Welcome to the next company. We're going to speak today to Alex Timm, Co-founder and Chief Executive Officer of Root. Alex is a veteran of Nationwide. He co-founded Root and is an actuary by trade. Root has demonstrated a great ability to execute and perform, but importantly, they are early in their growth trajectory and the best, and certainly ahead of the company. Root was founded in 2015 by Alex and his co-founders, based on the idea that insurance rates should be based primarily on driving behaviors, not demographics. They utilize mobile technology and data science to offer fair, personalized rates and to good drivers. Sorry about that. Root went public in 2020, and today it's the largest auto insurtech in the country and boasts one of the best underwriting track records in the industry. With that, let me introduce Alex. Alex, let me start with the first question. Can you share a brief history of how you got to where you are today and how did you create Root? I mean, first, right, it starts with a customer problem. And like I always say, I have never met anybody who, you know, when you talk to them about car insurance, they're like, oh, you know, what I get to do this weekend, I get to go shop for car insurance, right? Nobody likes this industry. No consumers really enjoy the product. And you ask them why, right? And they're like, well, if I buy the red car, then I'm going to pay more or the black car. And no matter what I do, my prices just keep going up. I don't know how this thing works. It's a racket. I mean, it's an industry that is generally pretty despised by consumers, and it's getting worse, obviously. And to Brad's point on my background, I had a front seat to that. I'm an actuary by training. My father was an insurance entrepreneur, and I was working in corporate strategy at Nationwide Insurance. And it was my job to look at, well, what do we do about this, right? And two big things were happening. The first is really the advent of data science and big data. And so, you know, as an actuary, I used to be sort of a hunter and gatherer of data. I used to say, oh, what's your credit score? Can I get this credit report and then put it in a linear model to try to figure out whether or not you're going to get into a car accident? And that was fundamentally changing, right? Now, suddenly, we're all walking around with supercomputers in our pockets, called your smartphone that you're sleeping next to, and it's just generating data like crazy. And so the data problem totally changed. It was now I get to plug into these sensors, and I'm just awash in data. And I have to figure out what data makes sense and what doesn't. And it turns out this thing called machine learning or artificial intelligence was super helpful. And so this was 10 years ago, and this was sort of when these algorithms really were starting to be developed. And the second thing that was occurring was consumers were moving. Consumers were moving to the smartphone. It's the fastest growing retail channel in the country, and there wasn't really a single large market incumbent that was leveraging mobile technology to meet consumers where they are. And so the core idea of Root was, let's build an insurance company that meets consumers where they are on the smartphone. And by doing business this way, let's leverage all of the rich behavioral data that we can get off the phone to better and more accurately price risk. So insurance is all about matching price to risk, right? And by the way, by doing business this way, we can increase transparency. We can create a much better customer experience. We can offer three-click purchases. Now we're embedding with vehicles directly, so whether it's an OEM or a vehicle sale, to make the consumer much happier, to create a frictionless product so it doesn't take 15 minutes to purchase a product online that you never wanted to shop for, frankly, in the first place. And so that's really how Root was born. It's been a long time. We launched the first product in 2016, and it's certainly been a journey since then. That's very interesting. We have a lot of new investors here who haven't known the story. Talk about the technology. What's behind that? And talk about the distribution of the model. So the technology, I said it a bit earlier. One, there's obviously our mobile app and our mobile phone. And we were really the first to come out and say, hey, you can use mobile cell phone data to sort of predict auto insurance claims. At the time, all of the still most of the telematics data in the industry is based on these things they call dongles. And so the model was, hey, sign up for insurance. I'm going to ship you a device. You're going to plug it into your car. You're going to drive around with it for six months. Take it out and send it back to me. If you forget, I'm going to charge you $200 for the device, all in the hopes of like a renewal discount. And obviously, consumer adoption was very, very low. One of the pieces of technology that we built was, how do you actually do that using a smartphone? And that's super hard. That technology problem is very different than using an OBD-II device. If I showed you an OBD-II device, the data would look super, you'd know what the car was doing. On a smartphone, you plug into these devices, and it was really built for video gaming. So we hit the device multiple times, 16 times a second. They're super noisy sensors, and we have to take all of that sensor data to figure out, were you the driver? Were you a passenger? Was that a bus trip or not? You've got to clean all of this data to actually figure out what the physical events are on the car. And by the way, you have to do it also in a manner that doesn't kill the smartphone battery. And so we really are one of the only ones that have developed internally, as an insurance company, a closed loop on data science and machine learning that is involved with that smartphone technology. So we control the way that we collect that data off of smartphones, which is very difficult, how you ultimately clean that data, and then ultimately how that actually relates to risk. And so we've had this now validated by Milliman as an independent third party that sort of said, our telematics is just far more predictive than anybody else because of that platform, that closed platform we've built. I mean, the entire company is a technology company at its core, and so we've really created an insurance company as a platform. So one of the things, too, that we leverage in terms of distribution is not just our direct channel on our mobile phone, our mobile app, but also we have an embedded in partnerships channel. So if you go to carvana.com and you purchase a car and you want to include insurance with it, that Carvana Insurance, it's actually Root. And the reason we're able to do that is because we've built these really flexible and dynamic underwriting models and systems that allow for us to ingest all of the data during that vehicle purchase process, actually ingest data also off of the vehicle if it's a connected vehicle, and then offer just a three-click purchase experience for the consumer. So when we launched that product, for example, on Carvana, we by many multiples increased their adoption of car insurance. And so that's been growing. We're adding more automotive partners to our platform right now, which we like. It lets us get closer to the data, too, that's coming off of vehicles as vehicle technology is changing. So really every part of Root, we've really rebuilt the entire insurance value chain based on modern technology, which then has allowed us to really put these really rich data science algorithms that sort of are self-tuning on top of that. So it's really the technology is pervasive. It's across everything. It's interesting. There are these giant insurance companies, legacy guys. How do you compete, though, against them? Can't they just do this? Well, you'd think that they could. I mean, listen, they have competitive advantages, and we don't sit here arrogantly saying, oh, we're just going to blow right by those guys. They've got a lot of money and a lot of brand, and they really compete on marketing. Billions. It's It's actually auto insurance is the number one advertised single product category in the United States. By the way, it's a mandated product to buy. So it's not like they're creating a bigger pie. That's how they're competing. The way we're competing is with product and technology. And the reason these guys can't do it, most of our competitors are over 100 years old. GEICO, as Ajit Jain just said at Berkshire Hathaway, that they have 600 back-end systems, and they're trying to get down to like six or seven. A lot of these guys are still on mainframes. Most of them actually, within the last 12 months, Progressive included, actually have had COBOL programmers posted on their websites to hire. So when you think about trying to do enterprise modernization, and I saw this working at a big insurance carrier, they're trying to just get the basics right. And they've outsourced almost all of their technical capabilities, even like policy management and claims management. Those aren't even their systems. So when you talk about creating a new closed loop system based on modern technology that's leveraging machine learning, I mean, they're not even close. It's very interesting. So talk to us a little bit about, I think you're the first insurtech company to get to GAAP profitability. And you did that in the third quarter of 2024. Talk about this and how it validates your business model. It took you a while to get there. And how are you guys thinking about that? Yeah, one of the hardest things about starting an insurance company from scratch is you have no data and lost data. And so one of the things, if you look over the long history of the company, since we launched, we've been getting like three points out of the loss ratio every quarter, which is basically three points of margin every quarter that we've been building in the business. And there was COVID and hyperinflation, which was kind of a challenging period for us. It was a very challenging period when we saw used car prices go up. But actually, if you trend right through that, you kind of end up where we are today, which is best in class margins. And the way we're able to do that is because of the technology. Being able to segment risk better means we're able to pick up the most profitable customers. Being able to have differentiated access to customers through our distribution channels has also created really a moat around our business, and as we've scaled, what that has resulted in is really margins that are not just better than all the insurtechs, by the way. They're also better than, I think, most all the incumbents, so we're very profitable. We've also grown our customer base. I think year over year as of last quarter, it was close to 100%, so the business is growing, and like I said, in terms of margin on the business, it's maybe the best or one of, if not one of the best in the auto insurance industry. Let's step back and assume this is not an insurance conference. Talk about loss ratio. Explain that to them, how you look and think about loss ratio and what that means. Yeah, so it's the most important financial metric in an insurance company. And really, it's your losses divided by your premiums. So what percentage of your revenue are you giving back to pay claims? And that's so important because, one, it's 60%-70% or so of all revenue if you just look industry-wide. And so you might be able to innovate and do some interesting things on distribution costs or fixed expenses through automation. But if you want to be serious about disruption and taking cost out of the system, you've got to be serious about how do you get loss ratios down. And that game is all about who's going to get into an accident and who's not. And when you take a step back, really, what that game is about is how do you identify the 5%-10% of people who are causing basically all of the accidents? There's like a few many. This data is incredibly skewed. Like when you're driving down the highway and you see somebody weaving in and out and you go, that guy's going to cause an accident, you're right. That's like 5%-10% of the population. And so what's really important is how do you identify that percent of the population and get them out of your book as soon as possible? And we've been able to do that both through our telematics advantage, and that's really what's led to that loss ratio being one of the best in the industry. Again, if not the best. That's very interesting, and then let's talk about your GAAP profitability, but you have to grow, right? You haven't gotten to scale. How are you going to balance that? Talk to us about balancing scale, investment in the business versus profitability. How do we think about that? Yeah, this is always an interesting question to me because I never thought this would be an interesting point of view because you kind of go to school and you learn, hey, we're all supposed to deploy capital above our IRRs and then stop, and that's how you sort of optimize. But what we do at Root is we basically, like I say, we worship at the altar of the unit economic gods. We continue to grow provided that we are returning with a high degree of confidence our cost of capital. That sounds obvious. That's a textbook answer, right? It's remarkable because when you look at our competitors, what we tend to see is that they're very focused on a 12-month period, and what that's resulted in sometimes is suboptimal decision-making by them. And so, for example, if I need to hit my bonus metrics for the year and I'm ahead on profitability but behind on growth, I might just push a whole bunch of marketing capital into the system, even if it's not accretive. Or conversely, if I had a bad Q1 and I'm not profitable and now I'm in Q4, maybe I'm going to pull way back even though my current marketing would be accretive. And what that does is it creates these cycles in the industry. And so when we talk about growth, what you'll see from us and what we've shown is we are almost countercyclical to that because we don't operate that way. When they pull out, we'll push in heavily. When they push in, you'll actually see us push out. And so on our direct channel, you actually see sort of this countercyclical growth sort of up and to the right. But again, it can come down and up, and it can ebb and flow. On our partnerships platform, that's been very consistent. That's been a balance of growth. We continue to add more automotive folks to our funnel. That funnel is extremely healthy. Given what we achieved with Carvana and then subsequent partners, that's just coming through. And if anything, that's more about can we service all those partners as they come through. So on the capital side and profit side, we're very, very healthy. But at the same time, if we see the opportunity to push growth harder, we'll certainly do that, provided we hit our returns. So it's not a, we're going to make this amount of money every single quarter. We don't think that's the right way to run the business. It's, we're going to deploy capital at our target returns, and that's how we optimize the long-term value of the company. So it sounds like you're taking a long-term approach to growing this business. Yeah, yeah. Provided long-term, yes, yeah. I mean. Versus a quarter to quarter. Yeah. Oh, yeah, absolutely. Not a quarter to quarter. We take a multi-year approach. That's great. And then talk about these growth. What levers can you pull? How do you make this business grow? What growth levers do you have? Well, so the biggest lever I mentioned is number one is just adding more partners to our platform. OEMs all the way through vehicle advertisers. We're live with independent agents. Turns out they don't want to be on the phone with you for 20 minutes selling you insurance any more than you want to be on the phone with them. So they like our platform a lot. So we're continuing to add partners. That's grown. I think as of last quarter, it grew like 130% year to date, and that's been really linear and consistent. Second, we're in 35 states, and so that's about 75% of the population. We're regulated on a state-by-state basis. No reason we shouldn't be national. So we're going to continue to push to get national. And then third, we're continuing to add actually new marketing channels to our platform. So we still are primarily operating in lower funnel search channels. We're starting to actually experiment more with social media, YouTube, and some of those higher other marketing channels as well, where we can use our data approach to sort of acquire the right customers. That's helpful. And that growth figure you gave, is that back? that back? You said year to date. I assume you're tying backwards to 930. Is that? Yeah, yeah. We don't have anything. Yeah, yeah. Just clarification on that. Talk about the partnership channel, getting channel and OEMs. What do you learn from OEMs? How does that become important to you? OEMs are so important. One, what we've learned is the idea to embed insurance at the point of vehicle sales is not a new one. Lots of folks have failed trying to do this. But that's because what they're doing is they're putting like an independent insurance agent inside of a dealership. And so after you've been on the lot for three hours trying to purchase a car, then they're saying, oh, go talk to an agent for another hour, and consumers don't want to do that. What we've done and what we've shown with Carvana is that when you do this in a digital manner, it's totally different. So when you can actually integrate with whether it's an OEM app or a Carvana app or even the vehicle itself, offering a three-click insurance experience as part of purchasing that vehicle, that does work. But to do that, you need to be able to integrate with those vehicles, which means you have to have modern technology. Root's really the only one that is both an insurance, a car insurance carrier, and a technology company that can provide that solution. And so that's what we have shipped and built. There's some really interesting things with OEMs. They're also working on their own technology. Now these cars are suddenly changing in terms of their risk parameters through over-the-air updates. So what does that do? And what we've done is by creating this platform that we can embed on sales is we're also starting to ingest a lot of that OEM data so that we can start to say, hey, this autonomous feature works and actually does reduce risk, for example, when it's used in this manner. By the way, they're not all created equal. These other autonomous features on these other year-make models, maybe they don't work, and so we sort of have a front seat to understanding how that vehicle technology is changing, which then allows us to be a better partner, better price risk, and build a better company. Besides avoiding that crazy driver out on the highway, who is your target customer? How do you find that? You know, it's interesting. Generally speaking, we over-index on people from the ages of 25 to 40, and they tend to be a little bit more tech-savvy. They tend to be a little bit more urban, but we've actually seen a very wide halo effect. We have lots of different customer demographics on our system, and one of the keys too has been we can be profitable in each one of those segments, and that's super important for us. That's super interesting. And so in terms of pricing, you said recently that you may be able to reduce rates for certain customers. How does that work? And are you doing that to grow market share? Or how do you explain that? It's interesting. As we get better and better, as we collect more data, we retrain all of our models, which get better. What that does is it basically tells us who's a good risk, who's a bad risk through a variety of different data sources. We have a decision to make. We can either increase margin with that model, or we can reduce rates. The way we make that decision is we look at the microeconomic curves and elasticity, and we say, well, what optimizes for the long-term value of a customer? That's exactly what you'll see us do. What's happened as we've continued to update our models and become better at segmenting risk, our loss ratios actually come below our targets. What you're seeing now is actually a reduction of rates. And so we're lowering insurance premiums actually for our customers as these models are getting better. And then it's interesting because as we do that, we grow faster and we get more data. And that flywheel, when that began to spin, that's really when you started to see sort of everything work in the business because, again, it's that virtuous cycle. And so we're not lowering rates to sort of reduce profitability. We're actually, it's the opposite. We're fine-tuning it for profitability. However, you will grow faster. So you talked about you came from a giant insurance company. They have these, you said, the biggest budgets of anybody. How does Root compete? How does Root sustain this growth of disrupting the industry? What do you need to do? I think one is we have to stay true to our technology. We have to continue to invest in the future. We have to continue to invest in our partnerships and embedded distribution and our product. And then we have to stay true to our principles and our culture. We have a very different culture, and I think we've got to continue to hold on to that. And that's what's going to, long-term, I think, create a really great company. And then just talk to what technology do you invest in? Where do you need talent that you don't have today? Or are you going to take that? We're heavily investing in data science. That's still probably our number one area that we're recruiting. And so we've got a lot of data scientists on staff. We're mostly just like a bunch of math nerds and engineers. And so we're heavily investing into both of those areas to both improve our embedded platform and create a more seamless customer experience, continue to launch new partners. And then as well on the data science side, where we continue to see opportunities to refine more and more of our model suite. Great, and I'm going to ask one more, and then we can open it up, but tell us what's your vision. What's Root look like in five years? I don't have to give us numbers, but what's your vision? This is an opportunity to build a historic company. Nobody came to Root to build the number 10, the number 12, or whatever the market share might be. We all came here to build number one. And we think it's very rare that you find an industry that is so widely hated by customers, so massive. I mean, it's a $300 billion industry just in car insurance. It's even bigger if you look at all property casualty and has been basically untouched by innovation, with over 100-year-old competitors basically dominating all of the top 10. And at the same time, you have these massive changes in technology that really change the fundamental value proposition of insurance, which is pricing risk. And so we think when you get that right, that we're actually just, we're not even in the first chapter. I say we're like on the first page. And so we think that our ambition is to be the number one carrier in the country. That's highly compelling. I think we're kind of out. Root's going to have breakout sessions. They got two down in Coquina Room, and I thank everybody for joining us, and Alex, thank you for your time today. Thank you. Thank you.