Thank you for standing by, and welcome to CCC Intelligence Solutions Fourth Quarter and Fiscal 2022 Earnings Conference Call. [Operator Instructions] I would now like to hand the call over to Vice President, Investor Relations, Bill Warmington. Please go ahead.

Good afternoon, and thank you for joining us today to review CCC's fourth quarter 2020 financial results, which we announced in the press release issued following the close of the market today. Joining me on the call are Githesh Ramamurthy, CCC's Chairman and CEO; and Brian Herb, CCC's CFO. The forward-looking statements we make today about the company's results and plans are subject to risks and uncertainties that may cause the actual results and the implementation of the company's plans to vary materially. These risks are discussed in the earnings releases available on our Investor Relations website and under the heading Risk Factors in our 2022 annual report on Form 10-K filed today with the SEC. Further, these comments and the Q&A that follows are copyrighted today by CCC Intelligent Solutions Holdings, Inc. Any recording or retransmission or reproduction or other use of the same for profit or otherwise without prior consent of CCC is prohibited in a violation of the United States copyright and other laws. Additionally, while we've approved the publishing of a transcript of this call by a third party, we take no responsibility for inaccuracies that may appear in that transcript. Please note the discussion on today's call includes certain non-GAAP financial measures as defined by the SEC. The company believes these non-GAAP financial measures provide useful information to management and investors regarding certain financial and business trends relating to the company's financial condition and the results of operations. A reconciliation of GAAP to non-GAAP measures is available in our earnings release that is available on our Investor Relations website. Thank you. And now I'll turn the call over to Githesh.

Thank you, Bill, and thanks to all of you for joining us today. I'm pleased to report that CCC delivered another quarter of strong top and bottom-line performance to complete another record year in 2022. For the fourth quarter of 2022, CCC's total revenue was $204 million, up 9% year-over-year and ahead of our guidance range. Adjusted EBITDA was $80 million, also ahead of our guidance range. Adjusted EBITDA margin for the fourth quarter was 39%. Revenue for the full year 2022 was $782 million, up 14% year-over-year, 2% above the high end of our initial 2022 guidance range. Adjusted EBITDA for the full year 2022 was $305 million, 4% above the high end of our initial guidance range and more than twice our 2018 adjusted EBITDA of $148 million. For a compounded annual growth rate of 20%, we believe our strong performance reflects both the nondiscretionary nature of the P&C insurance economy we serve, and the durability of our business as we continue to deliver innovation and operational efficiency for our customers. Based on our performance in 2022 and the confidence in our growth trajectory, we are providing revenue and adjusted EBITDA guidance for the first quarter and full year 2023, which Brian will walk through. Today, I'd like to discuss 3 important topics with you: CCC's focus on growth, innovation and our industry-leading AI Platform. Our customers continue to face a difficult operating environment with multiple challenges. Once a challenge is a severe labor shortage of claims adjusters at insurers and repair technicians at collision repair facilities. Another challenge is inflation across labor rates, parts prices, medical cost, new and used vehicle prices as well as supply chain issues affecting the availability of parts. You can add to that increasing complexity of the vehicles themselves that now require…

Thanks, Githesh. As we now turn to the numbers, I'd like to review our fourth quarter and fiscal year 2022 results and then provide guidance for the first quarter and full year 2023. Total revenue for the fourth quarter was $204.1 million, up 9% from the prior year period. Total revenue for the fiscal 2022 was $782 million, up 14% from 2021. Githesh our $1 billion-plus investment in R&D that's been made over the last 10 years. We are seeing returns from that investment in innovation as our newer solutions contribute to our financial performance. Approximately 1/3 of our revenue growth in 2022, for example, came from solutions introduced in the past several years, confirming that our strategy around innovation is taking hold. Approximately 6 points of our revenue growth in Q4 was driven by cross-sell and upsell into our installed client base, including continued adoption of solutions like mobile, Engage and our digital solutions around total loss. An incremental 3 percentage points came from new logos, mostly through repair shops and part suppliers. There was no growth contribution in Q4 from the large expansion deals signed in the second half of 2021 as we have fully lapped that growth impact. Also worth noting is that 99% of our revenue in the fourth quarter was domestic. Now turning to our key metrics. Software gross dollar retention or GDR and captures the amount of revenue retained from our client base compared to the prior year period. In Q4 2022, GDR was 99%. That is consistent with the last quarter and all of 2022. We believe our strong software GDR reflects the value we provide and the significant benefits that accrue to our customers from participating in the broader CCC network. Software GDR is a core tenet to our predictable and resilient…

[Operator Instructions] Our first question comes from the line of Gabriela Borges of Goldman Sachs.

This is Kelly on for Gabriela. Congrats on the quarter. First one for me is just you talked about one of your focus areas within payments as the carrier to repair facility payments. How is progressing from a technical perspective? And how is customer conversations been going?

Thanks for joining. I would say that the conversations are going well. We are continuing to see a fair amount of interest in really getting not only the carrier to repair, there's a lot of complexity there. So people are excited about that. We also expect that our payment solutions will generate revenue, and we are finding broader applications. So it's coming along.

And then just as a follow-up, how has progress been with Subrogation? Is there any difference in how you're approaching the go-to-market with that product? And how has that kind of trended relative to your initial expectations?

Sure. So we've done 3 things on the Subrogation front. First and foremost, we have substantially upgraded some of the technology underpinnings in terms of platform and architecture from the acquisition. So network -- that development work is complete so that we can actually execute at scale. So that's gone really well. The early conversations with customers in terms of pilots, capability, product expansion. Those are going well. The integration is going well. So we feel good about the strategic direction as well as the work to date to integrate Subrogation to be a key part of our offering.

Our next question comes from the line of Dylan Becker of William Blair.

This is [indiscernible] on for Dylan. I know you guys touched on the Estimate-STP, but can you elaborate on that journey and what the typical rollout looks like as you have like a large share of the DWP customers, but there's relatively low overall penetration. So how are you guys thinking of that value realization driving the ramp towards greater wallet share over time?

Yes. So here's how we -- how the solution itself is developing. As you recall, we said -- we delivered the product after many, many years of R&D in November of 2021. And we started working with early customers who wanted to test these capabilities and see how it works. And what we are really seeing is that the ramp follows really 3 particular ways -- 3 particular ways. So first, people test the solution for accuracy, capability, because this is, again, the first of its kind. So before people are willing to make a commitment, that testing can take a fair amount of time. So we're truly excited that today- as of today, 15 of our customers have selected, including, as you pointed out, 7 of the top 10. The second thing people do once they feel very comfortable with the solution is to start rolling it out in limited geographies. So people might start in 1 state or 2 states or 3 states. And then -- and as people get more comfortable, make the adjustments, start rolling it out in about all 50 states. Third, we've been very careful and very thoughtful in terms of which claims qualify for Estimate-STP and the AI. And so the third step is to now to have what -- the percentage of claims that go through Estimate-STP start to gradually increase as this thing applies to more and more qualified claims. So those are really the 3 metrics -- 3 ways in terms of adoption. And it's not really very different from adoption we've seen over many, many years for many other products where people start out and then continue to expand over time and -- but the early design wins, if you would, with customers making decisions on the platform, we view that as very, very fundamental. I hope that answered your question.

No, that was super helpful. And then just a follow-up on kind of switching lanes here. Can you talk about that broader medical opportunity and how the data, the cutline structure and the overall complexity differs from other aspects of your business and what it takes to build out that piece of the claims equation?

Sure. We have been delivering Casualty solutions for, say, almost a decade now. And roughly one in -- call it, roughly 1 in 5 auto claims results in a casualty claim. So there's a fair amount of linkage between an auto -- what happens in an auto claim and what results in a medical or casualty claim. So we have a number of solutions for medical bill review, a number of workflow solutions, a couple of mobile solutions to work directly with consumers, both in first party, first party, which is the claimant of the insurance company, or third party, which is the policyholder of the car on the other side. So we've built a number of solutions over there. And what -- and we've also spent a fair amount of R&D and capability in upgrading these platforms over the last several years, and we are now starting to see the benefit of customers adopting more casualty solutions. One metric to keep in mind is that while we have 300 insurance customers, we only have about 50 Casualty customers as of now. So that's why we view the growth opportunity is significant.

Our next question comes from the line of Michael Funk of Bank of America.

Yes. A couple if I could. So first, for a high level, any change in spending plans or activity from your customers?

Look, we are monitoring the macro environment very, very carefully. And we have not seen a material change. And I would attribute part of that really a handful of things. One, what we deliver is mission critical. And as we talked about, the operational efficiencies to really address inflation, to address labor shortage, to address vehicle complexity, our solutions deal directly with these solutions. And I think the other thing that helps to some degree is that the ROI for these solutions is very tight. We can get -- we can deploy a solution and our customers can see the impact literally in 30, 60 or 90 days. So it does not require a multiyear forklift big upgrade of platform. Third, since we are already integrated deep into people, into our customers platforms and systems, additional functionality is also easier to deploy in terms of training and rolling it out. So I think those things are helping. But I would say the single most important thing is and this is mission critical. And we are monitoring the situation carefully but have not seen any material changes.

And then you mentioned AI earlier in your script, obviously, your massive data set, strong adoption to date, STP, for example. But can you talk more broadly about the opportunity longer term incorporating AI, maybe quantifying the potential market there for you looking forward?

Yes. We have not actually publicly quantified the markets across the board. But one specific thing that Estimate-STP has done is this is actually one of the most complex applications of artificial intelligence because you're taking pictures around the car and understanding the 3-dimensional spatial structure of the vehicle, the damage to the vehicle, what parts are damaged, different color combination, cars, pickup trucks and the like. So it requires an extraordinary level of complexity and many, many layers of neural networks that you've build. And by deploying this solution first and dealing with that complexity, we also feel it's given us a lot of credibility with our customers to be able to go to really what we think is a much bigger and broader application of artificial intelligence. That is straight-through processing. By straight-through processing -- sorry, go ahead.

No, no, no, I'm sorry, I cut you off. Apologies.

Yes. So straight-through processing is a much, much broader application. So straight through processing, the way we think about it applies everything from first, when you report a claim, what should I do with this vehicle to routing, to scheduling, to parts ordering, to repair, to which claims to subrogate, which claims to not subrogate, what do I send to salvage. And then on the repair side, artificial intelligence applies extensively because you may be seeing -- as a repair technician, you might be seeing a car for the first -- this particular car and this particular damage for the first time. But any -- a car might have 20,000-plus parts, might have complex repair procedures, paint techniques, so we think AI applies in those areas, it applies across a very, very broad range. So the heart of it is really 2 things: One, continue to make sure our data set is really good that allows us to rev hundreds of AI models; and second, deploy that in line inside the workflow that we are already in.

Our next question comes from the line of Arvind Ramnani of Piper Sandler.

I just wanted to ask you about some of the investments you are making, I mean you're talking about the roughly 100 bps margin expansion this year and kind of 900 bps of margin expansion over the past several years. With that said, like I just -- I'm just trying to get an understanding of this AI and kind of automation opportunity that lies in front of you. And would it make sense to kind of double the efforts on making investments in that regard?

Yes. Maybe we'll handle it in 2 parts, with me and Brian jumping in. So I'll take kind of the first part of your question, Arvind. So I do think at the heart of it, what we've spent -- done over the last decade is build enormous core AI capability. That means the ability to build models, the ability to rev models, the ability to deploy models. And that -- and actually build a lot of talent right, with people, with doctors and everything from neural nets to AI and machine learning. So we built -- we feel we've built a lot of those capabilities. And what we are doing is being fairly judicious in terms of applying AI to a number of use cases and one of the things, as I mentioned earlier in my call, we have a Net Promoter Score of 82. So if you -- to get to a Net Promoter Score of 82, it means you have to be very judicious about the quality of what you deliver and the speed and rate of adoption. So AI will be deployed across the board because we see this as a secular opportunity of the many, many years but there's a certain rate at which you invest or the money is wasted. So we're being very balanced and very prudent. Brian, if you want to jump in.

Yes. I would just echo Githesh's point. I mean we remain super focused on a balanced approach. So investing in innovation and at the same time driving operational efficiency. And we believe we can do both. I mean, you highlighted the points you made or we made about 900 basis points of improvement over the past several years. At the same time, we referenced putting $1 billion into R&D. We talked about adding 20% of capacity and headcount focused on product development. So we believe we can do both, continue to put a significant investment in the business and really drive the AI capabilities. At the same time, continue to progress margins and move to our long-term targets of margins in the mid-40s.

Perfect. And I mean, I think if you -- that ChatGPT is sort of like kind of rages, everyone's talking about ChatGPT and generative AI, but I guess one of the limitations is that the data that available is only available until 2021. Your data is like a lot more real time, right? Like I talked about inflation and some of the kind of more kind of repair shops and the delay in getting automobile repair and stuff. Your data is a lot more real time. Are you able to kind of talk a little bit about how real time is it? Is it still like 3 months dated? Or is it real time as like every day it gets updated? And any kind of commonalities or differences between that generative AI.

Yes. I'll take your question in really 2 parts. And this is actually one of the most fundamental questions some of our customers are asking. In fact, we had a customer just last week in the office and this was actually one of the key things. And I think your point becomes extraordinarily relevant if you look at one data point, for an example, I'll just pick one. The price of used cars has increased by almost 50% in the last 18 months or so. It goes up, sometimes it goes up significantly and then sometimes it goes down and then goes back up. So used car pricing might literally change on a week-to-week, month-to-month basis. Same thing with parts prices and so on. So one of the benefits we have is that on any given day, the scale of transactional data repairs, estimates, supply chain information flowing through a network is massive. So even if you build an AI model, that currency and the speed at which you can rev this model, we learned how to do that with software releases. We did over 1,000 software releases last year and maintained a network or uptime of 99.95. So we had to do the same thing with AI, and we can literally rev some of the models on a monthly basis. Some of this gets updated. And not only do rev and update these models, there's also an important element of AI called drift that you have to manage. So drift is the difference between what your initial AI model is -- was seeing and what you're seeing in practical and real time and monitoring that drift also governs the frequency with which your models are updated. So all of these capabilities take enormous amount of time, compute power and the ability to scale and deploy especially across a large customer set. So you're absolutely right. That currency we think is critical. And then the second part of your question regarding ChatGPT, ChatGPT today relies on a lot of public data, lot of data that's in the public domain. And it's web data, et cetera. Even if the data goes from -- and we are actually quite excited about the technology, and we'll deploy it in probably some pieces of where it makes sense. But much of the data sets that we're talking about are changing on a very deep and real-time basis that unless you're deep in the middle of these transactions, you don't actually see this data set. Does that help, Arvind, in terms of the questions.

[Audio Gap] Process and consume data in real time. I mean I think that seems to be even more relevant in an environment where prices are moving, like you said, up and down, a little bit more dramatically than in the past.

Yes. Arvind, we lost you for a few seconds. So I didn't know whether you had a question or a comment.

No, no, I was just saying it was helpful because it just makes me realize that your solution is a lot more relevant in this environment where prices are moving up and down. And so it becomes a lot more compelling to use a solution that you can get more real-time data. So I was just -- saying just, thanks.

Our next question comes from the line of David Kelley of Jefferies.

I was hoping you could talk a bit more about the MSO relationship expansion that you announced, I guess, from our end to 400 location additions, seems like a nice add-on for quarters. So curious how impactful those MSO contract expansion tend to be for you, particularly as we step back and think about those customers continue to consolidate the repair facility sector at their level.

Yes, David, it's Brian. Yes, so we certainly -- the MSO relationships are a meaningful part of our business, and we continue to build those out. If you step back and look at our metrics on kind of the new logos. If you go back 5 years, we've been adding about 1,000 new rooftops per year. And certainly, the MSOs and the expansion of those relationships have contributed to that. And we feel really good about where that's going as well as we look forward. The $400 million that we talked about didn't necessarily play much into this year because we signed it at the end of the year and the onboarding will bleed into next year, but it will be part of our new logo growth in the repair facilities into '23. and we feel really good about kind of continuing the cadence of adding 1,000 shops a year.

And by next year, Brian, I think you meant '23.

Yes. I'm sorry, yes, 23.

Okay. Got it. That's super helpful. And then appreciate the color on the Diagnostics ramp within that emerging solutions contribution, you mentioned. I guess should we expect Diagnostics will again be, let's call it, like the leading driver of emerging growth in 2023. We're seeing massive vehicle evolution and clearly, vehicle level demand for Diagnostics. So could you speak to customer appetite to adopt the CCC Diagnostic solution, just kind of what you're hearing from NIM and how quickly they're looking to adopt that sort of solution set?

Yes. So first and foremost, what's been happening over the last several years is that as the vehicle mix changes, any cars that have really come in almost the last decade or so require a scan of some kind to understand what sensors are broken, what sensors need to be redone. So typically, the scans take place before and after. So that has been increasing and there's been a lot of inconsistencies in the market by way of how scans are done. And what we did was to bring a level of order and integration to those capabilities because manufacturers require it, consumer safety requires it. And -- so we've tried to bring a lot of order to that process. And with that said, the amount of diagnostic scans going through our platform is still a relatively low number. I don't know we've -- Brian, we've published the amount of what percentage of repairs are going through diagnostics, but still not a big number. But what we are seeing is that across the board, by integrating the most popular diagnostics providers into CCC ONE, it has provided a level of transparency and a seamless level of integration. So we do think this will continue to grow very nicely over the next several years. But again, we see Diagnostics as one element of a much broader portfolio of solutions that we are bringing out to the marketplace.

Our next question comes from the line of Chris Moore of CJS Securities.

First, the real-time conversation you just had a few minutes ago was -- that was fascinating, very helpful. Just trying to get a little better handle on the evolution of the CCC model. So at this stage, you talked about growth coming roughly 20% from new logo, 80% cross-sell, upsell, historically that have been more like 1/3, 2/3. So is that current level something that will change over time? Or more likely, it's just a mix within the 80% that could change kind of the relatively newer versus more mature products within there.

Yes, Chris, it's Brian. Yes, you have the metrics, right? So those are the metrics that we've put out. The shift from 1/3 new logo to 2/3 cross-sell, upsell of our installed base and moving to a 20% new logo and 80% upsell, cross-sell. That shift is happening, and we saw progress against that in '22, and we'll continue to move in that direction. We've given further color as you break down the 80% of cross-sell, upsell to the base and we've said over time, about half of that will come from existing solutions that have been in the market for the past several years and half of the growth will come from these newer emerging solutions that we've more recently brought into market such as Diagnostics, such as Estimate-STP and Subrogation. So we do think we'll have a meaningful impact from these newer set of solutions, but that will build out over time.

Got it. Helpful. And maybe my follow-up. Brian, you may have touched on this, but I came on a little bit late. You went through this -- the kind of the free cash flow dynamics for '22, did you talk at all in terms of expectations for '23.

No, I didn't specifically guide to '23. I talked about that if you look at our cash conversion on an adjusted EBITDA basis, we're converting about 59% of adjusted EBITDA into unlevered free cash flow in '22. There were 3 adjustments to it. And if you normalize it out, it gets to the mid-60s, which is consistent with our historical performance. That is a good benchmark as you think about modeling going forward using low to mid-60s as a cash conversion metric.

Our next question comes from the line of Saket Kalia of Barclays.

Okay. Great. Jumping between a couple of calls. So apologies if these questions were asked. But Githesh, maybe for you. It was great to see the commentary on Casualty. I was wondering if you could just remind us who is CCC usually displacing in a Casualty type of sale. And you mentioned, I think it was 50 insurance customers that are using Casualty, right? And of course, they're using the auto physical damage piece of the portfolio as well. When you cross-sell Casualty to that type of customer, what sort of a general kind of increase in run rate that you can see with that type of cross-sell? Does all that make sense?

Yes. Sure. Saket, I'll have Brian take the second part of your question, and I'll take the first part of your question. First part of your question is that when some of our Casualty solutions or solutions that don't exist, for example, our mobile capability, and I think we had a press release on this thing with the client where our mobile capability that allows you to engage directly with the consumer and handle many of these things, those are like new-to-the-industry type capabilities. Certain capabilities, we might be -- there are multiple providers of different casualty solutions. So we might go up against different players. And again, we don't generally go into the specifics of the who and what and where, but there are multiple providers and our real differentiation is the analytic capabilities, the integration into a single platform, those are the capabilities we bring. In terms of dollars and impact and the addition it does, I think, Brian, if you want to pick that up and comment.

Yes, sure. So Saket, just from a sizing perspective, clearly, it will really be dependent on the size of the carrier and kind of what solutions they take on in Casualty. But just at a really macro level, today, our insurance APD clients are about 40% of revenue. Our Casualty clients about 10% of our total revenue. Those can be the same size in magnitude. So as you think about the opportunity that Casualty provides is really for them to move up and look like more of the size of our APD client base. And so there's 30% of revenue opportunity as those balance out over time. And that's probably the best way to think about the overall opportunity in sizing for Casualty.

Yes. Got it. That's really helpful. Brian, maybe for you. I think you touched on this earlier with just the 80%, 20% kind of thought on growth from existing versus new. But maybe I'll just ask the question a little differently. As you look to 2023, anything to note just on net dollar retention expectations? And yes, I mean, I'll keep it open ended there.

Yes. I mean, again, I think we're seeing this progress. And I'd go back to the -- historically, it's been more like 2/3. And over time, it's going to look more like 80% of total revenue. If you look at '22 results, we are more like 25%, 75%, 75% from cross-sell, upsell. So again, it's showing that progression, and that will continue as we go into '23. So you can look at those ratios and then can look at it relative to the guide of 8% to 9% for the full year. And if you use those metrics, that will give you kind of a rough way to frame out the NDR impact into '23.

Thank you. At this time, I'd like to turn the call back over to Githesh Ramamurthy for closing remarks. Sir?

Thank you all for joining us today, and I would like to thank our customers, our CCC team members and our shareholders for a great 2022. We are excited about what we have planned for 2023. The durability of our business model continues to come through, and we remain confident in our ability to deliver on our strategic and financial objectives while helping our customers and investing in future solutions. On behalf of all my colleagues at CCC, we look forward to talking to you again in early May when we do our first quarter, if not sooner. Thank you so much for your continued interest and your trust in CCC.

This concludes today's conference call. Thank you for participating. You may now disconnect.