Before we begin, for important disclosures, please see the Morgan Stanley Research Disclosure website at www.morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley sales representative. We are thrilled to have the CCC Solutions leadership team here today are some of Brian Herb, CFO, and Bill Warmington, Head of IR. Thank you so much for joining us today. Yeah. Thanks for having us, Josh. I'm Josh Baer, software analyst here at Morgan Stanley. I wanted to kick it off with a bit of an overview just to level set for those newer to the story. Brian, can you provide an overview of the business? Really wondering how CCC fits into the P&C insurance economy, who are your customers, what are your main products? Yeah, sounds good. For those of you new to the story, CCC's mission-critical SaaS AI platform for the insurance economy. The business is historically focused on U.S. auto claims and helping facilitate and process U.S. auto claims. We are a multi-sided network that work across many of the companies that facilitate claims. Think about insuranc e companies. We have 300 insurance companies on our platform. We have 30,000 repair facilities on our platform. We have 6,000 parts suppliers on our platform. We have all the large car manufacturers on our platform. Our workflow and AI tools bring those parties together to drive and facilitate a claim resolution. The things we do is we help them with claim automation. We help them with if a car is repairable. We help them with the total loss. We help them if there's auto, medical Casualty part of the claim. All of those processes are facilitated through our platform, our tools, our AI. We recently expanded. We acquired a business EvolutionIQ of January of last year in 2025 that had AI tools that has moved us into the disability market and workers' comp market. That's new for us, but it certainly takes the same principle of claim resolution and using AI tools. It's just opened up new markets. Speaking of kind of expanding that opportunity, how big is your TAM, and how do you, kind of frame the, you know, what's addressable and what you can capture? Yeah. If you think about it globally, it's about $35 billion is the global TAM. When you think about it in the U.S., it's about $15 billion here in the U.S. The most immediate part of that is if you look at our existing products and solutions that we have in the market today, it's about $7 billion of opportunity. Today, we're about $1 billion of run rate revenue. You can see from the $1 billion we have today to the $7 billion for our existing products and solutions, that's the white space that's right in front of us. Excellent. You've had just tremendously consistent results over a long period of time, thinking about, you know, high single digit, 10% + growth rate. Right Great margins, usually expanding 100 basis points general philosophy. What's priced into the stock, obviously a lot of risk. I wanna jump in and really talk about the key debates that are impacting the stock. First and foremost is how AI impacts your business. From my perspective, you've got vast proprietary datasets, you have a network effect, and this data advantage helps to train your AI models. I was hoping you could unpack that a little bit and maybe add to what really creates your competitive moat and specifically around AI. Yeah. You, you touched on them, but just let me go a bit deeper. If you think about the dataset to start with. We have claims data from the clients, but we have much more than that. If you think about the other data that we use to facilitate a claim or a claim resolution, it's much broader than what's in the four walls of the client and their own claim data. We take part prices, labor rates, taxes and fees from different jurisdictions, all the different rules that carriers have, and the list goes on and on. All those datasets, Build Sheets from car manufacturers, they all come into the platform along with the claim data, and we bring it together to really help drive those decisions and recommendations. The dataset is certainly a really important part of it. We also have these deeply embedded workflows that facilitate and drive actual decisions. When you think about what we do, we're not providing AI insights, we're providing recommendations for decisions that are embedded deep into our client's workflow. That is, you know, is also a very big differentiator. The third I would highlight with the workflow, we connect the various players in the ecosystem. We have 300 insurers on our platform. We have 30,000 repair shops on the platform. We have 6,000 part suppliers. That scale really matters. Each part of the trade partners that are on the platform, they benefit from the scale. So, if you're an insurance companies, you wanna have a lot of repair facilities to give your policyholder, policyholders flexibility on what shops to use. If you're a repair facilities, it benefits you to have a lot of insurers on the platform because insurers are the largest place that will drive leads into the repair facilities. If you're a part supplier, it's helpful to have a lot of repair facilities. The benefit accrues to the companies on the network, and scale matters. Those are some of the things that are really important in how we think about what we do and the value we drive our clients. On the data point, I just wanted to say that it's not just $2 trillion of historical data. One of the keys is also that we're processing $1 billion in claims a day. By being in the center of that universe, we're getting the data flows that allow us to then adjust the models and correct for drift over time. Of course, we're the ones who are actually proactively putting the AI into those workflows for the clients. Excellent. Wanted to expand and talk about two areas of competitive risk with regard to AI potential. One is in-housing, which is a concern in the market that, you know, customers in any sector of software, but in your case, the large insurance carriers who already, you know, invest in their own, you know, some of their own capabilities in-house might look to replicate some of the CCC products or workflows. You know, could you comment on that? What are you seeing in your customer base? What gives you confidence that carriers will continue to partner with CCC rather than build themselves? Yeah, I mean, it goes back to those fundamental points that we talked about. I won't be redundant, but if you think about what we're doing for an insurance company, they have large IT budgets. They are investing in AI. When we think about kind of driving the claim resolution, it is a very nuanced and complicated set of decisions. That set of decisions, as we talk about, is taking in data sources outside of what the carriers have access to. It's out-data outside of the four walls of those carriers. If you think about it, just take an example of what we're helping them do. If you're a carrier and a policyholder has an accident, we help them through AI determine if that is a repairable car or if that car is a total loss and should be taken to a salvage yard. At the first point we're helping through AI make that decision or make that recommendation for the carrier. To make that recommendation, you need to know what it's gonna cost to repair that car. You're gonna need to know what are the part prices that are gonna be on the repair. You're gonna need to know how many hours it's gonna take for labor rates. What is the labor rate in that specific jurisdiction? Because labor rates are different in L.A. than they are in Lincoln, Nebraska. You're gonna need to know how many hours it's gonna take, et cetera, et cetera. We give them a view of the cost of repair, and then they compare that to should they total loss. That data and those decisions are very difficult to replicate. That's just one example of the suite of products that we provide, but it also shows how complicated and nuanced those decisions are, and we feel that the value we drive with our customers in helping them make those recommendations and decisions. I think that's clear. Just to round it out on the threat of new entrants. Mm-hmm. I'm sure, you know, some of what we've just discussed applies for, you know, an AI startup coming in, how to think about that threat. I mean, one question that I've heard from investors, is like, what about EvolutionIQ? Like, if the answer is just, "Oh, that's really hard," well, like how, you know, how did EIQ, you know, enter the space and grow so rapidly and be successful? Yeah. So there's two different questions in there. If you start with new entrants and think about U.S. auto claims, again, I would go back to the dataset. I'd go back to the scale and the network and the ecosystem. We certainly see entrants come in and kind of will look at a very narrow part of the processing. Can they provide software or AI tools in a very specific area? What we do is we really provide the client end-to-end. From First Notice of Loss, there are 100 decisions that are made across multiple trade partners to get that claim fully resolved so the policyholder goes back to pre-accident condition. For that full set of decisions and processes, we feel like we're uniquely positioned to be able to help the carrier through every step of those decisions. New entrants come in, they can attack a part of that process, we haven't seen someone come in and able to take the breadth of what we do. It goes back to data. It goes back to the network and the ecosystem and the complexity of it. That's how we think. I mean, certainly we remain very vigilant around the competitive landscape and new entrants and making sure that we're always investing ahead. Innovation is our competitive advantage, that we stay ahead of where the market is going, what the client needs are, and making sure that we have the right solutions to support the clients. EvolutionIQ, I think is a bit different. It's outside of auto claims, and it is supporting traditionally it is, and we'll talk about them moving into kind of cross-selling into our base. It has historically been in disability and then into workers' comp. They have, you know, when they go in and they're selling, they're really selling against in-house capabilities. They have, over time, shown through ROI that their models and their platform are performing better than the in-house for the clients that have switched. What will normally happen is a client will look at EvolutionIQ, test their software and their AI, kind of almost in an AB test, and then take a part of their book, run it through EvolutionIQ, and take part of their book and run it through the ways they operate. EvolutionIQ has shown that they have a higher benefit and a higher ROI, and that's why they win. They have nine of the top 15 disability carriers that are using their platform. They've moved into workers' comp and have started to win in workers' comp. You know, they continue to really have this meaningful ROI, and what they do is they usually sell in at one module, prove the value of that one module, and then expand with cross-selling additional modules, and they've seen a lot of success on that. Perfect. Just to be clear, the disability and workers' comp area, you were not previously in. That's correct. You're not disrupting. Okay. Exactly. When we acquire them, that was an opportunity for us to expand the TAM and move into those new markets. Right. Sort of round out the conversation on competition, can you just update us on what you're seeing as far as gross retention, sort of as a proof point, at least so far- Yeah -of you know, customers retaining their spend? Yeah, exactly. Gross Dollar Retention is 99%, and it's been 99% for the last two years. It's since we've been public, it's been between 98 and 99. It really highlights the stickiness of the platform and that clients stay on the platform. Even the churn that we see is really at kind of the low end of the repair shop, and most of that is just churning off the, you know, people moving to, you know, either shutting down facilities or acquisitions of facilities. We're really proud of the Gross Dollar Retention. It highlights the stickiness of the product, but it also highlights the services that we put around the products and the high NPS scores that we have. Great. Wanna ask one on autonomous, which has the potential at least to reduce accident frequency, I think, and probably reshape the auto insurance market. How are you thinking about the impact of autonomous on CCC's claim volumes and also the business model value proposition, and does the shift toward AVs, you know, create new opportunities for you? When you think about macro trends for carriers and our clients in general, there's kind of three macro trends. One is frequency, so the amount of accidents that happen. We do expect, and we've seen this, that frequency will moderate, have slight decline over long periods of time. And that's been a trend that's been in the system. The other two macro trends, one is the cost of the claim. So how much would it cost to repair the car, or if there are medical injuries, what's the cost to resolve that claim. We call that severity. Severity is certainly going up, and it's going up faster than frequency is moderating. The third is complexity. And that's really another macro trend that is growing at a really rapid pace. When we think about what we do for our clients and the value that we add, a lot of it comes down to how are we helping them manage the complexity. The ecosystem around a claim continues to grow. The number of part prices continues to grow. You have calibrations, you have scans, you have sensors, you have cameras. All of that continues to just add into the complexity. What we think about and the solutions that we bring for our clients is how do we help them drive resolution of a claim, and cut down cycle times, help them with their operational cost, and at the same time help them manage growing complexity around the ecosystem. That's why we feel like we're uniquely positioned to support clients as we go forward. Excellent. You've quantified the percent of your total revenue comes from AI-based solutions at 10%. Was hoping you could dig in a little bit. What are the key products? How to think about that opportunity? Within that, about half of that, just under half, is EvolutionIQ. That was the acquisition that we made. That business, using AI models to support disability and worker comp, is 100% AI. We also have AI in production with products like Estimate STP and the newer AI models from the launch of Estimate STP was like November of 2021 and bring that current. All of the AI is in that $100 million. There is a segment of that $100 million is pre-Estimate STP, which is more of the legacy models. Kind of think about those as kind of early models that are still in production. Clients are still using them, and they're driving revenue, but they're not necessarily kind of the rapid growth. The rapid growth cohort are the solutions that are sitting in our emerging solutions bucket, if that makes sense? Great. Can we double-click on Estimate STP? Yep. Where are we as far as adoption? What% of claims runs through STP, and what's the opportunity? Yeah. Estimate STP. For those of you that are newer, what that is using computer vision AI to determine the cost to repair the car. Someone can use their camera to take photos or video of the car. Within minutes, turns into a line item estimate that says this car will cost $4,535 to repair at a line item level with part prices, labor rates, labor hours. That's the product, what it does. We have 40 clients on Estimate STP using it at different levels, different penetration rates. About 5% of total claims are running through Estimate STP. We continue to see it grow in scale. I would say the clients are in different stages of adoption, the ones that are using it. You have some clients that are at the very early innings and have, you know, very little percentage running through, and they're kind of in the test and looking at how they operationalize it and roll it out. We also have a large national carrier that's running 20% of their volume through Estimate STP and really leaning into it and operationalizing that. We will continue to see that grow in scale. It will be further clients coming onto the platform and using it, and then the clients that are on the platform will continue to put more and more of their volume through it, and it will continue to grow in scale. Just to understand the value for both your customers and for you, what does it do from a cost perspective as far as savings, or how does that change their business? Yeah. How do you monetize it, and what's the difference once it goes through? Absolutely. All of our products are really sold on an ROI basis. What we do is we look at how the carrier operates kind of pre the tools, and then after they deploy the tools, what are the likely benefits that they're gonna see, and then we price the product on a 5-to-1 ratio. Kind of pre-Estimate STP, you can imagine a world where a policyholder calls into the insurance company, says, "I have an accident." They send an adjuster or an appraiser out in the field. They're driving around in their car. They're making an appointment to go to a driveway to look at the car, take software and write up the estimate and say, "Okay," to the policyholder, "here's your cost to repair, and then here's your next steps." Think about you have staff time, you have travel time. That estimate in that scenario is costing hundreds of dollars. Instead, you're using Estimate STP, you're deploying a link and the policyholder is taking the photos, and then the estimate is getting initiated through AI. You're going from one experience to something that takes minutes. From a carrier, they can just look at staff levels. They can look at the cost for that estimate. Using Estimate STP is significantly, you know, a significant cost improvement. That's the value we drive, and then we price in roughly a 5-to-1 estimate. If that estimate in the old world cost $100, Estimate STP costs $20, that's a win-win. Perfect. Yeah. You get much tighter, range of outcomes when you're using Estimate STP as well. If you take a couple of adjusters who have, you know, 25, 30 years experience and you ask them to write an estimate on a car, it could be 25%-30% variance in those two estimates. With Estimate STP, you definitely get a narrower variance on that. Great. Let's zoom out from Estimate STP. Yeah. Maybe think about the broader emerging solutions portfolio, which is one of the key drivers of growth contribution looking ahead. What else is in that portfolio that, you know, is really impacting the financials? Yeah. Yeah. It's a cohort of products that we've launched more recently over the past couple years. It's about 4% of total revenue. It's growing, you know, roughly about 70% year-over-year, so really good growth. It has AI products that sit across our APD solution set. Estimate STP that I talked about is one example of the AI solutions, but there's a broader set of AI solutions that are in there. We have subrogation, which is a solution to help determine liability between two carriers and then help them recover liability from one carrier to another. We're digitizing that through our subrogation tool. We have products for the repair shop. We have Diagnostics, Build Sheets are a few of the examples. We have both kind of these high growth products at the carrier side. We have these high growth products at the repair shop side. We're still early days of scaling them, but they're gonna drive, you know, significant growth contribution as we go forward. Okay. Let's zoom out one more time. Now you have emerging solutions. You talked about for the size of the market and your share, clearly you're a share leader. How much more runway is there for growth from new logos? Yeah. What about these e-established solutions if you talk about the growth algorithm? Yeah. So historically, what we've looked at from kind of a growth contribution, it's roughly been, you know, 30% coming from new logos, 70% coming from cross-sell, up-sell. Over time, we do expect new logo contribution to be lower, so going from 30% contribution to 20% just because we have market, a market leadership position. We look at repair shops, say there's about 40,000. Today, 30,000 are clients. We have over 300 insurance companies. We continue to grow new logos, but it will be a smaller part of the growth algorithm. That would be about 20% of growth, and the balance, 80%, will come from cross-sell, up-sell. We talked about emerging and the contribution of that. There are areas in our established product set that have good growth runways in front of us. Casualty is a product in established that we talk a lot about. If you think about our APD solutions, we have 300 clients on APD. It generates, you know, roughly around $400 million. Casualty is about $100 million of revenue, about 10% of the overall business, has 50 clients on it. At scale, Casualty could be as big as our APD business, a lot of runway with our Casualty solutions. We think about the repair shops and upgrading the software there. We continue to roll out new modules, new technology. We see good opportunity in the repair facilities, in upgrading the packages. You know, parts suppliers, diagnostic suppliers are still very you know, early days of digitizing, and see really good opportunity in that part of the business as well. Lot of ways to grow, a lot of ways to win, both on our established solutions and our emerging solutions. Okay. Excellent. You just hit on your whole product portfolio, which was great. Let's talk about some numbers and some margins. I think this year, excluding EvolutionIQ, you expanded EBITDA margins by 200 basis points. Can you talk about some of how that was possible, and, you know, where do you go from here? Yeah, we were really happy with the margin progression in the year. I mean, what one data point is year-over-year, outside of the acquisition of EvolutionIQ, year-over-year, headcount was flat. We absolutely continue to invest in new innovation, continue to support a very robust roadmap. At the same time, we do see areas of opportunity for productivity. We were able to manage the headcount to flat, and that was the largest part of why we're seeing the margin progression that we saw last year. On average, we talk about 100 bips of margin progression per year. At, you know, we're at 4,200 margin progression per year. We've put a target out there at about 45% as a medium-term target. There's no ceiling there that says when we hit 45, we have to stop. We're just putting a target out there that feels realistic that we can get to in a few years. It's a very efficient cost base. You know, our software is all GA. It's a single instance. We feel that it's a really scalable business model. As revenue scales, we have a lot of operating leverage that drives margin progression. 45%, you know, plus margin target. From a growth perspective, are we still thinking about the 200 basis points of incremental growth from EIQ on top of the 7%-10%? Is that 9%-12% on a durable basis? Is that the right way to think about growth? Yeah. That is. I mean, that's the way we frame our growth. I would say, you know, EvolutionIQ has a long runway. We're seeing really good opportunities with them, both from them scaling in the disability and workers' comp market. We're now seeing early wins as we bring their capability across to our client base and start to cross-sell EvolutionIQ capabilities into auto casualty. In the earnings, Githesh highlighted, we had our first cross-sell win with a auto client taking MedHub, which is a medical summarization synthesis platform that helps carriers kind of digest all the medical information, both structured and unstructured, and have recommendations in what to do. That is something that EvolutionIQ has in market, and Disability has in market, and workers' comp, and we're now bringing it to auto Casualty, and we had our first win. Lot of space for EvolutionIQ to go. The core business outside of EvolutionIQ, we've talked about kind of 7-10 as a long-term revenue range. We feel really good about that. That's organic? That is organic, correct. Just to follow up on the EIQ win and the cross-sell, are there further investments needed from a go-to-market? Is that, you know, fully set up, that everyone is selling the whole portfolio? There are ongoing investments, but what it really means more than that is just bringing the EvolutionIQ and the product specialists from that team and having them work closely with kind of the CCC team. The CCC team has these great relationships with these national accounts. EvolutionIQ has the specific, you know, product specialty and bringing them together and taking the best of both of those teams really gives us, you know, what we need to be successful as we scale go to market. It's less about investment. It's more around bringing the teams together and continue to integrate the acquisition. Got it. As AI and emerging solutions increases in mix, how does that impact the gross margins of your business? Yeah. Like, when we look at the unit economics of AI, either at EvolutionIQ or AI within core CCC, the unit economics are good. When you look at them versus our historical products, they will have similar gross profit characteristics. We, we don't see necessarily AI in production putting a drag on gross profit. What we've seen in gross profit has shifted down slightly over the past couple years. It was more in the upper 70s. Last year it was 76%. It's more as we bring these new set of solutions into market, the cost will outpace the revenue until the revenue scales. When we launch a new product, the depreciation of that product starts to get amortized and runs through the P&L. The support cost for that new product starts to ramp up. The revenue, it's SaaS, so it's not lumpy. It builds up over time. When we're in these subscale launches, it has pressure on gross profit until it gets to scale. Once it gets to scale, it will have characteristics of our more mature products. Did want to come back to claims volumes, because it is one of the key topics of conversation with investors. It has been a modest headwind for you. What's the latest that you're seeing from claims volumes? Also wanna ask, is there there is a piece of it, your business that's transactional. Correct. Is there a way to sort of remove or lessen the exposure to transactional increase, more recurring subscription revenue there? Yeah, absolutely. I mean, if you look at where we had been, it the mix was more like 80/20, so 80% subscription software, 20% transactional. We continue to shift it towards more subscription, through renewals on Casualty or Casualty client, which has historically been a transactional business. Renewals through our smaller carriers. Most of the large national carriers are on kind of full subscription deals. Where we see transactionals in the smaller carriers, but through renewals, we're moving them to subscription as well. We highlighted that when we look at the business now, it's more like 85% subscription, and 15% transactional. We are seeing it move, and I expect it to continue to shift towards subscription over time. The business will be less exposed to just in-year claim volume, as we move that mix more and more to subscription. The, the first part of your question is what we're seeing on claim volume. We are seeing ongoing moderation. In Q4 of last year, total claims were down 6%, but a, a part of that was weather-related events that it lapped in 2024. Those are kinda one-off items. When you strip that out and you look at kind of on a normalized basis, claim volume was down about 3%. That continued to moderate throughout 2025. As claim volume continues to moderate and our subscription continues to be a larger part of the revenue, this just becomes less impactful on the growth as we go forward. Just to make sure I understand, the weather events, is that a light winter? It was more in 2024. There was a bunch of hurricane storms that hit the East Coast. Those events drove you know, substantial claim activity. Oh, okay. Okay. We didn't have the same activity in Q4 of 2025. It's just the comp that we were running over in 2024. Excellent. In the last few seconds, just wanna touch on capital allocation. If you could hit on your buyback, Brian. We'll end it there. Sounds good. We announced $500 million in December of last year. Within that $500 million, we did a $300 million ASR. That was kinda mid-December. We retired 33 million shares within that ASR. We are currently in the open market buying. When we complete the ASR, we then have $200 million that we said we will use free cash flow to continue to buy against. We feel good. I mean, clearly, the stock, it's a buying opportunity. We believe the stock is undervalued. We'll continue to look at buybacks because we believe it drives long-term shareholder returns. Excellent. Thank you, Brian. Yeah. Thank you, Bill. Thanks, Josh. Really appreciate it. Appreciate it. Yep. Great.