Underwriting & the Underutilization of Data: An Interview with Will Ross, CEO, Federato

August 21, 2023

On this episode of The Leadership in Insurance Podcast, Will Ross, CEO & Co-Founder of Federato joins host Alex Bond for a wide-ranging conversation about innovation in insurance underwriting, the rise of the portfolio underwriter, and how leading insurers are using reinforcement learning and other bleeding-edge technologies to operationalize their data and risk strategies, and optimize their portfolio. Will also shares his take on why embedded insurance is more than just a distribution play, but a way for insurers to gain a risk selection advantage.

“The basic concept that we call RiskOps really comes from this idea that the risk department or the portfolio management department within most insurance companies today sits at quite a distance from the day-to-day underwriting operations. As we think about the macro factors that are affecting the industry right now – natural catastrophe, social inflation, economic inflation, cyber would be another big one – almost all of these topics require some level of more proactive portfolio management. So, the idea of RiskOps is, ‘How do you bring the portfolio aspect of the risk department to the day-to-day underwriting operations in a more proactive manner?’”

– Will Ross, CEO and Co-Founder, Federato

Key Takeaways

🎙Why insurers can no longer afford to underutilize data.

🎙How the Federato RiskOps underwriting platform brings proactive portfolio management to the insurers’ day-to-day underwriting workflow. 

🎙A look under the hood at how Federato does what it does.

🎙Why risk transfer, limited capacity, and the rising cost of reinsurance is the #1 problem facing insurers today, and how a tech-driven approach to portfolio management can improve outcomes in reinsurance negotiations.

🎙The importance of culture when building insurtech teams, and the need for insurance knowledge in-house to deliver true value.

🎙What Federato's recent $25M Series B raise means for the company, how it came about, and what the next 12 months hold for the company and its products. 

Watch the Full Episode

Tune into the full conversation between Will and Alex on Spotify or Apple Podcasts, or click play below.

Read the Full Transcript

Alex: Good morning, and welcome to "The Leadership in Insurance Podcast." I'm your host, Alex Bond. And I'm very lucky today to be joined by Will Ross from Federato. Will, how are you?

Will: Doing well, doing well. Good morning.

Alex: Yeah. Morning. Yes, it's the ruse of the morning, the release time. I hadn't prepped you on that. I'm just gonna launch into a kind of wrong time of the day. But look, thank you for joining us. I know that you're a really busy guy. And before we dive in, we've seen it, we've announced it. We announced your fundraising in June. And obviously you and I have spoken before, but it would be great if you could introduce yourself and the Federato business, please.

Will: Yeah, sure. So, for those of you who may not know us, Federato is a technology provider, so we fall into that side of insurtech. And specifically, we build what we call the RiskOps underwriting platform. And so, the basic concept that we call RiskOps really comes from this idea that the risk department, or kind of the portfolio management department, within most insurance companies today, sits at quite a distance from the day-to-day underwriting operations. And as we sort of think about the macro factors that are affecting the industry right now, natural catastrophe, social inflation, economic inflation, cyber would be another big one, almost all of these topics require some level of more proactive portfolio management. So, the basic idea of RiskOps is how do you bring the portfolio aspect of the risk department to the day-to-day underwriting operations in a more proactive manner? And so, we use a sort of underwriting workflow piece of software to both facilitate the underwriter's workflow and bring kind of that portfolio management to bear in a more active way.

Alex: Awesome. Thank you. I love the slickness of a man that's been through fundraising rounds because you know you can succinctly explain it.

Will: Well, the irony is, we didn't even go out and fundraise our series B, right? You know, it was an internal round, and quite a pleasant surprise at that. I don't think everyone sort of recognizes that, but it was actually led by our seed investor, Caffeinated Capital. You know, I think my investors would tell you I'm notorious for being the worst pitcher they've ever seen. Yeah. I think our Series A investor, the partner who's on our board, Lotti Siniscalco, had to go re-pitch her own partnership, basically, on my behalf. So, I appreciate the compliment, but I'm not convinced it's my number one skill.

Alex: What do you think makes you a bad pitcher? And shouldn't you be good at pitching, with your background?

Will: You know, to be honest, I've heard a lot more pitches than I've given historically. You know, my background is much more analytical, right, kind of come from a data science and product background, you know, not a sales background. And, you know, this is my first company. So, you know, like, look, it's a big part of the job. As you can imagine, I spend plenty of time in sales meetings and plenty of time with potential investors and things of that nature. But, you know, I don't think it's the number one job of a CEO, right? I think it's one third of the job of a CEO. You know, the other two are a little different, so...

Alex: I remember when I first started working for myself and I was trying to set up a company, and my uncle's a very successful but self-made entrepreneur. And he had a big design company. And the first thing he did was like, sit me down and went, "Right, now you're the CEO. You are 100% a sales guy. If you weren't a sales guy before, you're now a sales guy." And, yeah. And then he said, "And if you go out of a venture," and he's like, "that's a bit...you know, and fundraising, is, it becomes a huge part of your job as well." So, yeah. It's strange that you kind of start a company because you're passionate about solving a problem or having a solution for things. And then actually, the role of the CEO kind of becomes, you know, selling the idea, the vision sometimes, and then fundraising as well, the part of it, and bringing you away from kind of executing on probably that part of that as well. So, It's really interesting to see how people kind of evolve in that.

So, I’m interested to know: this is your first company. Why was this the thing? Why was this the problem that you wanted to solve? Yeah, I'm always intrigued about why was it this one that you couldn't let get away, and you had to kind of dive into?

Will: Yeah. Well, look, I mean, certainly among those who've stumbled their way into insurance, but I think via a very different path than most people. You know, my whole background is in the machine learning space, like I said. So, kind of a data scientist, product manager by training, and have been working in and around AI since sort of the last big wave, which was the advent of deep learning, particularly in natural language processing and computer vision, around 2011, 2012. You know, this new wave of generative AI is a really interesting thing to be experiencing. But really, it's been a wild ride for 10 years straight. And I had started to have a bit of a macro observation about AI companies. I'd been privileged to launch many AI products, see several failures, several successes.

I'd also been in a position where, like I said, I was seeing a lot of pitches from startups. I was in a corporate development role, and, you know, got to see the outcomes of those companies and how those companies performed through time. And the big thing that stood out to me was, a lot of people were trying to solve AI problems where they took a human out of the process, rather than looking for what I call kind of a stochastic marketplace that they could optimize. I took a step back and thought about, you know, how can a really big company be built with machine learning? And when you think about the biggest companies out there where machine learning is at their core, core, core, names like Google, Facebook, Uber, DoorDash should all come to mind. And if you just sort of describe those problems, they're all optimization-type problems.

And so, you know, a while ago, I had started looking for, "Is there an optimization-type problem that I can solve out there with machine learning?" Happened to meet my co-founder, a gentleman named William Steenbergen, doing graduate research at Stanford, focused on wildfire modeling. That was just an independent passion of mine. I was getting a second graduate degree, specifically in that area. And he and I started to get approached by insurance companies. And over time, what we started to realize was that while they were coming up to us out of interest in our wildfire model, we could give them the best wildfire model in the world. But if they couldn't operationalize what that sort of portfolio risk-type wildfire model was telling them to do in their underwriting operations, it wouldn't have much value to them.

And so, in some ways, the problem fell into our lap. You know, I think Guy Raz, if you've ever read his stuff, "How I Built This," or listened to his podcast, he talks about entrepreneurship. You know, there's always an element of luck, right? And things do kind of fall onto you, but it is about putting yourself in the right place, so that there's a greater chance that you'll be that kind of right place, right time. And so, you know, I think we were fortunate. We kind of knew what we were looking for in terms of a problem shape. We happened to just be pursuing our passion in a certain area. And then those two pieces, portfolio management, and sort of the wildfire stuff, came together into insurance. And we do a heck of a lot more than just wildfire today. But it's been a wild ride, so...

Alex: Awesome. Awesome. Yeah. Sadly, a lot of need for that wildfire stuff alone at the moment. But yeah, I think we were sharing that we were in the, we as a team were in New York for the event, and we were there while the wildfires in Canada were kind of, like, coming over. And yeah, it was pretty apocalyptic. But then, I think I've just seen too many apocalyptic-based movies in New York, so I just got slightly paranoid when I emerged from a bar and could see this kind of smoky outlook above us. But I'm intrigued about, you know, the proposition. I think it feeds into that place of going, "Right, we've got the data, which is great. But how do we monetize it or use it, or how do we actually implement it into a business model?" So, kind of, I asked you beforehand, and you said, "What question have you never been asked?" And he was saying to you, "We're not asked enough how we do what we do." And I think that's always one thing that sits with me. Anytime you talk about insurance, machine learning, anything kind of, like, complex, we never get into the how. And I think sometimes it's really nice to look under the hood. So, I'd love you to, like, walk us through how you do what you do.

Will: Yeah, yeah. You know, I think we were already in love with the insurance problem before we sort of started to figure out how exactly to formulate this portfolio optimization or portfolio management-type problem for the industry. 

One of the most elegant and underappreciated things about our product is that we found a way to take the way that insurers have managed their companies for decades, if not centuries, and use very modern technologies to apply those methods. So, specifically, when I think about an insurance company that's going out to the market, they're trying to align their capacity or their reinsurance tower with their mandate.

They set their strategy – there's usually a strategy that is composed of four key fundamentals, right? The first is new business. Where do I want to grow? That can include classes of risk, etc., right? I want to get this much new business in this class, this much new business in this class. It could also include regions, or, kind of, you could slice that data by any data category. The next is retention, right? If I have an existing book of business, what percentage of that book of business am I aiming to retain, versus kind of move off my books? The third is, given, you know, let's say I'm retaining 88% of that, how much am I looking to grow within that? And that's almost always by line of business, by class code, by, again, the various data attributes that might be associated with any one given insured, or one given policy or account.

And then lastly, there's this idea of accumulation. You know, maybe that has to do with new business. I want to grow in this class code, in this class code, but I don't want more than 80% of the book to be in either class code. I need to make sure I have at least some level of balance. Or, you know, from a natural catastrophe perspective, I don't want to accumulate more than a certain amount of TIV within a certain distance to the coast in these counties in Florida, or Louisiana, or just within, you know, a given geographic radius, from a wildfire perspective, in California.

“These strategies are things that insurers have been coming up with for decades, right? And they've been putting them into plans. The problem is, those plans, even though they're developed in a very mathematical and actuarial way, they're often implemented using, frankly, PDFs, right? What we call underwriting guidelines. And so, what we recognized was, if that data exists to do the actuarial science, then that data can also be applied at the point of choice.”

– Will Ross, CEO and Co-Founder, Federato

And so, what we have effectively done is we've formulated an optimization problem that says, how can we maximize the growth of the carrier? Everyone wants to grow, right? If you can control your loss using those four categories of constraints I just outlined, you want to grow as much as possible within that. I've never met an insurance company where that wasn't true if the constraints could be met, right? And so, that is what we do. 

Every company we go into, we are basically re-solving the problem that says, "What is your unique portfolio strategy?” Allow us to take data that we know you have, because you did the actuarial science, and turn it into this optimization problem that can be proactively applied in that point of choice. We've been very fortunate to stumble on that intricate link between a very cutting-edge set of technologies that's required to solve this type of optimization problem, and a very classic approach, in terms of, you know, we're not trying to change the way our partners do business, right? We're just trying to help them do what they say they're going to do, as efficiently and as precisely as possible. And that shows up for them on the back end in very real ways, in terms of certainly, loss ratio, growth, but also in terms of basic things like more capacity, as a program, or better reinsurance terms or rates, from a treaty perspective.

Alex: Yeah. Because one would assume that this plays very nicely to the reinsurers, in terms of, kind of, they start to have a true understanding of one, you know, your plan, what you want to write, and how you're going to write it, and the constraints on it. And also true numbers, right? We can start to rely on the numbers that we produce.

Will: Yeah. No, look, I mean, I think... I outlined what we call kind of the big four at Federato earlier, right, social inflation, economic inflation, cyber, and natural catastrophe, as these big existential changes. If you took every single one of those, where do they actually show up in the pain point of, like, managing an insurance business today? It has to do with reinsurance, right? That is the number one problem in the insurance industry today, is not any of those four categories of how it's manifesting, but rather the inefficiency of risk transfer, right? The people who are paying the price right now are the reinsurers. And so, that is what is creating this perpetuated hard market. This is becoming quite a long, hard market cycle, because as reinsurers continue to take rate at the top, that flows down to the primary originator of the risk, right, whoever that underwriting entity is.

And so, you know, our point of view is, that makes a lot of sense, because given the inefficiency, given the fact that these treaties or programs are signed up based on a plan that never gets anywhere close to hit, how can those rangers possibly operate? And so, we believe the world will move to a much more real-time, data-driven kind of bordereau through time. You know, we're still going to see lots of PowerPoint presentations, etc., and meetings on a yacht in Martha's Vineyard, for years to come. But, you know, it's very clear to us the direction the industry is moving. And so, the more we can sit at that interchange and look our customers in the eye and say, "If you're doing this, you will see the financial return on that side of the marketplace," that's a great place for us to be operating as a business. And the operating benefits, you know, saving an underwriter half an hour a week... You know, we have a bit of a phrase around here, which is, "If you save an underwriter half an hour in a week, they're going to eat a sandwich." Right? These are very busy people. And, you know, I think insurers are looking for technology solutions that have a hard cost benefit, right? And the leaders of insurance companies are all confronting these problems in their reinsurance tower right now. And, you know, if we can put ourselves at that intersection, we become a topic of importance, versus, you know, an afterthought. And, you know, we're super happy to be playing in that intersection.

Alex: I think it was a London-based underwriter, they'd have another glass of wine with a half an hour, to be fair. But, you know, the sandwich is a quite slightly nicer phrase. I was thinking about, when you were talking about the way that it's done now, and the PowerPoint presentations, and the, kind of, yachts in Martha's Vineyard, and I wondered if... It's a bit unfair to put you on the spot, but I'm always thinking from a talent lens. And do you think some of this resistance is because we don't yet have the true data-led or technology-literate leaders of these businesses? And that's not to say they're technology-naive, but I'm drawing a big distinction between, you know, knowing what the possible is. Is that some of the resistance to this journey?

Will: Look, I think we can always do better as an industry, right? There are incredible leaders out there today, who are really challenging their teams, who know what they don't know. I have one particular leader in mind. He runs a mid-size regional, still multi-billion dollar insurer out of Iowa. And, you know, he is so forward-thinking, and so focused on data, right? And I think some of that just comes from the fact that he has, you know, kids coming out of university, right? So, I would hate to characterize it that broadly. That being said, you know, there's a lot history can teach us about this. Andrew Ng, who's a very well-known figure in the AI world, has said that AI is the new electricity.

Well, there's another, you know, slightly lesser well-known figure in the AI world, a guy named Eric Brynjolfsson. What he likes to say about electricity, and the industrial revolution in the context of electricity, was, when electricity first came onto the scene, what factories did was they took these huge, massive steam motors that worked in their factories, and they replaced them with these tiny little electric motors, relatively speaking, right? It took an entire generation of new managers to come onto the scene to realize that just putting an electric motor into the same spot where that steam engine... No, no, no. You could completely reconfigure the factory, right? You could get all sorts of additional efficiencies from that.

And so, I think, you know, very basic inventions like electricity, if that analogy Andrew talks about holds true, teach us that, yes, it is going to take a new generation of managers to completely change the business. But there are always going to be those forward-thinking leaders. And, you know, this is just the cycle in which technology is adopted, right? There's always those early adopters. And it'll be quite some time before the laggards kind of catch up to that. But, you know, we know the direction things are going. I think that is quite obvious. And it could take 50 years instead of 10 to get there. That is the pace this industry has historically moved at. But, you know, it's not certain, right? And certainly our job is to help speed that up. And so that's what we're out there to do.

Alex: Yeah. I think it's interesting talking about future-thinking insurers, and, you know, it sort of made me have a wry smile, because, you know, we work in providing talent to the insurtech space, but we work also with traditional carriers on innovation teams, or innovations they're trying to drive, like, you know, algorithmic-driven underwriting teams. And it's very interesting because you get to kind of be a little bit of a bellwether of which companies you consider forward-thinking, really, by the actions of the change in hiring strategy, the different type of people they're hiring. One of the things that I think plays into this space really well for me is that it's that move towards more prominent, more high-profile portfolio and management positions, whether that be kind of alongside other functions, so, it's a...

And also, moving to portfolio underwriting being something that's admired, because we love specialist underwriting, particularly in Lloyd's of London market, you know. And it's super important. You need that expert that's on-hand to look at individual risks, that's in their field of expertise, and they add tremendous value. But the rise of that kind of portfolio underwriter, where you are looking at things in its entirety, we've noticed with great prominence. And this, really, your Federato business, kind of plays into that exactly, and taking a kind of real-life view on the exposure. Have you noticed that, in terms of, kind of, your interaction points? So, I was thinking that, in terms of, kind of, who's most interested in this tool? Who are really your champions within the carriers? And I presume it is different in different businesses. But is there a sort of common entry point that is most interested in your business?

Will: Yeah, look, we are actually seeing that portfolio underwriting title crop up quite a bit. And it's always a good sign for us, right, if someone has created that title and put someone in that role, that's there. You know, what we have found is, it tends to report through sort of a home office-type chief underwriting role anyways. And so, I would argue that role has always been there, through the product teams and through the chief underwriting office. I think the fact that a role is being created means some of what we're onto, and others are onto, sure, as well, is starting to take hold, right? And so, the name may be changing. I think, critically, the ideas haven't, necessarily. But, you know, to me, you talk about that specialist, Lloyd's underwriter, or whatever it is:

“The problem is never with the one underwriter and the decision on the one risk. The problem is always that a trade-off may be made on that risk, right? If you decide to accept a mid-market account that's got 300 buildings and tens of thousands of employees, and a bunch of those buildings happen to be in Northern California and exposed to high wildfire risk, but you love the class code of the workers' comp and the GL. And so, you really want these profitable liability businesses, even though you're taking some property risk. A specialist can look at that account and make that decision in isolation. The problem is never that specialist making that one decision. It's what happens when 20 different specialists make that same decision 20 times. In some ways, what our software becomes is a mechanism of communication.”

– Will Ross, CEO and Co-Founder, Federato

Now, it's not for me to chat to Bob and Andrew and say, "Hey, Bob, Andrew, I just made this exception. You should make it too." No, no, no. That's all mathematically defined in the back end. It sees that I made that decision. It recognizes that trade-off. It sees that I have a max accumulation in California. It sees that I've just added a certain amount of TIV towards that. And it, you know, basically is flagging for those other underwriters, when they go to make that next exception, that next exception, you essentially want to make it slightly harder and slightly harder. There are all sorts of nice UX ways to do this. You can require referrals as you get close to thresholds. That idea, of a dynamic referral, a referral that isn't hard and aligned to a letter of authority, but rather comes up when we're starting to push against a portfolio goal, just to drive awareness, because now a more senior person, maybe the portfolio underwriting department, knows to go look, right?

These aren't novel concepts. They're not super-innovative, in that, like, I think these have intuitively made sense. But a system needs to be in place to actually do them, right? And I think that's what our software really provides. And so, I think this approach tends to really resonate, right? When you can sit down with true underwriting leadership, this is obvious to them. This isn't, like, a controversial idea. There's always trepidation. Don't get me wrong. I think this is an industry that's been tortured by technology. And we can talk about that, but, you know, it's pretty intuitive stuff.

Alex: Yeah. Yeah. I mean, I think you explained it really succinctly there as well, is that you're taking elements of a business that have already been agreed upon, underwriting guidelines. They exist. But you're making them talk to each other, talk to each other across class, talk to each other across the portfolio of business. Because that's the other thing. Underwriting guidelines, we know, are written class-by-class, and they're written by this underwriting leader and this underwriting leader. And there's no actual, kind of... Well, it's not no. That's overstating it. But there's less inter, kind of, class communication, inter-team communication than one would imagine. And we know there haven't... What I wanted to sort of ask you, and this is probably conjecture, really, but how much of this is based on the technology wasn't there to do this. You know, we weren't up to speed. So, is that really, we're just in 2023, and the technology now exists to be able to do this efficiently, effectively? Or is it just been a, we've just been a bit asleep at the wheel for this stuff?

Will: Look, I mean, I think there are elements of this that could have been solved, and in fact have been solved by certain businesses. You know, to name a couple companies we think very highly of, you know, won't name names of whether any of these are our customers, but I look at names like RLI, Selective Insurance, Chubb Workers' Comp specifically, but Chubb as a whole. You know, these are three organizations that have been very well-known for their, as we just said, portfolio underwriting over the years, right. Real consistency of underwriting results, right. Really stable loss ratios, regardless of cat, right? Everyone likes to carve out the CAT losses. Turns out they're still losses now. But, you know, you look at those companies, and they have these sorts of philosophies, and have found ways to do this.

That being said, technology has made it a heck of a lot easier. And that's technology on three different levels, just to be clear. It's not just about the machine learning capability. Most people don't realize that the name Federato actually centers on our federated data graph, which is an underlying, kind of, data aggregation level. What has been really hard for insurers is they often are in transition, from a base technology perspective. So, they might have three policy administration systems, a CRM, a separate document store. They do a lot of work in email, right? The ability to play interconnector between those different systems, and then build an application layer on top of that, we leverage very heavily a set of technologies that really came out of Facebook in the last, you know, 7, 8, 9, 10 years. And so, absolutely, you know, it would've been hard to build on that, other than the last two, three years, because it took that long for that kind of open source ecosystem around that stack to kind of mature.

On the front end, in terms of the user experience, right, how many bad applications have been built slowly? Well, again, like, there has been a lot of progress in how to build data-intensive, data-rich applications, right, that are event-driven, and see all sorts of interaction. We borrow very heavily from an open source project that really came out of LinkedIn, on that end of things, manage and orchestrate a back end, and be able to have a very, frankly intense data experience come across as a very simple and real-time application on the front end. And then in that middle slice of the road, one of the biggest challenges to solving this problem is you're trying to solve that optimization problem under uncertainty. And that is where this last wave of AI innovation has really played a huge role, right?

The application of deep learning, right, inclusive of things like transformers, which was a key innovation in ChatGPT, etc. But really, deep learning as a whole, deep neural networks, has allowed us to basically predict the next-best action under a condition of uncertainty. In other words, I've got a bunch of accounts in front of me. I don't know what accounts are going to come in the door tomorrow. But I'm going to predict what the next best action today is, based on the information I have, using historical context about what might come in tomorrow. And well that is never perfectly optimal, it is so much more optimal than just a first-in, first-out kind of approach, or "what broker is the loudest" kind of approach, which is more what we see. And so, as a result, so, yeah, look, there have been three massive technology innovations that the way we built our technology could not have existed without. But I think it's also fair to say that there's some companies that have done a great job, and have done this sort of approach for years and years and years. Our job is to make sure that the ones who haven't leapfrog to sort of the state of the art, and the ones who have, right, tend to want to continue on that journey with us.

Alex: You got me thinking, when we first spoke and we had this conversation. And when I hear about technology plays like this, and I hear about the kind of ability to portfolio manage, and, you know, I discussed this point of... You could take this view of insurance companies, or carriers, that essentially, they're an investment vehicle, and their method of return is underwriting. Like, that's their play on that money. And, you know, using tools like this, portfolio-managed, then you could purely see it as a fund that's grown by this method, and then take away lots of the, kind of, like, distribution that we typically see. And that got us into a conversation about Embedded. What was interesting is that I sort of said, "Oh, Embedded, it's just a distribution play." And you said it wasn't. I thought that was a really interesting point that you made. So, convince me, Will. Why isn't it just a distribution play?

Will: Yeah. And I want to be clear. There are massive distribution benefits to Embedded Insurance. And I think those are obvious to people. The question is, what is the number one problem the industry is actually facing right now? That's new, right? I think this capacity crunch and the lack of return at the reinsurance level, and how that's trickling down, is it. And you think about what we talked about, this idea of real-time bordereaus, data connectivity, etc. Another way of saying that is, it's extraordinarily hard as a reinsurer in today's world, right, or just someone sort of sitting at, maybe you're sitting excess of someone else's risk, whatever is meant by that. It's extraordinarily hard to truly know what exposure you're underwriting to, right? If you're underwriting to an aggregated exposure, you are relying on the continued underwriting in good faith, aligned to those guidelines of your treaty partner, right? If you're writing Excess to someone, you are relying on the fact that, you know, those guidelines are followed, and that you're getting accurate information from the primary about what the exposure they underwrote is in the first place.

What Embedded does is it creates a lot of certainty around data, that has to do with the exposure, right? If you think about Embedded Insurance as, you are kind of putting that insurance purchase at the place of sale, right where the SKU number, and the price paid, and the date that that product shipped, etc. exists, you have a much higher confidence in what the exposure you're underwriting to is, right? And you're doing so on a kind of unit-by-unit basis. And so, I really do believe that, well, the distribution is attractive to people. I think it's the precision of that distribution that is ultimately attractive, right? Distribution without precision is useless. Growth is easy in insurance. Efficient growth is extremely hard. Anyone can sell a $50 barrel of oil for $20, right? You can always out-compete on price. And I laugh. So many of our customers will come to me and things they'll see in our system are, "Wow, I'm growing like a weed in this class code." Is that a good thing? You know? That's the question.

We either are killing it, or we are behind the market. And we don't know which it is. And that's the beauty of Embedded is, you really have visibility into the risk you're getting, in a very, very real way. Usually that product is being originated in a digital setting, so that data is also sort of available via API, and connected through. And so, all these things that we talk about in terms of bordereau, connectivity, etc., I think they hold really true in Embedded. And I really do believe that that has been a large part of the attraction to the capacity that goes behind those sorts of offerings. Distribution, awesome, right? But no one's going to look for a distribution play if it doesn't give them some sort of selection advantage, because there's always a chance that they grow like crazy into a horrible book of business. And no one's looking to do that. So, yeah. I do believe it's both sides of the coin. It always is in this industry.

Alex: Yeah. It made me think of when people talk about raising money. And they talk about, you know, smart money and dumb money. And you always want smart money, because there's a value-add to that money, and it's, you know, distribution, as you say, is great. But, you know, there are lots of people that I'm aware of that write really big books of business, but really bad books of business. So, it's like, yeah, you can write a great... You can make volume, but profit? And we all know what we're really looking for. I'm kind of conscious of time as well, so I'll kind of start kind of bringing this to a close. You know, you've obviously got skills that are kind of outside of the industry. You've obviously got good awareness of the industry, but as you're growing in insurtech, this is kind of from a team perspective, how much did you fill the need for in-house insurance knowledge? Like, how much was that kind of part of growing that team out? Because I'm always kind of interested in tech-driven businesses, because some people take the view of, "Well, we're smart. We'll work it out. It's fine." Others go kind of insurance-heavy. How much did that kind of play as you were building your team?

Will: Yeah. Look, I think it's always been a balance for us. If you look at the co-founders, we are kind of first-principles technologists, through and through. That being said, our COO, right, so, you know, our peer in running this business, is a woman named Megan Bock Zarnoch. And Megan came with 25 years of underwriting expertise. Simultaneously, you know, the reason we met Megan was we were out there doing user interviews. And we actually met Megan doing a user interview, trying to understand the industry. And so, you know, I think there's two sides to this. One is you absolutely, in our business, want to have some level of that knowledge in-house. And then two, you have to know what you don't know, right? And you have to have a real mindset, and this is so important for any entrepreneur, of "pursue the truth."

You know, in some ways, some of the earliest ideas for Federato came out of a time when I was spending time working at a venture capital firm called Venrock. And there's a guy named Ethan Batraski, who hosts a great podcast. And Ethan said this to me: “You know, entrepreneurship is all about this idea of pursuing the truth." And I think the reality is that there's a lot of entrepreneurs out there that are willing to lie to themselves.

“If you're going to go after this space, and try and solve a problem for underwriters, you better understand what the problem actually is, and you better spend the time with them.”

– Will Ross, CEO and Co-Founder, Federato

So, you know, back to your question, we've always had that underwriting knowledge. You know, it was critical to developing our product. And then, I think probably the biggest area where we've continued to hire underwriters is in sales: about half our sales team has some sort of insurance-specific background.

Now, I don't mean they sold software for Guidewire. I mean, they were a broker, and grew up in a producer household their whole life, right? They're an actuary, right, with full credentials, on our sales team, right? They're an underwriter, by training. Same thing on the customer success side, right? What that allows us to do, right, is have that conversation of trust, in a language that is familiar to our customers. And critically, those people, as part of our company, can play translator, to make sure that technology gets implemented correctly. I think the biggest frustration, for a lot of underwriting organizations, is that their technology partners don't get it. And so they find themselves explaining things two, three, four times. And we're not perfect, right? I think we're considerably above average in the level of service we're able to provide, because we have not just a product that was based on that knowledge, which gives us a great starting point, but kind of this ongoing feedback loop, that we're able to sort of use to take what can sometimes be articulated as a vague idea in three minutes right at the end of a call, and almost nail it the first time, because we know exactly what they're talking about. We kind of get what they're getting at.

So, yeah. We're huge advocates of it. You know, we do not typically look to insurance companies to hire our talent in front-end engineering, right? We get our talent in front-end engineering from the best front-end engineering training grounds we can find, right? I mentioned we leverage technologies from companies like Facebook, right, open source technologies, but largely built by Facebook. You know, we went and got several of our front-end engineers from those companies. You know, that's what you have to do. You always want the best people, with the best training. And you should always be willing to pay a premium for them, right? And that's kind of been our approach to talent, is fewer people, pay the premium, and get the best people in their discipline, right, the true first-principles experts. And then it's kind of no, you go, amigo, right? Once you're here, know what you know really well, and know what you don't know, and work with a team to figure it out.

Alex: I'm gonna clip that and send that to all my clients, Will. Hire people, pay a premium for the best people. No, no, it's, honestly, it's really refreshing to hear, and I think you're absolutely right. And particularly in engineering. And engineering is so... You know, engineering's a large part of what we do. My colleague, Gavin, heads that up for us. And it's fascinating how many people say, "All these people must come from an insurance background." And the question we always ask is, "Why?" You know, when you're talking about engineering, "Why?" I'm not saying that the subject knowledge is not important, but engineers need to know their engineering. And then you need that subject matter expert in the room.

But I think what you've done, which is so smart, is you brought it in at the right level as well, because, you know, seniority matters. You need to say that, you know, a 25-year veteran of the insurance industry is at our core, and your COO, and then you can filter it down. The amount of times that we've worked with businesses that go, "Oh, we've got a head of insurance." And then you look at the business, and it's like, there is one person from the insurance industry. And that person may have come from... And as we know, the insurance industry is very specific. So, say you work in claims, or underwriting, an actuarial, and you don't really cross over to others. And then any question about insurance is, you know, for this poor person to deal with.

Will: And to be clear, like, as an example, our VP of Engineering, Tim Collins, is the original co-founder and CTO of MetroMile, right? He has that type of insurance experience. Our VP of Product, Verlyn Fischer, spent his whole career in vertical SaaS. We actually worked together previously, but his last job before joining us was Acrisure, right? So, we really do believe that the best talent, right, probably has multiple dimensions to them, and knows what best-of-breed software looks like, but may come with some insurance context. But your run-of-the-mill, sort of average front-end developer, right? You're gonna have a much better time, sort of, finding the people who can help them write really specific requirements given the inputs coming from your insurance customers, right? And then let them be a very efficient software developer, a very efficient coder, who can implement what is very explicitly outlined for them in a clear and succinct way, with an eye to the future of how does this become scalable? How is this reusable? How is this configurable? You know, it's all a balance, right? I don't mean to suggest it's bifurcated. But, you know, we think it is possible. You know, a lot of that comes back to culture, right? You have to be a place people actually want to work. And, you know, we're very proud of the culture we've created. But, yeah. It's both sides of the coin, always.

Alex: Yeah. Yeah, businesses are lost in one culture. I'm a big believer in that. The last question, because, you know, you raised a series B, and, well, didn't even have to go out for it, and you got your internal raise, and that's great news. But it was a pretty significant raise, and I was kind of just intrigued about what the next 12 months looks like? Is it territory growth? Is it kind of, like, more development of the product, or everything above, presumably?

Will: Yeah. You know, I'm gonna be really honest. We run our business differently. For us, it's about focused growth, sort of like our underwriting colleagues, not just growth. You know, we were very fortunate. Our inside investors saw our Q1 board deck, and basically said, "We don't want this going out to market. We know how sweet this is, how well this is growing, how much this is resonating." They talk to our customers. They've met our customers at some of our offsites. We actually bring our customers and our board together. We believe in that kind of level of transparency. And everyone was just so psyched that what we were doing and the resonance we had, that it was obvious to them, we need to just stay involved and make sure that we're getting ahead of this, and the founders kind of keep their eye on the ball.

Our bigger focus in the next 12 months, just being honest, is about growing at a certain clip, with the right customers, right? We are turning business away, right? Some of that is on price, right? We believe we are a premium product. We have charged a premium historically. And, you know, this is an industry that has revolved around discounts. You know, there aren't a lot of procurement teams used to software companies saying "no" to them, right, in this industry. And, you know, we're very willing to say "no," to sort of preserve what we're doing, and because the long-term goal we have is we want to be an enduring company, right? We have investors who want us to be an enduring company. They all have longer-than-average fund lives. They all believe in building, kind of, for long-term success. And so, you know, the biggest focus we have right now is on, we like to say, "Growth that doesn't cause us to lose our identity."

And since that identity is as a product company, you know, it's the continued hardening and productization that allows us to then, looking forward to 2025, 2026, grow more and grow more and grow more as those people come back around, those people who we may have actually said "no" to, for a variety of reasons, right? And to be able to handle, kind of, that additional capacity. So, it's a privileged position to be in. Don't get me wrong. And I hope we can always stay there, but, you know, it's not a grow-at-all-costs mentality at Federato. That is just not how we operate. I think it's serving us well. Like I said, we're fortunate to have a board that thinks that way. But, you know, the focus becomes putting the right people in place, to deliver the right product, to continue productizing and hardening every last feature, and building things the right way.

And then, yeah, look, we have growth targets, but those growth targets are something we're trying to manage very precisely, right? We are underwriting our customers, in many ways, because we don't charge for services, right? Like, literally, if we take on a customer, and they have a set of requirements that's not in our core product, and we have to go build something truly custom for them, we do a lot of configuration of our product, but something truly custom, that is not a good use of our time if there's another customer who fits more precisely in that bracket, right? And through time, we add features, and we can then handle that customer. We can come back to them, etc. But, you know, that's been the approach. So, that is the approach, that will be the approach, and, you know, we're super happy with the level of growth we can achieve within that.

Alex: Awesome. Will, it's always nice to talk to a company doing well, and it's a really interesting area that you're in. And yeah, so, it just resonates so much with some of the work that we're seeing from our side of things. And, you know, thank you once again for being so generous with your time, and I've really enjoyed this conversation, and thanks for being on "The Leadership in Insurance Podcast."

Will: Yeah, no, thank you, Alex. I really appreciated the time.

Alex: Thank you. 


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