year road map. 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. And what we've kind of really learned in the last 5 years is that the opportunity in Business Services is much, much bigger than we originally thought. And it's primarily -- it's because of the global products that are available. It's not a country-by-country approach, it's a global product. And that view was partly influenced by the acquisition of ThreatMetrix and that digital capability. So what we've been doing in the last 5 years is really accelerating our kind of focus and our resources in building that global scale in Business Services, and it's going incredibly well, much, much bigger than we thought. Now on the Insurance side, we 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-by-country focus. We're in a few countries, and the U.K. is the main country. And we tend to view the opportunity in Insurance now is 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, all countries operate very, 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 still a nice growth market, growing very fast. And it's nice that there are new things in new geographies that you're going to bring back to the U.S. There's lots of some benefits in doing it, not just financial benefits. But that's the kind of view we've got of kind of international in insurance.

That's really helpful. That's very helpful. If I can just take one very final question, I mean, just in terms of why you kind of found out that the insurance international perhaps wasn't as big as you thought, what was driving that?

Many different factors is -- when you think about it, there's -- when you think of our 4 key capabilities, I mean, data is a key one you need when you go abroad. You can take technology, you can build local talent, but it's -- many of the markets around the world don't use data in the same way, the data is not available in the same way. And 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 at that competitive advantage all the time. So that was kind of a key criteria. But we're delighted with what we're doing in the U.K., it's growing very nicely and same with China, but it's not as big to find as many countries like that. And it comes back to when you look at our auto business, it's got tremendous opportunities. We're not going abroad because our U.S. opportunities are smaller. If anything, the U.S. opportunity is getting bigger. So it's all kind of relative to each other.

Really helpful. Thank you.

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.