CCC Intelligent Solutions Holdings Inc. (CCC) Earnings Call Transcript & Summary

Good to go. All right. Before we begin, for important disclosures, please see the Morgan Stanley research disclosure website at www.morganstanley.com/researchdisclosures. And if you have any questions, please reach out to your Morgan Stanley sales representative. We are thrilled to have the CCC Solution leadership team here today are some of Brian Herb, CFO; and Bill Warmington, Head of IR. Thank you so much for joining us today.

Yes. Thanks for having us, Josh.

And 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 and really wondering how CCC fits into the P&C insurance economy? Who are your customers? What are your main products?

Yes, sounds good. So 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. And we are a multisite network that work across many of the companies that facilitate claims. So think about insurance 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. And our workflow and AI tools bring those parties together to drive and facilitate a claim resolution. So the things we do is we help them with claim automation. We help them with -- if a car is repairable, we help them with a total loss. We help them if there's auto, medical casualty part of the claims. So 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 2025, that had AI tools that has moved us into the disability market and workers' comp market. So that's new for us. But it certainly takes the same principle of claim resolution and using AI tools is just opened up new markets.

And speaking of kind of expanding that opportunity, how big is your TAM? And how do you kind of frame what's addressable and what you can capture?

Yes. So 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. So 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. So you've had just tremendously consistent results over a long period of time, thinking about high single-digit 10% plus growth rate and great margins, usually expanding 100 basis points general philosophy. What's priced into the stock obviously, a lot of risk. So I want to jump in and really talk about the key debates that are impacting the stock. And first and foremost is how AI impacts your business. From my perspective, you've got vast proprietary data sets. You have a network effect. And this data advantage helps to train your AI models. But I was hoping you could unpack that a little bit and maybe add to what really creates your competitive moat and specifically around AI.

And you touched on that, but just let me go a bit deeper. So if you think about the data set to start with, so we have claims data from the clients, but we have much more than that. So 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 4 walls of the client and their own claim data. So 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. And so all those data sets, 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. So the data set is certainly a really important part of it. We also have these deeply embedded workflows that facilitate and drive actual decisions. So when you think about what we do, we're not providing AI insights. We're providing recommendations for decisions, better embedded deep into our clients' workflow and that is also a very big differentiator. And then the third I would highlight with the workflow, we connect the various -- the players in the ecosystem. So we have 300 insurers on our platform. We have 30,000 repair shops on the platform. We have 6,000 parts suppliers and so that scale really matters. And each part of that -- the trade partners that are on the platform they benefit from the scale. So if you're an insurance companies, you want to have a lot of repair facilities to give your 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. And if you're a parts supplier, it's helpful to have a lot of repair facilities. So the benefit accrues to the company's on the network and scale matters. So 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. And so by being in the center of that universe, we're getting the data flows that allow us to then adjust the models and correct or drift over time. And then, 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 2 areas of competitive risk with regard to AI potential. One is in-housing, which is a concern in the market that customers in any sector of software, but in your case, the large insurance carriers who already invest in their own, some of their own capabilities in-house might look to replicate some of the CCC products or workflows. 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?

Yes. I mean it goes back to those fundamental points that we talked about. So 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. But when we think about kind of driving the claim resolution, it is a very nuanced and complicated set of decisions. And that set of decisions, as we talk about, is taking in data sources outside of what the carriers have access to. It's the data outside of the 4 walls of those carriers. And so if you think about -- just to take an example of what we're helping them do. So 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. So at a point of -- 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 going to cost to repair that car. And so you're going to need to know what are the part prices that are going to be on the repair. You're going to need to know the -- how many hours it's going to 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 going to need to know how many hours it's going to take, et cetera, et cetera. So we give them a view of the cost of repair and then they compare that to should they total loss. So that data and those decisions would be -- are very difficult to replicate. So 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 and helping them make those recommendations and decisions.

I think that's clear. Just to round it out on the threat of new entrants. I'm sure some of what we've just discussed applies for an AI start-up coming in. How to think about that threat? And I mean one question that I've heard from investors is like what about EvolutionIQ? Like if the answer is just that's really hard. Well, like how did EiQ enter the space and grow so rapidly and be successful?

Yes. So there's 2 different questions in there. So if you start with new entrants and think about U.S. auto claims, again, I would go back to the data set. 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 AI tools in a very specific area. What we do is we really provide the client end-to-end. So 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. When new entrants come in, they can attack a part of that process, but we haven't seen someone come in and able to take the breadth of what we do. And it goes back to data. It goes back to the network and the ecosystem and the complexity of it. So 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 really -- 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. But it has historically been in disability and then into workers' comp. They have -- when they go in and they're selling, they're really selling against in-house capabilities. And 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. So what will normally happen is a client will look at EvolutionIQ test their software and their AI, kind of almost an AV 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. And EvolutionIQ has shown that they have a higher benefit and a higher ROI, and that's why they win. They have 9 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. So they continue to really have this meaningful ROI. And what they do is they usually sell in at 1 module prove the value of that 1 module and then expand with cross-selling additional modules, and they've seen a lot of success on that.

Perfect. And just to be clear, the disability and workers' comp area, you were not previously in.

That's correct. Exactly. So when we acquired them, that was an opportunity for us to expand the TAM and move into these new markets.

And 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 of customers retaining?

Yes, exactly. So gross dollar retention is 99%, and it's been 99% for the last 2 years. It's -- since we've been public, it's been between 98% and 99%. So it really highlights the stickiness of the platform and that clients stay on the platform. And 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 people moving to either shutting down facilities or acquisitions of facilities. So 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. I want to 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 CCCs claim volumes and also the business model, value proposition? And does the shift toward AVs create new opportunities for you?

Yes. So when you think about macro trends for carriers and our clients in general, there's kind of 3 macro trends. One is frequency, so the amount of accidents that happened. And 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. But the other 2 macro trends, one is the cost of the claim. So how much would it cost to repair the car or if they're 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. And then the third is complexity. And that's really another macro trend that is growing at a really rapid pace. And 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. So 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. And so 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. And 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 that comes from AI-based solutions at 10%. I was hoping you could dig in a little bit. What are the key products how to think about that opportunity?

Yes. So within that, about half of that just under half is EvolutionIQ. So 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 then the newer AI models from the launch of Estimate-STP was like November '21 and bring that current, all of the AI is in that $100 million. And then 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? Where are we as far as adoption? What percentage of claims runs through STP and what's the opportunity?

Yes. So Estimate-STP and for those of you that are newer, what that is, is using computer vision to determine the cost to repair the car. So someone can use their camera to take photos or video of the car. That then turns into 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. So 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 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 very little percentage running through, and they're kind of in the test and looking at how they operationalize it and roll it out. And then 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 so we will continue to see that grow in scale. It will be further clients coming on to 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.

And 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? And then how do you monetize it? And what's the difference once it goes through?

Yes, absolutely. So all of our products are really sold on an ROI basis. So 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 going to see, and then we price the product on a 5:1 ratio. So 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 and appraise that are out in the field. They're driving around in their car. They're making an appointment to go to a drive way 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. So think about you have staff time, you have travel time. So that estimate in that scenario is costing hundreds of dollars. Now you're deploying -- 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. So you're going from one experience to something that takes minutes. And so from a carrier, they can just look at staff levels, they can look at the cost for that estimate. And it's using Estimate-STP is significantly a significant cost improvement. And so that's the value we drive and then we price in a -- in roughly a 5:1 estimate. So if that estimate in the old world cost $100, Estimate-STP cost $20. And so that's a win-win.

You get a much tighter range of outcomes when you do -- when you're using Estimate-STP as well because if you take a couple of adjusters who have 25, 30 years experience and you ask them to write enough to bet on a car, it could be 25%, 30% variance in those 2 estimates. And so with Estimate-STP, you definitely get a narrower variance on that.

Great. Let's zoom out from Estimate-STP 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 is really impacting the financials?

Yes. So our -- it's a cohort of products that we've launched more recently over the past couple of years. It's about 4% of total revenue. It's growing roughly about 70% year-over-year. So really good growth. It has AI products that sit across our APD solution set. So 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 2 carriers and then help them recover liability from one carrier to another, we're digitizing that through our subrogation tool. And then we have products for the repair shops. So we have diagnostics, build sheets are a few of the examples. So 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 going to drive significant growth contribution as we go forward.

Okay. And let's zoom out one more time. So now you have emerging solutions. You talked about or 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? And what about these established solutions if you talk about the growth algorithm?

Yes. So historically, what we've looked at from kind of a growth contribution, it's roughly been 30% coming from new logos. 70% coming from cross-sell, upsell. 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 of them are -- 30,000 are clients. We have over 300 insurance companies. So we continue to grow new logos, but it will be a smaller part of the growth algorithm. And so that will be about 20% of growth and the balance, 80% will come from cross-sell upsell. We talked about emerging and the contribution of that. There are areas in our established product set that are -- have good growth runways in front of us. Casualty is a product and established that we talk a lot about. So if you think about our APD solutions, we have 300 clients on APD. It generates 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. So 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 technologies. So we see good opportunity in the repair facilities and upgrading the packages and parts suppliers, diagnostic suppliers are still very early days of digitizing and see really good opportunity in that part of the business as well. So 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. So 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 where do you go from here?

Yes. So yes, we were really happy with the margin progression in the year. I mean, one data point is year-over-year outside of the acquisition of EvolutionIQ year-over-year head count was flat. We absolutely continue to invest in new innovation, continue to support a very robust road map. At the same time, we do see areas of opportunity for productivity and so we were able to manage the head count 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 bps of margin progression per year. So we're at 42, 100 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. But it's a very efficient cost base. We -- our software is all it's a single instance. And so we feel that it's a really scalable business model. And as revenue scales, we have a lot of operating leverage that drives margin progression. So 45% 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% to 10%. So is that 9% to 12% on a durable basis? Is that the right way to think about growth?

Yes, that is. I mean that's the way we frame our growth. I would say EvolutionIQ has a long runway. We're seeing really good opportunities with them, both from them scaling in the disability and workers' comp market but 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. So in the earnings, Githesh highlighted, we had our first cross-sell win with an 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 and what to do. And so that is something that EvolutionIQ has in market and disability, has in market and workers' comp, and we're not bringing it to auto casualty and we had our first win. So a lot of space for EvolutionIQ to go. And then the core business outside of EvolutionIQ, we've talked about kind of 7% to 10% as a long-term revenue range, and we feel really good about that.

And that's organic.

That is organic, correct.

Just to follow up on the EiQ win and the cross-sell is -- are there further investments needed from a go-to-market? Is that fully set up that everyone is selling the whole portfolio?

Yes. There are ongoing investments, but what it really means more than that is just bringing the Evolution IQ and the product specialists from that team and having them work closely with kind of the CCC team. So the CCC team has these great relationships with these national accounts. Evolution IQ has the specific product specialty and bringing them together and taking the best of both of those teams really gives us what we need to be successful as we scale go to market. So less about investment is more around bringing the teams together and continue to integrate the acquisition.

Got it. And as AI and emerging solutions increases in mix, how does that impact the gross margins of your business?

Yes. From a -- like when we look at the unit economics of AI, either at EvolutionIQ or AI within core CCC, the unit economics are good. And when you look at them versus our historical products, they will have similar gross profit characteristics. And so 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 of years. It was more in the upper 70s, last year was 76%. It's more as we bring these new set of solutions into market. The cost will outpace the revenue until the revenue scale. So 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. And the revenue, it's SaaS, so it's not lumpy. It builds up over time. And so when we're in these subscale launches, it has pressure on gross profit until it gets to scale. And then once it gets to scale, it will have characteristics of our more mature products.

I do 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? But also I want to ask, is there is a piece of your business that's transactional. Is there -- is there a way to sort of remove or lessen the exposure to transactional increase more recurring subscription revenue there?

Yes, absolutely. I mean if you look at where we had been, the mix was more like 80-20. So 80% subscription software, 20% transactional. We continue to shift it towards more subscription through renewals, 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. So where we see transactionals in the smaller carriers. But through renewals, we're moving them to subscription as well. And so we highlighted that when we look at the business now, it's more like 85% subscription and 15% transactional. So we are seeing a move, and I expect it to continue to shift towards subscription over time. So the business will be less exposed to just in-year claim volume as we move that mix more and more to subscription. The first part of your question is what we're seeing on claim volume. So we are seeing ongoing moderation. So in Q4 last year, total claims were down 6%, but a part of that was weather-related events that it lapped in 2024. And so those are hard -- those are kind of one-off items. So when you strip that out and you look at kind of on a normalized basis, claim volume was down about 3%. And that continued to moderate throughout 2025. So 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.

And just to make sure I understand the weather events, is that a light winter?

No. It was more in '24. There was a bunch of hurricane storms that hit the East Coast, and those events drove substantial claim activity. And we didn't have the same activity in Q4 of '25. So it's just the comp that we are running over in '24.

Excellent. In the last few seconds, I just want to touch on capital allocation. If you could hit on your buyback, Brian, and we'll end it there.

Yes, sounds good. Yes. So we announced $500 million in December of last year. Within that $500 million, we did a $300 million ASR. So that was kind of 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. So we feel good. I mean, clearly, the stock, it's a buying opportunity. We believe the stock is undervalued. And we'll continue to look at buybacks because we believe it drives long-term shareholder returns.

Excellent. Thank you, Brian. Thank you, Bill. Thanks. Appreciate it.