Ray and Ben kick off The Inside Lane with the origin story of DOT Analysis — how curiosity about FMCSA data, BASIC scores, and the questions no one was allowed to ask turned into a platform for the truck insurance market. Then they open the dashboard live and unpack Geico's book of business: relationship duration, renewal rate, and a new business trend that flips the picture the moment you tighten the date range.
Full transcript
A complete written record of this episode.
Raymond Moss: Good.
Ben Curtis: All right, well, here we are.
Raymond Moss: Yes. We've been meaning to do this for a while, and we haven't yet. So now we are.
Ben Curtis: Man, life's been busy.
Raymond Moss: I know. It's been a whirlwind the last couple of months especially. It's been a busy couple of years, and definitely a busy couple of months.
Ben Curtis: Yeah, no doubt. But we've been talking about this for a while, and I'm super excited to be recording episode number one of our brand-new podcast.
Raymond Moss: You want to hit us with the intro, Ray? Let's do it. Here it is. Welcome to the podcast that accompanies the DOT Analysis platform, where we discuss real-time trends in the truck insurance market and explore answers to the questions you are not allowed to ask. I'm Ray.
Ben Curtis: And I'm Ben, and this is The Inside Lane.
Raymond Moss: Yes. We've been having people mention the story that we told a couple months ago when we were down in Orlando at MCIF, on stage, about the inception of DOT Analysis and how it came about. So what better thing to talk about in our first podcast episode than the retelling of at least a little piece of that story, right?
Ben Curtis: Yeah, the origin story.
Raymond Moss: Yeah, the origin story. So it is kind of fun.
Ben Curtis: It is, yeah. It's great to think back, and it sets such good context. Stories do that. They set context. What we're doing is so exciting and so interesting. And yet what we've identified, what our users have identified, and a term we use all the time, is how iterative things are, how iterative life is. You get somewhere by just iterating and building gradually on what you had before. And so anybody who jumps into the middle of something feels like that is the beginning to them. Especially starting out in this podcast, I think it would really help to tell the story, catch all of our listeners up on what's been happening, how we got to where we are, and set the stage for where we're going in the days and years ahead.
Raymond Moss: Yeah, absolutely. A lot of that hinges on what DOT Analysis is built on, and that is curiosity. I love curiosity because you start to pull different threads. What about this? Why has it always been this way? Can't we do that? And it just begins to unravel narratives. It's this never-ending story that is alive in any industry and in any market. But specific to the truck insurance market, I don't know, maybe it makes me the ultimate geek to be excited about truck insurance data. But it's so exciting, and so much of my life has been defined by that over many years. I guess that brings us to the beginning of the story, which was almost twenty years ago — fifteen, sixteen, seventeen years ago — when I jumped into the truck insurance industry.
Ben Curtis: Yeah. Curiosity was really the beginning of our story. If we skip some of the boring details of the industry backgrounds, there was a whole bunch of stuff going on with the FMCSA back in the early 2000s, including the inception of digitizing data and creating a database to be able to look that stuff up. That's really where the inception of a lot of the data that underlies what we're doing started. But our curiosity with that, and yours specifically related to what could be done with that data, was in the late 2000s, early teens?
Raymond Moss: Yep. A lot of it began with people asking questions. I've been in technology my whole career, and a lot of it in the truck insurance world. It really began with people coming up with hypotheses or questions. They would say, "Shouldn't we be able to look at industry data and validate whether this is real?" My favorite would be when a marketing person from an insurance company would come to a specific team and say, "We're growing big in this state," or "This is happening." Then the team would come back and say to me, "They said they're growing by fifty percent in the state of Idaho or Illinois or whatever. Can you figure out if that's actually true?" My first assumption was always, "Well, guys, they're telling us that they did that, so of course it's true," which we discovered wasn't always the case. That's always really fun. But being curious is a required component to that.
Ben Curtis: Yeah, so quickly here, let's just tell the story of how that curiosity turned data into DOT Analysis. In the early teens, the 2010 to 2015 timeframe, with the passing of the FAST Act and the BASIC scores, the government had mandated the FMCSA to come up with a safety mechanism to understand the safety profile of motor carriers on the road. It was really designed for the public, right? A lot of people don't even realize that was the case. They're so entrenched and ingrained in the underwriting and insurance landscape that it's often easy to associate them with that. But that actually wasn't the origin of the BASIC scores. They became so detrimental to the trucking companies themselves that the government finally decided not to publicly post these scores anymore.
Raymond Moss: Yeah, yeah.
Ben Curtis: But the insurance companies and underwriting teams had become so reliant on them that they scrambled to figure out how they were going to reconstitute or recalculate those scores so they could continue to use them the way they had become dependent on them. I think it was that event, really, for our team, that sparked this curiosity you mentioned. It led us to think: why has the insurance industry become so dependent on something they didn't create or even really come up with? Wasn't that a key moment?
Raymond Moss: Yeah, that really was. That was very key. Another piece of curiosity sparked by that was, if this is so important to them, is this the only thing you can discover inside this data? That was the next iteration. We talk about iteration, and everything we do is iterative, because that wasn't the first assumption. It was the next iteration where we started to unpack the safety picture of a motor carrier with the data, just like the government was doing. Then we were sitting in a room one time, looking around at each other, and the question was, "Wait a minute. Look at all the other patterns that are in this data." There is so much more about the industry at large that you can pull out of this data. Maybe we should be asking different questions of that data.
Ben Curtis: Right. I think the realization we made was that the FMCSA had this safety mandate, so they went to this huge database and asked it a safety question, and they got a safety answer. But we realized that just because they asked a safety question doesn't mean those are the only questions we should be asking. So we started exploring the range of questions we could be asking and that this data could be answering for us. That was wild. I mean, almost overwhelming.
Raymond Moss: Yeah, because the moment we came up with a question, it immediately sparked five more questions, and then each one of those five sparked another five. It's this wild prioritization game of, okay, now we know it's possible to ask these sorts of questions about the truck insurance market. How do we prioritize which ones are most important? Then you have people in your ear from all sorts of different perspectives saying, "This is the most important," or "This is the most important." You have to prioritize that and figure it out. That was exciting to be able to do.
Ben Curtis: Yeah. Our starting point was identifying the questions that actually matter to insurance professionals and that we should be focusing on in the data. I think you've got your screen there. Do you want to pull our dashboard up and look at some of the questions we asked, what that's doing, the visibility it gives us into the marketplace, and the stories we can see and find that we want to discuss on this podcast?
Raymond Moss: Yeah. Let me throw one in here that is always top of mind because so many of our current clients and customers reach out and ask questions about it.
Ben Curtis: Even what you're doing right now is an example of a question that we said you should be able to ask. You should be able to not just look up who a motor carrier is insured by, but ask who all the motor carriers are that are insured by a specific insurance company. Shouldn't we be able to see that book of business and have visibility into it? What you're displaying right now is the ability to look at Geico's book of business and see what that market picture is.
Raymond Moss: Right. In theory, the original question was, if we have all this data, all these little grains of sand out there, shouldn't I be able to zoom all the way out and see the entire beach? Can't I see all of that sand at once and form a cohesive picture and understanding of underwriting behaviors, market dynamics, and realities? Absolutely, we can and should be able to do that.
Ben Curtis: Right. And then to break that down a little more, we want to be able to see not just an individual grain of sand and not just the entire beach. We want to go in between that and see the sandcastle that exists on the beach as well. What we're looking at here is that we can zoom in and out to just the right depths to see whatever we want to. For example, in this case, we're not looking just at an individual writing paper. We're looking at Geico, which has grouped together their writing papers so we can get a full view of their true market presence.
Raymond Moss: Yeah. That's one thing that was really exciting: aggregating that knowledge together. I literally remember the first time we realized what kind of value could be created by putting that picture together in a meaningful way. When you can take all the papers that a logical insurer, as we call it, is using to write business, and put all those together, you can actually see and understand what their market presence is. I can see, for example, that Geico has just about twenty-six thousand filings here, split across several different papers. If you just look at one, you get only part of the picture. And if you have part of a picture, you can't use that because it doesn't tell the whole story.
Ben Curtis: Right. A couple other examples of the types of questions we felt like we should be able to ask, and that the people in our orbit wanted to be able to ask: I see the relationship duration graph there. So give me an understanding. This is the question, right? To understand their book of business, how mature is their book of business? Tell us a little bit about this relationship duration graph.
Raymond Moss: Yeah, this graph was born out of answering a whole different slew of questions. The primary one was the depth of relationship in a book of business. You can take someone who's got a thousand clients or someone who has ten thousand clients, and that doesn't tell the whole story. You have to know how long they've had a relationship with those clients in order to estimate the stickiness of those clients and the likelihood that they'll be around for the long duration. Then you have to compare that to the general market. Maybe nobody has a five-plus-year client, but you do. How sticky is that really? Unless you have a comparative metric for so many of these things, it's much less meaningful data. Being able to compare a book of business to the market or compare a book of business to a different book of business — that's the power of what we can do here with the relationship duration graph. I love doing that.
Ben Curtis: Yeah, and most people in the industry know that Geico is relatively new on the scene, which is perfectly illustrated by this graph. It shows almost exclusively their business being in that first one or two years. Of course, the orange market average gives us that comparison. You can see that it's not uncommon: twenty-four percent of the market exists in that five-plus-year duration.
Raymond Moss: Right. You can see that book as it matures from the left side of the graph over to the right, and you can understand where an insurance company is going. If you've been in this industry long enough, you've seen some of those new insurers come into the space because there are huge premium dollars in trucking, right? But then they have a big splash and fizzle out. I'm not saying that's going to happen with Geico. I have no idea. We're just looking at the data as it is. But those stories have played out over the course of my career, over the last fifteen-plus years, and over the careers of many others who have been in this industry for a couple of decades.
Ben Curtis: Yeah. We're obviously not going to get into the policy-level data here, but just to point out, we do have the individual grains of sand. Depending on how people are using this, we have the ability to go into the underlying policies in each of those categories, which is a discussion for another day but a very interesting way to unpack these. Now, to get into a little bit of the nuance of the types of questions we're asking, let's compare the relationship duration graph to the renewal rate. It's easy to hear those terms and think that's the same thing, but they're uniquely different. With renewal rate, we're not just looking at what percentage of their book of business exists in each policy year, but the rate at which they move their business from one policy year to the next.
Raymond Moss: Right, which is so telling because it's going to answer a whole litany of other questions about the health of the insurer or the health of the grains of sand on the beach, so to speak. It tells you whether those motor carriers are commodity buyers who are just buying for price, or if they're buying for quality, and you can see the churn. In this case, Geico is surprising a lot of people. They're actually renewing better than the market average at both the first-year and second renewal, which is the bulk of their book. They're doing decent in that regard.
Ben Curtis: They are, yeah. But because we can see that relationship duration graph, we see how much of that is in the first year. Even renewing at a forty-seven percent rate still means that a huge number of policies are leaving Geico if that trend holds. It's still interesting data to use however you want to unpack it and utilize it.
Raymond Moss: Right. That's very true. In order to sustain that, they have to keep their new business game going. Statistically speaking, if only forty-seven percent are renewing on the first renewal, that means fifty-three percent are gone, and you have to backfill that. So there's a lot of new business growth that has to continue on Geico's end.
Ben Curtis: Yeah, so let's use that and unpack the menu here, specifically new business. We've had conversations with so many of our customers recently, and one of the themes is the amount of work it creates without a tool like this to generate a dashboard like this. But it's significant to have an instantaneously updating dashboard with the depth of menus that we have, to contrast different market segments or update date ranges and get an immediate comparison, because that's what really brings a story to light.
Raymond Moss: Right. It definitely does. What do you want me to change on the filters here to illustrate that best?
Ben Curtis: You mentioned new business, so we have the ability to break out new versus renewal business. Let's look at Geico's new business picture specifically. We also need to point out that we're looking at a date range. By default, we're comparing now to a year ago. We look at the trailing twelve-month time period. We can see the trend data over that time period, which is interesting, but it's a snapshot. It's one picture. Like I said, I was talking to a customer just a few days ago who actually felt a little bad. We were looking at this dashboard and he said, "Man, I just wasted a week of my life because I tried to create what you're showing me. It took me a week to generate what we're looking at right here with the click of a button." It really is powerful to be able to do that. So take this snapshot we're looking at now compared to a year ago. We can see not only on the overall policies, but on the map, where they're growing and where they're declining. Now we're looking specifically at new business, so we can see that it was a little different than their overall book, which was pretty much exclusively green. But if we adjust the date range, that's where we can really start to zero in on the trend that's developing. Let's do that. Why don't you play around and tighten up the date range a little bit and look at how this trend is developing? First, read off the stats we've got here for the now compared to a year ago.
Raymond Moss: Yes. I'm looking at Geico now, and they're down by three percent compared to a year ago. I'm just talking about new business, okay? I'm looking at all fleet sizes in all states, just new business. They have, call it seventeen thousand policies, that are new business between now and a year ago. So I'm going to cut that in half. They're down by three percent in the last year. Let's just look at the last six months.
Ben Curtis: And overall book.
Raymond Moss: This updates, and look at this trend. This is so fascinating because I cut that in half. They're not down three percent; they're actually down fourteen percent in their new business growth over the past six months.
Ben Curtis: And for those of us who aren't on the video or are just listening, the map is turning substantially more red, meaning a lot more states are red and showing declines over the last six months.
Raymond Moss: Yeah. That's interesting because you can start to see where they're reeling in their new business appetite. It's amazing to see that visually play out. I love being able to do that. What's also fun sometimes is when you have an insurer you're working with and you know some of the lay of the land internally with the underwriters. I love when I can see the personality of an underwriter displayed on the map, with whether their states are green or red. It's so fascinating. So here, with Geico, I'm looking at now versus the last six months. Let's get back to this. It's down by fourteen percent in new business growth. Let's cut that in half again and look at the last three months. All right, the trend is holding. They're down by fifteen percent in total over the last three months. Super fascinating.
Ben Curtis: Yeah. And all but, what, four states are red on the map now?
Raymond Moss: Right. Yeah. Just a little bit of green in Montana because they had eight new filings there. Nevada had a couple. New Mexico, and then Vermont had a handful. So yeah, every other state is turning red. Fascinating.
Ben Curtis: So interesting. If we reset it back to now compared to a year ago, just to emphasize the difference, look how different the picture is. You might still make the assumption looking at that data that Geico still has this insatiable appetite and they're writing everything. Well, they're still writing a decent amount of business, but being able to adjust those timeframes, we can see that there is a drastic difference. The trend is going way down.
Raymond Moss: Right. And let's not miss this too. Because we're just looking at new business, that's even more clarifying. If you're just looking at number of filings, you can't see the difference between new and renewal. So when you look at both new and renewal, it looks like it's green just about everywhere.
Ben Curtis: Almost the entire map is green. Only a couple of states are red as far as decline over the last year.
Raymond Moss: Yeah. Having the ability to answer all of those natural questions that come out when you're unpacking a specific market story with someone's book of business is always exciting because it's like you're reverse engineering what's happening in real time.
Ben Curtis: Yeah. The stories are very fun to follow. There are so many different ways to use this information. We like to say we're data agnostic, meaning none of this information is inherently good or bad. It's all useful in various ways depending on what you're trying to do. But knowledge is power, and the more you know, the more you're able to operate from a place where you're making strategic decisions and not just subject to the whims of whatever story you're being told. That's what we want to do: present the data, the facts, what's visible, what we can actually see. Then you can determine how you want to use that data and how it's going to be meaningful in your business or in the weekly plan you're making.
Raymond Moss: Right. Yeah. I'll give a twenty-second story here just to emphasize that point, Ben. I had a client probably three, maybe four months ago, jump into DOT Analysis. One of the signal moments that really sealed his desire to jump into the platform was the fact that I showed him the state he was in. He said, "Hey, look at this specific insurance company." We pulled them up. He had just gotten a commission rate cut from that insurance company because the insurance company had said to him, "We're writing a ton in this state, and you're just not pulling your weight. We need you to be writing more. We've got a lot of new business growth here, and you're not doing much of it, so we're cutting your commission rate back down." That was fascinating because the state was blood red, and that insurer was falling dramatically. So he was able to leverage that and have an easier negotiating conversation with that insurance company, which is fascinating.
Ben Curtis: Yeah, but without a tool like this, what would you do? How do you respond to an insurance company that's telling you this is their reality? Until you're on the same playing field and have access to this data, you're not able to approach that conversation differently.
Raymond Moss: Right. You can't see it. Yep. So many fun stories like that from the insurer perspective or underwriting perspective. I could go on and on, but I'll save that for next time.
Ben Curtis: Well, we're looking forward to unpacking a lot of interesting stories. We love your feedback too. Let us know what stories or insurance companies you'd like to hear about, or interesting things you see happening. We'll be following trends here and tracking progress and development, as well as uncovering unique and developing stories and bringing those to light. In general, we'll be unpacking things that are interesting to insurance professionals and, hopefully, being a platform of completely unique content for the industry.
Raymond Moss: All right, well, until next time, we'll see you guys later.
Ben Curtis: Yep. Have a good one.