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

Hello, everyone, and welcome. Today, I'm delighted to have with us CCCS; and CEO of the company, Githesh; and Brian, CFO of the business. Githesh, Brian, thank you very much for coming. Glad to have you with us.

And as a starting point, could you discuss in some detail the amazing business that you're running, which I feel is somewhat less sensitive to a lot of the macro trends and headwinds that some of the other SaaS companies are experiencing.

Thank you, Alexei. Good morning, everybody. So when I look at CCC and the way we've operated for several decades, it's actually a very stable underlying macro environment in which we operate. By the way, a quick show of hands, how many of you drive a car, how many of you have auto insurance, all right, similar number, all right. So if you look at it, auto insurance is mandatory and it's a very fundamental part of really what gives the stability to this industry and our business. So the number of cars on the road has steadily increased over the last 2 decades. It continues to increase. Half GDP growth comes from population growth, so a number of car keeps increasing. So the underlying macro environment of auto insurance is what provides stability. That means our customers can also plan for the long range. And what we've also seen is through various economic cycles, whether it's 2008, whether it is 2000, we've seen a very steady underlying basis for auto claims and auto insurance. That's what's given us that stable base. And then, of course, we've been able to drive a tremendous amount of innovation on top of it, and that innovation is really what's driven the growth for our company.

And I was very lucky to be at one of your recent events in Arizona. And one of the things that I took away was the announcement or soft launch of the ISTP. Could you discuss in a bit more detail what is it? And how is it different versus what your customers are using today?

Sure. So when we talk about the I in ISTP, it stands for intelligent and the STP stands for straight-through processing. So if you look at 2 macro things, vehicle complexity and process complexity that massive both are increasing pretty rapidly. So intelligent STP or straight-through processing is the ability to streamline, digitize and automate a lot of these capabilities. So over the last decade of developing our artificial intelligence, the reason we call it ISTP instead of STP is that the ability to apply artificial intelligence through our tech stack at every facet of this capability, we think allows our customers to deliver a very unique experience for that particular policyholder on that particular day, on that particular damage, in that particular geography. That is what intelligent STP does. And our customers are all seeing shortage of people. They don't have enough people. They need more capabilities, and it is really getting a lot of excitement from customers.

One other element that I thought was quite fascinating is the level of trust that they felt you were able to establish between a lot of the parties that are involved in this very complicated process of this auto economy, as you call it. So could you discuss in a bit more what it gives you in terms of perhaps your NPS scores or your customer relations and how you've been able to build that?

Sure. Because it's over $250 billion are spent in auto insurance in what is spent on auto claims and the many different parties. And many of these parties are often can be antagonistic or have different priorities and maybe that's a better way of saying it. So you have insurance companies, repair facilities, parts providers, banks, car companies, so many different participants involved. So over the last couple of decades, what we really have felt is building a very deep network of participants where the CCC information becomes the standard of communication or the transparent way. So for example, if you look at an estimate, the average repair estimate is $4,600. Auto insurance -- car insurance companies ultimately pay for the repair, repair facilities repair the vehicle, car companies, parts providers, so many other people are involved. So it has to be a trusted company and a trusted data set that all parties can agree. So that has allowed over the last couple of decades as more insurance companies, more repairers, more parts providers, the network has grown and along with that, the network of trust, the trusted network has grown. So as you know, that's to the square function when you have kind of that exponential growth. So that's been very important to make the process more efficient.

And that phenomenal NPS, like frankly, I haven't seen that high level of NPS across many of my companies that we cover, what helps you achieve that? I mean what's the secret source behind it?

So if you're -- I think you're referring to our NPS of 82, right, because the average software company has an NPS of 14. So 14 to 82 is a big leap. And we had always felt that we wanted customers to use our products because they love the product, not because they needed to use the product. And now it does both. What is really -- there's about 6 or 7 things that go into the NPS function. First, the platform itself. It's got to be super easy to use. So we spent enormous amount of time on the user experience, the tech stack, the delivery. We delivered 99.9-plus percent uptime. We delivered 1,500-plus software leases last year. That means the pace of innovation that you're constantly delivering for customers that they're getting value for the money, the impact in terms of efficiency. And at the end of the day, it's -- the references mean an awful lot. When one customer tells another customer, this CCC's products are fantastic and has huge impact on me. That has a far better impact than any marketing or any other material we could put out. So for us, NPS has been true north in that sense.

And I think that it would be fair to say that CCC has been investing into something that now is on everyone's mind AI for a very long time, more than 7 years now. And I was wondering if you could remind us all of your AI-enabled products at this juncture as well as what are the benefits that AI could bring to your customers?

Sure. So underneath, it's been about a decade worth of work that we put in from building the very, very early AI models. And then we started deploying Estimate-STP, our first really complex piece of AI where you can go to a car after an accident, take pictures, go click, click, click, and then the car -- the AI understands the 3-dimensional complexity of the vehicle, the part structure, damage, et cetera. So that was -- that's actually been a game changer, right? So since we delivered that in November of '21, I think the vast majority, over 50% of the industry has adopted this solution, including 7 of the top 10 carriers. So we have also been deploying AI capability because we've been building AI capabilities for almost a decade. So Estimate-STP is deployed in subrogation, it's deployed for repair facilities. We've also been using large language models. We will send 80 million text messages between repairs and consumers to keep them updated as to what's happening during the repair process. So we also use contextual AI and have been using it for some period of time, but we see AI turbocharging our tech stack in line with existing workflows. So that's -- we think that's a huge differentiator is to be able to deliver AI inside the existing workflows.

And could you talk about some of the current penetration levels that you're seeing of that straight-through processing within your total volume claims?

Sure. Brian, do you want to take that?

Yes. So as Githesh said, out of the top 10 carriers, we have 7 that are using Estimate-STP. There are different stages. Some are at full rollout while others are at the early pilot stage. But as Githesh highlighted, if you just look at the volume that those carriers represent, it's over 50% of the market. We're still really early. So we highlighted that we're about 1% of claims are actually running through Estimate-STP. But we certainly see the clients progressing through adoption and the ramp-up. And when we think about the sizing, if you look at how we frame it over the long term or medium term, there's about 20 million -- there's over 20 million claims, 80% are repairable. We think about looking at the repairable side, about 30%. We use mobile as a proxy. Today, we have about 30% of claims running through our mobile capability. If we get to 30% using Estimate-STP, that represents similar to our mobile channel. And the price point that we've been talking about is for a no-touch claim is about $20. So if you run through the math and say, okay, 50 million repairable and 30% times $20 as a price point, that's over -- that's around $100 million opportunity that we see. We certainly are seeing the progress as we start to ramp.

Perfect. And obviously, everyone is concerned about potential disruption that AI could bring to some of the businesses. But I feel like something that people don't realize is within P&C insurance, all that crash data, it's sitting behind various firewalls, right? So it's not readily available, while simultaneously, you guys have $1 trillion worth of data available to you. So clearly, that's a competitive advantage.

Yes. Part of the reason for that is that there's a lot of sensitive proprietary information in repair, in estimates and vehicle information. And some of it is data we produce, some of it is from partners but because of the complexity and the privacy issues, that's where the trust part that you're talking about comes in, in a huge sort of way being trusted by all sides, to be trusted with this information has been super important. We have about $1 trillion of historical data that's also allowing -- and we collect well over 500 million photos a year. So that allows us to continuously update and tune and keep the AI very, very accurate. So that's a huge part. That data set, not only is that a big data set, but the data set is changing every single day, every single minute. Like if you look at what we'll process in 1 day, that's a massive amount that we process in just 1 day. So you have to keep updating and changing the model as well.

Right, right. That sort of kind of takes me to the question of some of these competitive models, I don't think that many of them anticipate certain drifts that are happening constantly with these models. So what is it in your model that makes your business stand out? And how is it different?

So almost every trust is, as we talked about, an extraordinarily important part of what we do. So when we produce our AI and we produce our solutions, we also predict what is -- how do we feel about the accuracy of the prediction we're making. So we will actually upfront say we have very high confidence. We have very low confidence. So we actually mathematically calculate the confidence levels for every single thing we do. So with intelligent STP and routing, the routing can be adjusted based on the confidence level of the AI. So that has also helped build a lot of trust over time because our big concern was people find it pretty exciting when they first tried this out. They say this is something that required so much human ability to be able to do, how is an AI even able to do this, right? So people went from, I don't think this is even possible to this is amazing. And we didn't want people to actually over-index on that because we see a long ramp, a very nice ramp over this. So the other thing we've done is that the data we collect every single day drift -- the drift that you're talking about, drift is really the delta between what is accurate and how the data is changing. So because of the fact that we're in these flows every single day, we're actually monitoring, adjusting and can deploy the models very, very quickly through our infrastructure. That keeps the accuracy really intact.

And how do -- how are you able to apply some of that AI technology into your clients' workflows?

Because we're already connected into people's workflows. So take mobile. So our systems over the last 20-plus years, we have very deep integrations between us and our insurance customers. On the repair side, we have 28,000 plus repair facilities. And we are the platform in which they operate every day. Our largest repair customers has 35,000 employees. Our smallest repair facility has 3 employees. And our platform scales up and down through the whole thing. And every single person has work use and the like. So because we're already integrated deep into the existing workflows on every facet of it, parts providers and the others, inserting and delivering the AI in line with the existing workflows makes it super easy.

Understood. Perfect. And if I could maybe change gears slightly and talk about some of your new opportunities. I mean it's clear to us that you've established quite a dominant position in auto physical damage. But could you discuss your current exposure in casualty? And what makes you think that you can replicate the success that you've had in auto claims?

Maybe we'll do this in 2 parts, and maybe, Brian, you can take the second part. So when you look at the physics of the accident, 15% of all auto accidents have a medical claim associated with it. So there's a linkage in the connectivity. So we actually have physics models and AI models that can actually look at the physics of the accident and then help predict what kind of injuries resolved, what kind of payment should happen. So that's a very deep connection. And then maybe, Brian, you can take the other part?

Yes. So as far as the sizing, today, casualty is about 10% of our revenue. So say, $80 million. The auto physical damage side of the business is closer to $300 million. If we were at similar level of adoption, those would be similar size product lines. So we think the opportunity is moving from $80 million to $300 million and doing that over time. Today, we have 27 of the top 30 on our APD side and much lower penetration rate on casualty. And so that's the opportunity we have in front of us.

Perfect. And talking a bit more about one of the somewhat newer elements within your story, which is subrogation. Could you talk about the opportunity there and the demand for that product that you're seeing?

Sure. So just for the audience, subrogation is a process of one policyholder hitting another policyholder and then the person at fault collects the money from the other side that happens behind the scenes. So today, roughly 15%, 20% of all claims are subrogated. And so the dollars involved are massive. It's about $20-plus billion in subrogation and $2 billion to $3 billion is just administrative cost. So what we've been able to do is to deliver a brand-new product. And again, the artificial intelligence plays a key role into it, where the AI can now understand the claim-related information about who is at fault, which one should you collect and which ones you shouldn't collect. And we've been applying a lot of that capability to several and the -- and we've just literally introduced the product in the last few months, and the receptivity has been absolutely terrific from customers because the heart of subrogation, the underlying information is a valuation, is a total loss report. It is a medical claim. It is a tow bill. It is a repair estimate, all pieces of information, we understand very deeply.

Understood. And if I may ask about some cross-sell and upsell opportunities. There are quite a few products that you discussed, diagnostics, calibration. Can you talk about what role does upsell and cross-sell play in your long-term growth strategy and revenue assumptions?

Yes. So we frame long-term growth targets of 7% to 10%, and we talk about that as an organic position. And what we've said is, over time, we'll be moving towards -- about 20% of that will be coming from new logos. Historically, it's been higher, but because of the penetration rate we have with the carriers, we see about 20% in the long-term model coming from new logos and then 80%, to your point, is coming from cross-sell, upsell. And then we've said about half of that will be coming from these newer solutions that we've more recently launched and brought to the market. So that's Estimate-STP, as we've talked about is a subrogation product that Githesh just talked about. It's diagnostics, its payments. So those are those new emerging solutions will be about half of the cross-sell, upsell going forward.