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

Thank you so much for joining us Day 3 of the Goldman Sachs Technology Communacopia Conference. Delighted to have the CCC team up on stage with us. My colleague, Callie on the right. Githesh and Brian, thank you so much for your time today.

Likewise, thanks for having us.

Githesh, we've had some iconic type company present. And what I find iconic about CCC is we've already delivered through 40-plus years of technology evolution and technology transition. So I would love your perspective to start. I would love your perspective to start, how do you think about this car technology transition and the insurance industry relative to prior transitions that we've seen with cloud or multi-tenancy and there's been so much that the company has spent time on. Maybe just give us your observations and someone, who's been in this industry for a very long time.

Sure. So one of the things that we're very proud of is through this whole cycle, we have essentially reinvented this company multiple times over this time frame. So the durability, if you think about our business model has really been that the end markets have been very stable, right? Auto insurance for a long time, number of cars on the road, that continues. So that's been there. And at the core of it has really been an extraordinarily deep understanding of not where our customers are today, but where our customers need to be 1 year out, 2 years out, 3 years out because as you know, our customers are making 5-year commitments with us, right? So that means a deep understanding that we'll keep them at the forefront 1, 2, 3, 4, 5 years out. So that means -- and then we've also -- then what we also have done is keep a very deep foothold on the technology side. So exactly as you pointed out, each wave of technology, right, going to client server, moving to object-oriented computing 30 years ago, going to mobile, going to cloud and our cloud platform, we went there 25 years ago, right? And then on AI, our investments and starting to buy NVIDIA hardware in 10, 11 years ago. In fact, we went to production. I said there's a Wall Street Journal article in November of 2021, right, production. So we see this wave of AI-driven innovation as actually larger and more impactful than any other wave that we have seen.

Yes, yes, that makes sense. And so maybe stay with us on some of the AI innovations that you're driving internally. 12 months is a long time in AI world. Maybe share with us 1 or 2 most exciting technical achievements over the last 12 months tied to your AI road map.

Sure. So I think interestingly enough, we've done 2 things that we have achieved on that, right? One is really an extraordinary level of depth around what we call visual AI. Visual AI, this is slightly different from generative AI. We use generative AI models from everybody, right? We have 10 different models. We have hundreds of models we've built on top of this. So we think the deep generative AI models, everyone, is going to have access to. And then on the visual AI, what has been extraordinarily difficult and that it's taken us many years too, is to understand from a photo, a 2-dimensional photo, the 3-dimensional complexity of a vehicle because every damage is unique. Unlike a production car coming out of an assembly line, each damage is unique. You have to understand all the 3-dimensional structures of the vehicle, the cost, the labor, all of that and getting a level of accuracy on that capability and most importantly, seeing our largest customers trust us with that accuracy after several years. That's why in Q2, we're really excited about customers now starting to roll this out.

So it's interesting that you mentioned visual AI because one of the hypotheses we've been debating is, is the barrier to entry actually higher for visual AI and for some of these AI technologies that span the physical world and the digital world relative to generative AI. And so I guess the question for you is, do you think we've already had a ChatGPT type moment in the applied AI or the visual AI space? Or is the question not even really relevant for visual AI?

Yes. I think it is. What we are doing is very unique in the space. And I think we have crossed that moment where customers now consider this a working valid technology. That's why we have 40 customers. That's why we started with Estimate-STP, and that has led to a whole series of other solutions. How do you handle the first part of the claim? How do you handle the reinspections? How do you do other aspects of it. It has given us enormous credibility because of that early lead that we have. So I'm not sure I call it a ChatGPT moment, but the adoption by our largest customers is also sending a signal to everybody in the marketplace that, hey, this is mainstream, it's real, it's working. And that's taken, as you know, a little bit of time, but we're very excited about where we are today.

Yes, absolutely. And I think this next question is for both of you because, Brian, you have an operator's perspective as well. There is a debate in the market right now on competition. And it's specifically around do the barriers to entry in the software go down because it gets easier to code and because of how transformational some of these technical technology milestones have been. We spent a lot of time in the private company ecosystem, and we're surprised by how many start-ups we meet that say we're targeting insurance. Here's our insurance case study. Here's how we're doing exciting things in insurance. So my question for you is, how is competition changing? And how do you think about the barrier to entry for a vertical-specific domain solution relative to, we've had a lot of horizontal application companies present here as well.

Maybe you can start and then I can add.

Yes. Maybe let me start off, right? So we've always operated in a competitive environment. Also, remember, many of our largest customers, car companies, insurance companies, some of the largest multi-store operators, some of our customers have 10,000, 20,000 people in IT. And they are the customers for many of the most sophisticated technology providers, yet they have relied on us to deliver this technology. So we've always operated in a competitive environment with competitors. So that's just going to be par for the course. I think what really differentiates our solutions are really 3 very fundamental things from a competitive standpoint. So first and foremost, we have an extraordinarily deep understanding of the unique workflows that are very specific to this industry. And that doesn't rely on just the insurance company or the repair facility or the parts provider or the rental or the tower or the car company, but it's a network of workflows that goes across all of these different entities. That means your AI has to work and orchestrate. That's what we call the IX Cloud across all of these different things, right? So that is -- that network effect is an extraordinarily important piece of competitive advantage. The other thing, I would say the second thing is that the depth of what we have in terms of the data set we have is massive, $2 trillion of historical data, 500 million, 600 million photos. And most importantly, we're seeing about $1 billion a day of claims in the United States flowing through. That means drift in our models, accuracy of the models, that volume and the accuracy is extremely good. And third, I would say the tech stack that we have developed integrates traditional workflows and SaaS with a seamless integration of AI and revving that AI. So I think those are how we think of our competitive differentiators. Maybe, Brian, do you want to add?

Well, no, you hit it well. I would just -- the only incremental point I would make is what we're doing today with AI is putting AI on top of our core software that's already in place. And so it's really an extension of what we do for insurance for estimating, what we do for them with workflow. And then we put AI on top of those existing core software. And so they really work seamlessly with our existing software to make recommendations to the carrier to make them more operational efficient. So that is a real extension of what we're doing with our core software that we've had in the market, but the AI on top really is integrated deeply into our existing core software. So that also makes it from a competitive perspective, is very differentiated.

So maybe then just to drive this home, help us reconcile when we talk to companies like Palantir or even when we talk to start-ups like Ryder and they say that they're doing insurance use cases, where does that fit in the stack relative to you? Do you see them in the ecosystem? Or is it adjacent? Is it completely separate? How do we reconcile different insurance use cases with your competitive differentiation?

Sure. There are many, many parts that we are not touching, right? For example, customer service for our customers. That's a huge area. I mean our customers are handling thousands of inquiries, phone calls and the like. And yes, we do participate in some ways in that, but the technologies to really mine the data, use the data, generative AI. So across their core systems, there's so many other facets where we have been very focused is where we can have a very unique impact on the outcome and the performance of our customers as opposed to what I call a much more of a horizontal play. So our -- the vertical nature of what we have and the connections to repair and all of these things is really where we continue to be.

Yes. And beyond just the vertical, like we're specifically in a carrier helping them facilitate an auto claim, and right? So our software and our AI is really focused on that process within a carrier. As Githesh said, their carrier has many other different areas and departments, but that's where predominantly today, our revenue is generated from its solutions that are facilitating the process of an auto claim through the ecosystem.

Yes. So this leads nicely into a question about budget prioritization of the customers. Because I know over the past 12 months, 18 months, there have been quarters where emerging solutions, there has been ebbs and flows to the pace of adoption. So my question for you is, is it possible that customers look at the CCC broader portfolio and say, look, this is going to be a pretty heavy lift for us. Let's wait until we feel better about our own IT infrastructure. In the meanwhile, we'll do all of these POCs with some of the horizontal tools, some of these other tools, which may be easier to deploy. In other words, are you seeing a little bit of a crowding out because customers are more focused on new shiny objects that are easier and they don't want to do the heavy lifting on you? Or how do you think about that relative budget priorities?

So first and foremost, we are not seeing any impact of this because our customers have had access to all these tools for a long time because, as we've said, many of them. And in fact, what customers are increasingly realizing that if this is an integrated deep into the existing workflow. When I'm moving a car, should I repair this car? Should I total this car? So when I'm dealing with my consumer, how does the consumer send the pictures up? How do I schedule an appointment for the consumer into the repair facility. So these are all things that our customers are now starting to understand. That's why we're -- and we have had no issues with our customers piloting, testing. And then as we said in the second quarter, this is starting to roll out. We rarely hear, well, we have other AI we're doing. So we are not willing to look at subrogation or reinspect many of these.

Yes. I would also just add, I mean, our products and solutions are fundamentally ROI-driven. So when they look at our solutions, we're talking to them about a 5:1 ROI. So deploy the software, the AI and you'll see operational savings 5:1. And so that really drives engagement because they're all focused on how do they improve their operations and drive efficiency. And so that ROI mindset and mentality in how we sell is also make sure that it stays kind of top of mind through budget allocations.

That ROI is incremental.

Yes, absolutely. It sounds like is it fair to say there's been a shift in momentum over the last 12 months where you're now at the point where the consistency of emerging solutions is sort of coming together?

Yes. I mean we're starting to -- it's picking up, and we're feeling good on the overall momentum. So in the first half of this year, it's been about just under 2 points of contribution of growth. So we saw that. And last year, we were 1 point of contribution of growth. And so it's scaling in absolute dollars. It's growing the fastest part of the portfolio. Some of the wins we talked about in Q2 give us confidence that, that will continue to scale and move up. So we talk emerging solutions being about half of our cross-sell and upsell over time. And it's SaaS revenue, so it's going to build and it's going to sustain. And we feel good on the momentum and the trajectory that we're headed. So yes, overall, we're feeling good.

I wanted to ask a little bit on the change management and rollout of particularly emerging solutions, I think Estimate-STP comes up a lot with this. Given how crucial the workflows are that like an Estimate-STP is trying to solve for your customers, how do you manage rolling that out across kind of what is a very sensitive area?

I think we've learned a lot, first and foremost, in the last 18 months. One of the most fundamental piece of learning that we've had is the trust that you have to build for AI solutions is different from traditional what I call deterministic software, right, where I do X, I put in inputs of X, I get output of Y. So that level of trust and change management has been very important. So we've really spent a lot of time in gaining people's trust and how that works, both in terms of our UIs and how this is integrated into the piece. The other thing we have also seen is a learning with our own customers. They're saying, rather than just make the changes in place, I can complete -- I can reshift my operation. I can think about this differently. I used to have 7 different centers. Now, I can do this because of this capability. I could have a single center with a level of expertise that is more efficient and also delivers a very differentiated experience for my policyholder, right? We're seeing that with repair facilities. Our multi-store operators. For example, we have one multi-store operator that uses a jump-start for literally 95% of their estimates. I mean the consumer comes in, they're doing $1 billion-plus of repair. First thing there is take the pictures, the AI writes in seconds, 80%, 90% and then their people are using. So I was at dinner, as dinner with one of them, they said, why wouldn't I use this tool for all my people. Now that's at one end. Overall, jumpstart even at our repair facility is still in the single digits. It's increasing. But these are the early signs that we're seeing is our people changing the process to handle complexity to get efficiencies.

Yes. Maybe just a data point. So today, Estimate-STP, about 4% of our claim volumes is running through that channel. But we had a top 10 carrier that's committed to put 20% of their volume through that channel. So they're showing the signs that they're operationalizing these tools and solutions that give us confidence that others will follow because it works, and they're seeing the benefit operationally as they scale these solutions.

Makes sense. And then I think the IX Cloud framework was something you guys came out with to kind of contribute to this vision of just increasing automation across the entire platform. So can you speak a bit to how that architecture has allowed you to deliver on some of these?

Sure. So the IX Cloud platform, think about it as a layer of fabric, if you would, that provides connectivity of workflows across customers and industry. So it connects consumers, it connects insurance companies, it connects collision repair, it connects parts providers, it connects all of these. So underneath this is really an event management model that allows the AI to say, "Hey, based on this condition, I need to flag this vehicle." I'll give you an example. There might be a vehicle in the repair facility. That vehicle should not be repaired. It's a total loss. It is causing a lot of dysfunction for the repair facility, a lot of angst for the consumer and for the insurer by spotting it very quickly and saying this car should be moved immediately within 3 hours because it's a total loss, it should not be repaired. That's an example of IX Cloud connecting different segments and using AI in the workflows to be able to make these decisions and make these movements. So that will continue to extend across casualty, across all of these different capabilities. So we're pretty excited about it.

And speaking of casualty, can you talk a bit about the Evolution IQ acquisition, what that's given you in casualty? And then I would also love to walk through kind of what that means for the growth algorithm going forward and just kind of how you're excited about continuing to roll that across your customer base?

So Evolution IQ was a very unique acquisition for us. We have a fantastic team, where Evolution IQ, what we -- is highly differentiated, starting out with disability, right? 7 out of the top 15 disability carriers. And I've personally gone out of the team to visit some of these carriers and the ROI is huge. It has had a big impact. And as the team has evolved, the next thing we've done with Evolution IQ is a solution called MedHub. So a lot of the medical -- the ability to synthesize medical information, we've taken that and created medical synthesis capability, that's, we call it MedHub, and it's connected to our casualty operation. So we are now integrating those capabilities into our casualty solution as well. So if you think about a claim adjuster who might have 250 medical claims on a particular day and each claim might have hundreds of pages, so to go deep and extract the pieces. So that's been super helpful. So that's the second piece. Third piece around EIQ is really workers' compensation. Many of our customers, CCC traditional customers, 7 out of the top 10 have been CCC customers for a long time, and they're excited to now work with VIQ or workers' comp, which is a huge area, again, relying on the underlying core principles of how do medical claims actually work.

And to answer the question on the financial impact, when we get into next year, we've talked about Evolution IQ adding about 2 points of incremental growth to our long-term revenue target. So we expect them to continue to contribute to the growth for a long period of time.

Makes sense. And then you guys have so many products in your portfolio, especially even just within the emerging solutions. So are there any kind of other products that you'd highlight? I know like subrogation, diagnostics and some of these other things that you've just been really impressed with over the past couple of months?

I would say bill sheets, I think we've talked about this. This is a product where it has become so intuitively obvious and the impact is so large. There's almost 0 change management. It just eliminates a lot of problems. So that's one that's really taken off very nicely. Diagnostics, we're continuing to add providers. We're also starting to offer back-office solutions for the repairs. And then we'll continue to pick up more activity with even our OEM customers, car companies. So there's just a ton of different things, but the key is a single overall focus on making sure that we are having an impact across the ecosystem.

And then, you talked a lot about claims volumes over the past couple of quarters, not to spend too much time on it, but what are you seeing currently with claims volumes? And on the growth algorithm, I know you're not that exposed to, but can you talk through a bit of the moving pieces of how you are exposed to claim volumes and how that makes you view the growth algorithm going into next year as well?

Yes, absolutely. So our business is 80% subscription. So it does not have -- that part of the business does not have an impact or exposure on claim volumes. 20% is transactional, which does have exposure -- or some exposure to it. The 20% is really focused on our casualty solution, which has historically been a transactional business. It also has some of the smaller carriers will pay transactionally. And then a percent of our parts business is on GMV, and that is transactional as well. That said, when we look at the claim volume, we saw 9% down year-over-year in claim volumes in Q1. It somewhat moderated to 8% down in Q2. That is driving about 1 point of a drag in our growth rate. But if you did the math and said, okay, 8% or 9% down on 20% of the business, it should be more like 2 points. But it's really highlighting that where we're seeing the claim challenge is more on the low-end claim because it is not -- we don't believe it's a frequency and accident frequency point. We believe it's a customer behavior point where consumers are filing fewer claims. But when we talk about the higher-end claims on total losses or the higher-end claims on casualty, they're not seeing the same impact. And if you look at ISS data in Q1 of this year, casualty claims has actually grown. And so our largest portion that's transactional is casualty, and that is not seeing the same pressure of -- as the rest of APD. That's why it's not perfectly correlated. We are assuming in the guide that we'll continue to see about 1 point of drag for the balance of the year, and that's what we baked into the position. We'll continue to monitor it as we go through the second half of the year and talk about how that will play into next year.

And we have a lot of conversations with investors on how to think about claims volumes kind of longer term from a cyclical and a structural standpoint. It sounds like what's happening now is a little bit more cyclical, but I think investors do have concerns that there are, in the future, going to be structural pressure on claims volumes. Can you talk a little bit about the autonomous vehicle landscape and kind of how that makes you think about claims volumes?

Yes. I would say, look, having watched this over about 30 years, right, with every new piece of technology, whether it's front-end braking, whether it's automatic braking, it's -- we've seen across the Board. We think there will be a small gradual decline in claim frequency. As Brian pointed out, today, it's more of a claims not being filed issue, right? It's not an underlying. Our belief it's not an underlying frequency issue. And over time, we do think there will be back to reversion to the mean, small changes will continue. And as you know, there's about 250 million vehicles, the car park turning over, that's literally years and years away. But what we are also seeing on the flip side is the amount -- the number of areas where we can have an impact with our solutions should far surpass any impact on claim frequency, right? Because solutions in casualty and workers' compensation, in disability, in parts ordering, there's so many, many areas that we feel very good about our next 3- to 5-year growth strategy.

That makes sense. And then if we look kind of past 3 to 5 years, there's a couple of different things we can talk about like international growth, payments maybe being a growth driver, expanding into other types of insurance. Can you talk a little bit about how you view those kind of longer-term things and where you think that you would have differentiation in kind of each of those categories?

Sure. We are actually just updating our 3-year plans, and we just finished a little bit of work in that area. So we think at the bottom line, we feel very, very good about the next 3 years to 4 years' worth of growth. And with Tim Welch coming on board, a lot of the thinking -- a lot of the work he's doing in terms of the markets, getting ready to really help our customers really execute. So we feel very good about that. We're also very confident with the tech stack we have, the deep understanding of our customers, which has always been the case. Look, I come from a time when we were $20 million in revenue, then we grew to $100 million. We grew $200 million, $500 million, past $1 billion, that ability to regenerate and understand customer problems and keep solving more, that will just be the nature of the beast and except our growth numbers need to get larger and larger each year, so we're scaling up the management team, scaling up the organization to anticipate these changes. So we think international, fraud, there's so many other adjacencies that are very natural for us.

That makes sense. And then as you're kind of doing some of that initial planning going into next year, any kind of like 1 or 2 things you're thinking about from like the R&D organization, the go-to-market organization that you're excited about?

Sure. There are really 2 things that when you look at our R&D capabilities that are super exciting, right? One is we've started to apply artificial intelligence in a substantial way to writing software, building software. What used to take us 2, 3 weeks to build prototypes with Figma and the like, we're not doing that in 2 hours to 3 hours. So the feedback loops that we're seeing to be able to generate and show functional prototypes, so that's being applied across the Board, and we're really excited about the changes there. And then at the same time, the changes we're making in go-to-market in terms of how we approach our customers and that's also being received very early as we think about the next 5 years, that's also being received very well. And Tim, is, of course, deep in the middle of all of that.

Yes. You talked about some of that like AI-driven like leverage and productivity benefit. Does that change the way you think about structural margins longer term? Or how you kind of think like investors will view the long-term structural margins in vertical software in general? Yes. And maybe just to drive this point home, you said 2 things there. You said scaling, but then you also said AI efficiencies. So net that out for us on what it means from a margin scalability standpoint.

Yes. I mean we've talked about in our long-term guide, talks about 100 bps of margin progression per year and moving towards kind of our midterm targets, getting our margins to about mid-40s, 45%. We feel really confident that we can do that based on just the efficiency of the model that we have, but also these operational efficiency areas. So yes, it gives us a lot of conviction on this 100 bps, allowing us to continue to invest in new areas and build out the portfolio at the same time, see margins progress. And there's no ceiling that sits on top of the mid-40s. We certainly could see pathways beyond that, but it's just a target that we put out there for investors to understand kind of capabilities or the way we'll run over the next several years.

And many of our operational teams are working with the latest tools in each of these areas. And to tell you to your point, they're pretty excited about it.

Yes. I guess last one for me. We always go to your conference in May. A couple of months out from the next one, but kind of anything you're already kind of getting excited about to spend time with customers at that conference?

I think what we are -- at a very macro level, what we're excited about as you think about the conference and where we're coming up is really the ability to really help our customers really deliver a very differentiated experience, which is efficient, effective, but by connecting all the different parts of the ecosystem, which we think we can uniquely do.

Gabriela, anything?

Yes. Githesh, I love that you brought up deterministic versus nondeterministic. So help us understand how do you think deterministic workflows fit with nondeterministic workflows? And the balance here is you want the AI to be semi-autonomous such that it's giving value, but you also need customers to be comfortable that the guardrails are in place. So I would love to hear you talk about how you're balancing that?

Where that really comes to light, Gabriela, the singular point is the UI. So what we're seeing is the UI evolve to where -- and we're seeing that with Evolution IQ, for example, where the UI itself for an AI-driven solution is very different. So because it's probabilistic, it asks a different set of questions. It doesn't force you through the same workflow. So based on what the decisions are and based on what the decisions or not, it guides the user. This is why we call it guidance. Our next big evolution is AI-driven guidance. So guidance means we're not going to ask you to do these 17 steps. Based on the conditions and how this shifts, we may say on this particular claim, on this particular day, for this particular vehicle, hey, think about these 4 actions and your consumer has this, this, and this requirement, think about these actions differently for the consumer. You couldn't do that before. You had to have the same workflow because you've got 25,000 people in your claims organization, and that is what we're really excited about, and that's where design of the UI/UX is really where we think this is going to come together.

Fantastic. Githesh, Brian, thank you so much for joining us. Please join us in thanking the CCC team for their time.

Thank you, Gabriela. Thank you, Callie. Thanks a lot. We really appreciate being at your conference.

Yes, this was a lot of fun. We had some really interesting topics.

Thank you.

Thank you. I appreciate it.