Speaker 1: 0:19

Hello everyone. Welcome to another episode of Ensure. Take Unscripted. Alisa Favi, your host. I'm super excited today about having TX-YO, the general partner at FICO Ventures, today with me. He's someone who's been involved with insurance for a while, who is a McKinsey involved with their insurance practice, and he's been investing in insurance for a while. I mean he invested in companies like Policy Genius who, as you know, are one of some of the OGs in the insurance space. So he brings a lot of unique perspective into the podcast with a lot of learnings that obviously happened over the past few years. So let me start off with TX. Welcome to the podcast. Maybe you could tell us more about your background and where your interests are coming from.

Speaker 2: 1:00

Thanks for having me, ali. It's such a pleasure to be here today. So just very quickly, on my background, I was an entrepreneur till in BC so started a very small bootstrap company. We're selling college textbooks online, of all things. So this was right out of college. We were very fortunate, ended up selling the company in 2006. And at that point I realized maybe I was a good entrepreneur but didn't have the right distance experience to scale a company. So spent a couple of years at McKinsey and was very fortunate to be part of their insurance practice. So worked with a lot of clients like City Prudential, aig and through that experience kind of informed how I wanted to invest my time when I became a VC later on. And insurance tech has definitely been a constant focus within our portfolio since day one. So we've been investing in insurance tech company since 2013. It's about 10 years now.

Speaker 1: 1:49

Very interesting. So let me start off with someone who's been in insure tech since 2013. How do you see the evolution of insure tech? Because I got involved in insure tech beginning of 2016. And I have a lot of thoughts about how insurance is going to make for 2016 to 2020, like 19 to 2022. And even now, like if it's the second wave or the third wave or whatever. But you've been in it much longer, right? So how do you see the phases in insure tech for insurance evolution?

Speaker 2: 2:19

Yeah, I think the first wave back in 2013 was similar to other financial product categories. I think we're just getting people comfortable with transacting and buying insurance online. I think insurance traditionally as you know, the average broker today is still 60 years old kind of meets a due in person. So it's very uncommon and maybe not intuitive for people to be able to self-select the insurance policy. So that education process and discovery was invicting in kind of the 1.0 of insure tech. So that was probably 2013, all the way to 2017. And I think after 2017, consumers got more sophisticated, right. So the second wave it goes beyond discovery to price comparison and finding what's the best policy for them. So I think that's the second wave between 2017 and 2021.

Speaker 2: 3:05

And now I think, with this market correction as a whole within tech, I love the new focus on profitability and strong unit economics. So I think we can dive into this a bit later, ali. But a lot of people are realizing that single line insurance products are very difficult to scale, that the unit economics might be pretty hard. That's why a lot of the traditional carriers MGA always have multi-line products that they sell. So a lot of the innovation, at least in the last couple of years is around kind of product fumbling, thinking about better targeting across different financial products. So how can you bundle maybe, a mortgage product together with insurance, together with, maybe, trust and will? So I think a lot of the innovation now happens in being able to use data and provide each individual the exact suite of financial products that they want, and insurance obviously serves as a very big category within the suite of products.

Speaker 1: 4:01

Very interesting. So maybe we'll just jump into my favorite question always, which is what's one or two of your most controversial opinions or ideas about insurance, something that you feel like it's different than how the majority see insurance?

Speaker 2: 4:18

Yeah, I actually think we need to go back and empower these offline brokers. I think, instead of competing with them, I think we should empower them. I think what we see now is a lot of these relationships with offline brokers are still very persistent, especially the older demographic, and insurance is a lot about trust. It's one of these core products that a lot of people want dedicated advice. So, instead of competing with them, we've actually invested in certain platforms, like a company called Fair Street that helps Medicare agents kind of improve how they operate, and so we're not competing with them. We're not creating a new avenue for carers to sell products. We're actually empowering or supercharging the existing channel. So that to me is like a very interesting category and we want to do more investments in similar spaces.

Speaker 1: 5:07

So I wonder, because I think about this all the time when I was thinking about Kovu, as you spoke about this briefly but I'm very passionate about the distribution space because I believe transformation of insurance starts with transforming distribution and how do we advise people, guide them, educate them to make the correct decisions? That's, at least to me, like the right way to start with distribution, transformation of insurance. But when I think about distribution channels, there's a huge controversy around embedded versus brokerage model, or you know, between, I Would say, the hottest topics. Now I know you were talking a little bit more about how insurance gets involved and idea of bundling with like financial products and all that which sounds more like embedded and to me that's a little bit different than like empowering workers. So how do you see, how do you like navigate this? Like the difference between like, is insurance going to be more focused on bundling or is it going to be more focused on like, empowering the traditional agency channel, on evolving them?

Speaker 2: 6:12

Yeah, I think it's a bit of everything. Maybe maybe I'll break it down to three different parts. I think embedded it's very interesting and maybe a controversial view I have is that everyone wants to be an embedded insurance company, like wet-cell insurance, but I don't think a lot of companies have the right data right. So, ultimately, if you want to become an embedded insurance company where you can actually capture value, if you're willing to underwrite some of the risk yourself, I think if you're just going to distribute these policies, you're no better than an affiliate model. So that's something that has been tried and tested in the past. I think if you look at companies, for example, maybe I'll name a company called hint AI, so Tim dot AI works in marketplaces like rental car marketplaces, like two row, but there's actually a lot of data that they're collecting about Individual drivers and their driving records and experience and they I think that's a unique advantage for beyond Kind of what the insurance carriers publicly see you have a lot of granular data that will inform you of how to better price the policy. So in that case, I think it's very interesting for an embedded insurance play. Where's in others cases where the data might be more sparse, so you're like a middleman transactor where you actually don't capture a granular level transaction data, then that that case, I think there's less of a wedge and or there's a less of a long term mode for you to be able to better price risk within that. So that's the embedded category. I think that's pretty interesting.

Speaker 2: 7:37

I think the the other one that's pretty interesting, as we talked about, being Empowering existing Brokers, existing channels. I think there are two categories. I break them down. One is like a pure play let's provide more SAS tooling to these existing channels. The other is like a lot more distribution. We recently invested in a company called outmarket that helps a lot of carriers identify good distribution partners. So they identify Brokers that the carrier currently doesn't work with. Our MGS. There are wholesalers that the carrier doesn't work with today but could be very strategic given the carriers footprint or the carriers intent to expand their coverage in certain regions. So I think this model of like a AI co-pilot is becoming very interesting when you think about Empowering people with an ecosystem very interesting.

Speaker 1: 8:26

So let's just flash forward to, like, let's say, 20 years from now. I know it's a little bit of a stretch, but I just wonder, like, how do you see the future? Do you just distribution wise? Do you see it as a market in 20 years that is more dominated by, I don't know like AI enabled brokers, or like a model where insurance is taking a bat's backseat of all these big commercial brands? Then is more just bundled into distribution. I don't know you buy your car insurance from Toyota versus you know like your broker.

Speaker 2: 8:56

I really hope that. I think, with the wealth of data and the cost of creating these AI systems going down a lot, that I think the Analogy you gave about hey, you buy your Toyota and then, yeah, I presented if you're your car insurance and then I get your physical address because I'm taking down your driver's license and your details and I can offer your policy because now I capture data about Kind of where you live and kind of what you do for a living and kind of your lifestyle trend, so I think all of that is going to be the future. I don't think that's something we get to in the next three to five years. It's probably gonna be 15 to 20.

Speaker 2: 9:29

The other thing which I think it's going to be interesting is that, given a lot of the, the insurance education can be automated, that you can embed insurance within other financial products. So, instead of just a car dealership, you walk in the bank, you open a bank account Maybe it could be online now an online account and at the same time, get asked you a few questions that can prompt you to buy insurance as Well. So I think we see the bundling of products not just with non financial players, but also with other financial products.

Speaker 1: 10:00

So I'll tell you my thesis and I want you to basically correct me and say, like Ali Sure, I've thought about this quite a bit and there's two versions of the features that I could see. One version is that you have someone who's your risk advisor that understands the risk you're responsible for and tells you how to predict your downside. And the other one is that the one that you mentioned, which is you buy a car and then the car manufacturer says I don't know. Let's say, if I mean if you have a total of cars, then you're not driving, so it's not your liability or risk. Is the cars liable to you and risk? In that case they should provide insurance, not you. But if it's your risk, then I guess the risk advisor makes more sense to me then. So I mean, we always talk about the idea of bundling, but I wonder why shouldn't idea bundling come from this angle, which is like a holistic risk advisor, as opposed to bundling life insurance with mortgage or bundling I don't like auto with the car manufacturer?

Speaker 2: 11:02

Yeah, I love it. I like the idea of a holistic kind of risk advisor to help you with like your entire life and you're like everything else. I do think that the one thing has to change and maybe this is not just insurance but other financial products that everyone's incentive buys to get you to buy more financial products. So how do you take that away? I think if a financial advisor sells you more insurance, you take a higher level of coverage. They ultimately make more commissions. So as we think about the risk model, like I think we need to change kind of the commission structures or how we think about compensating people with distribute insurance so that the end consumer gets what's right for them, not what's most expensive for them.

Speaker 1: 11:44

So we build an AI risk advisor, because that was my original thesis and the idea was a holistic, unbiased and transparent advisor. The idea that I have had, at least as it, was that it's supposed to be algorithmic. So if it's algorithmic and he doesn't have a human intervention and it's kind of like open source, so you know, like what is recommended to what, that should solve the issue. Because the combination that I like the most was that the AI generates advice and then the human does the hand holding for explaining it, because the explanation I don't think AI I don't know AI should be there eventually, but people still want that trust and human touch and human hand holding when it comes to like these kind of complex products which I think might be able to solve that, to kind of provide some of that transparency and some of that unbiased incentive into the mix.

Speaker 2: 12:31

Yeah, I think that's super interesting. Maybe one kind of early innovation of the space is that we found that some of these early shopping tools for insurance have taken off, like platforms like SaveBot. I think what's interesting is that I feel the incentives there are more aligned with the consumer. So I like it that you're running an algorithmic model in this case, where you take away the biases and you're recommending what's best for the customer. So I think maybe there's a happy medium or a compromise that we can strike right because a pure shopping tool again, you don't want to just get the cheapest insurance policy. You want what's best for you, but you also don't want to like over commit the policies that you don't need. So I think something in between is kind of what you're building is definitely going to be the future for how people should be thinking about insurance.

Speaker 1: 13:18

Yeah, and, of course, the biggest issue here is that people's relationship with risk is very complicated. I think people are wired to buy certain policies, which is auto, home and life, maybe to some extent, and they're not wired to buy other policies like disability insurance or all this stuff that they're not used to buying. And convincing them to buy something that they're not generally wired to buy it's a very weird dynamic because it's not a logical discussion. It's like when I tell someone that you have a 25% chance of having some sort of disability in your life, they're like okay, so there's a 75% chance, nothing's going to happen to me, and that's like how a lot of people treat it versus yeah, but that's like the whole point of insurance is like we're talking about, like low frequency, high servers, the items, and that's what insurance is for. So I think that was the biggest challenge we ran into and that's why I thought like the human advisors still need it to kind of massage everything on top of like unbiased recommendation from an intelligent system.

Speaker 2: 14:13

Yeah, I think the other thing, too, that will be interesting is that I think there'll be more product innovation on the insurance side. I think. One example, ali, I know you and I have had offline conversations about this, but I think the whole topic of insurance for AI, I think it's going to be very interesting. I think a lot of people are talking about AI for insurance, but I think the opposite is very interesting If you think about certain categories. If I'm a medical practitioner, now I'm relying on AI to meet memo grams for me. Or if I'm a lawyer and using AI to drop drop letters for me to some of my clients. What if there's a mistake, though? Is this covered by my general liability policy, or do I need something additional in AI? So I think this is a very interesting product innovation that will need to exist, at least in the coming years.

Speaker 1: 15:05

So I know tech ENO has existed, which is basically right, is like you develop a tech and you're covering its errors and emissions. I think this is just a more complicated tech ENO and the question is Because the insurance companies who write tech and you are writing these tech and those and I don't think they have the money models to do a better job with writing it. So the biggest losers in the space are like when insurance companies write this and then realize shit like that's like a lot of you know. So I think the so from a customer lens, I feel like the products are out there as tech you know from an insurance company lens, I feel like they need to just be adapting much quicker now with all these new systems.

Speaker 1: 15:46

To give you an example, like RAI, we have shown that it could pass the licensing test, like 5% accuracy or whatever, and we haven't even spent a lot of time on it, like to improve it. So for me, I asked the question from a few commissioners and like the regulatory space and insurance is like look, this is as good as like a licensed agent, like so what? Like can we start using it like a licensed agent or how would that work? And obviously, I don't think the world is equipped to be able to answer these kind of questions and I feel like there's going to be more regulations coming into it, there's going to be more learnings, but I think the foundation is for sure there, but it should be super exciting what comes out.

Speaker 2: 16:25

I think it's a lot of insurance companies, especially the larger ones, think about where they want to spend money on future development.

Speaker 2: 16:33

I think one huge benefit with AI is, I hope, that a lot of the RPEX costs whether it's like customer service, whether it's billing all of that should be streamlined away and a lot of the focus should be on future product innovation or really like understanding.

Speaker 2: 16:47

Like hey, how do we actually tailor our policies to each individual? Maybe the other, the other pipe dream I have is that even though everyone tells you now you get a personalized quote for insurance, you're still bucket that into a few categories. They're placing you, they're checking a few boxes, or you're within this certain age group 40 to 55, you live in these cities or zip codes and will give you the policy. But it's not down to the individual level and sometimes I think insurance companies also don't have a holistic view of like. I think the whole idea of a risk advisor is pretty interesting, like if you're covered with maybe some of your company policies, maybe your personal insurance policy doesn't need to be that high. So I think this understanding or common database that's shared across all insurance companies but at the same time remains anonymous, might be super helpful in helping the end consumer get better price policies.

Speaker 1: 17:39

Makes sense. So let me ask you this what do you think investors got wrong over the past few years? And then I'm just saying, like, where I'm trying to go with this conversation is after it's going to be like what do you think investors are getting drawn now? And then I'm going to ask you about what insurance companies are getting wrong. So let's start with what investors and insurance companies to some extent, have got wrong before.

Speaker 2: 18:04

Yeah, I can get overestimated the lifetime value of each customer and the number of additional products they could upsell to each consumer.

Speaker 2: 18:11

I think there was a lot of confidence maybe some cases blind confidence that here we start with one product, we can upsell you three other products and a lot of the VC dollars that flowed into the space and again we are guilty as charged to get people we've done the same thing that a lot of the assumptions you're making on how profitable each business could be were based on these assumptions that don't hold.

Speaker 2: 18:32

So I think the other assumption was that customer acquisition costs for these people would hold constant at scale, which is not true. I think insurance is just like every other financial services both the go, where at once you get to a certain amount of scale, the cost of acquisition actually increases a lot, so that you need that buffer from day one in order for you to find a viable product and scale. So that's what I think both carriers as well as insure texts as well as VCs have gotten wrong over the last couple of years, and a lot of it, I think, wasn't uncovered till we had the market correction, where people started to pay attention hey, there's no more free $50 million lying around for your next round. Like we really need to focus on margins instead of just focusing on popline revenue growth. So before that was just popline revenue growth at every expense right, which is not the case anymore.

Speaker 1: 19:22

Let me ask you this do you feel like these models, the market? Because, like, I'm not going to mention any names, but a lot of people said like these market corrections. It was more about like the like, just the price multiples. But the question is that do you feel these companies can save themselves or do you feel like they're fundamentally flawed businesses?

Speaker 2: 19:43

I think a lot of them are fundamentally challenged businesses as standalone entities, so I think they would need to merge with another entity to get to that exponential scale, and scale not just in terms of revenues but back office footprint, for example. If you combine two of these companies, we could combine operations where you could streamline probably 50% of the cost. So I think in order for some of these players to succeed, we would need to see drastic consolidation in this market, which hasn't happened yet, but I'm predicting that it will in the next one or two years.

Speaker 1: 20:19

When you say these players we're all talking about, like you still MBA slash carriers right, like that's the right. Yes, yes, that's right. So is consolidation between them and other new stock carriers, or is it going to be more between them? And I don't know like traditional carriers.

Speaker 2: 20:35

Yeah, it could be traditional carriers too, I think. If there's a very complementary footprint say they have a strong hole in certain product lines, then I could see kind of that. I see vertical integration being very helpful, but I think horizontal integration, which is what we were talking about initially, I think that it's also a very viable path in order to create kind of a much bigger company.

Speaker 1: 21:00

Makes sense. And what do you think people are still getting wrong now versus before.

Speaker 2: 21:07

I think where what people are still getting wrong is that a lot of investors are still funding single line insurance products and I just don't think that single line insurance products scale very well.

Speaker 2: 21:20

I think these are likely going to be. You're going to tap out at, I would say, like 50 million in revenues and then finding that kind of second chapter in your playbook is going to be extremely difficult. So I think I think, from day one, a lot of people are still not focused on the right business models, are not thinking about hey, instead of building one single product, how can I build a suite of products that would serve the end customer? So I think where they get things wrong is they, instead of being customer led in their product discovery, they're just being led by a single line of product. I think you really need to think about the customer demographic you're serving from day one and understand like, hey, what else can I sell this specific customer? I think that's a more interesting question to answer, but a lot of insured tech companies in the seed stage are still not focused on that.

Speaker 1: 22:09

The challenge that I see with that is that I just feel like the model of selling multiple products at the same time in the online channel doesn't work, and even from an embedded model doesn't work.

Speaker 2: 22:26

I mean look to chat more though what examples you've seen that happened, Because I think we actually think the opposite with some of these examples. We think would actually get skilled.

Speaker 1: 22:39

I mean I spend a lot of time with customers trying to understand how they work. I mean I have customers in different categories, but one category is of people who buy online. Let's talk about three different channels. One is B2C. Imagine someone like Branch who does home on auto together.

Speaker 1: 22:56

I don't know if I'm a big fan of a direct B2C play to go to someone and say, day one, bundle your home on auto with me directly. I just feel like the person who's shopping online typically is looking for one policy and then try to sell them to multiple things at the same time. It's that much harder. It's from a high-intend customer that you'll find online. If I'm talking about a bank customer or, let's say, a financial product like 8 points or something, I'm trying to sell them home.

Speaker 1: 23:27

Again, these are hard conversions as they are for single line and high-intention. And convert them in multiple policies at the same time is even harder. And if you just sell them on one policy, trying to bundle a few other things after is also very hard, because most of these customers you have very low engagement with and there's not much. That's one of the reasons I got into the agency space anyway, because it felt like in the agency space. The renewals are really where we want to go after people for bundling, because you basically bring them in on a single line and then you have that relationship with them that is engaged, and you have that personal relationship with them as opposed to like a Acorns relationship or banking relationship or something, and that's what you use to cross sell. At least that's my thesis. I don't know if I'm getting it right or wrong, but that's how.

Speaker 2: 24:11

I do it. I definitely can see your angle. I think what I mean maybe to piggyback on the example, like maybe auto and home, it's not maybe naturally like a complimentary product, unless you bring in maybe a third product like an umbrella product, and you can say like if you get these two from us, your umbrella premium goes down. So I think, instead of selling them three policies at once, I think there's a short-term opportunity to resell policies, so getting them to go up out of the current policy and pick something else in the short term. And the other thing that's challenge about selling multiple products is the underwriting timelines are not consistent. So maybe that beckons another challenge we have in today's insurance industry.

Speaker 2: 24:54

So I think, if you think about life insurance, it's so archaic that a lot of it still requires us getting a blood test and everything. Well, if you think about it like, okay, most of us have gone for medical checkup within the last one or two years, right. So I think we can rely on the data and I think a lot of us subscribe to online platforms, like one medical, for an example. So I guess why isn't there more of a data integration between this? Why can't get an instant policy? So I think a lot of the challenges is also the data and switch right. You come back with a very low premium number and then two weeks later they come up with certain exclusions, so like, okay, I can do this. I think being upfront at the start and getting pricing right and underwriting periods shorter is going to be like the winning formula, but I don't really think we've cracked the code yet.

Speaker 1: 25:37

Yeah, and why do you think investors are still finding single line insurance products Like is there, like they haven't learned the lesson or they're betting on a certain thing. That? What are they betting on?

Speaker 2: 25:49

Like insurance, is such a such a big category. So a lot of people think that the TAM, even with single line products, is big enough. So I think a lot of them are focused on the TAM. And I think the second thing is they're focused on people who have that experience in the space as corporate executives and like, hey, we know the space inside out, we have all the right relationships, you're going to get the right distribution channels, but fundamentally, are you building a business that works? So I think, as they think about supply, they love investing in people who have all the right relationships to all the carriers and MGS. But I think that's still that consumer acquisition fly we also talked about is something that is still very hard to fix.

Speaker 1: 26:29

And another thing that I wonder about is that before, when you think about root or lemonade, people were basically giving SaaS multiples on premium. They counted premium like revenue and like a 90 SaaS multiple on like the low margin, unprofitable premium. I just saw the announcement from Kin insurance that they are unicorn now and I wonder what are the multiples now for like a single line in J or carriers? It goes before.

Speaker 2: 27:04

Yeah, it's much, much lower. So maybe a lot of the background is that these first batch of companies like Ruth Eliminate, as you mentioned, these were, like, I think, the first in 10, 20 years of a new insurance company coming on the public market. So a lot of, I think, less informed public market investors this is like the retail crowd they didn't really understand the difference between premiums and regular SaaS multiples. So I think revenues is like a small fraction of premiums that everyone finally understood. So I think, as you look at the newer companies, a lot of these new companies are going to be bay-valued off kind of net revenue multiples, which is then going to be more consistent with SaaS multiples. But if you look at like top-line kind of revenue multiples, I can't see anyone trading for more than like three, four, x kind of premiums, which is which is sounds crazy, which is still very high in my opinion. But I think everything is going to be focused back on like bottom-line revenue numbers.

Speaker 1: 28:02

Yeah, but even the bottom-line revenue number is not a SaaS margin business. It's still like you know. You have a huge customer service and all that kind of stuff. So I would assume they're still running at 30, 40% margin and if they carry any risk, they have like huge unprofitability issues now with sorry. So it's still interesting, but I mean, can being insured to unicorn? I mean props to them in this market in that category. I think I was here that news, but let's see, I wonder what, like what are the multiples on them? So you spoke a little bit about like areas of insuring that you're excited about. One of them was the idea of ensuring AI, which is a very new trend. Anything else that you're super excited about these days.

Speaker 2: 28:44

I think we're very excited again. We, I think for the last, I would say the last five years a lot of people have focused on more consumer innovation within insurance. I think we are now more excited about helping a lot of the existing players large wholesalers and carriers fix their back office operations, which is something very interesting, I think. One big innovation again not to kind of go back to AI again, but I think in the past we were only able to leverage our PA technology, so a lot of the innovation was with regards to like okay, we can ingest data faster and process data faster. So we can ingest a PDF form and, okay, spit out the data into a database. But now I think we call it smart processing or smart contextualization. But not only can you capture the data, the data can be used to inform other decisions, and this is only kind of made possible more recently with AI.

Speaker 2: 29:37

So a lot of this information that we're pretty excited about, like the example I told you, we invested in this company called Outmarket. That's a, it's a co-pilot for a lot of carriers and wholesalers to improve their distribution reach by finding existing brokers that could actually help them and could be additive to their current portfolio. So I think that's going to be pretty interesting. So the areas of focus was a lot, I would say, like, back office, a lot of distribution automation, a lot of customer service automation, a lot of receivables automation. That's all pretty interesting to us today.

Speaker 1: 30:12

And what are some of the trends that you feel like now have a huge impact on insurance just outside of the insurance space that people should be aware of? Do you expect like a big impact on insurance or insurance?

Speaker 2: 30:26

Yeah, I think. I think a lot of the trends in that are happening more on the macro level are going to make an impact on insurance as well. Right, I think if you think about the cost of capital for all businesses, it's gone up a lot. So I think, as you think about the whole underwriting and the MGA model, I think kind of people who are sitting in the wrong part of the stack are going to get compressed as well. I think the other thing that's going to affect the insurance industry a lot too is, just now that there's more data about understanding premiums, a lot of the carriers are quickly finding unprofitable markets.

Speaker 2: 31:02

I mean, I'm sure you know this, but State Farm kind of moved out of California as well for their home insurance. They're realizing like, okay, all these policies that we underwrote, now we have data on it, they're like gee, not that profitable, especially with all the fire risks that now we can predict. I think before that a lot of the wildfire risk was not really factored into these models. I think with the data a lot of the carriers are getting a lot smarter. So I think there's going to be kind of, I would say, a more variation in pricing which is going to affect the insurance industry. We're not going to see a homogeneous kind of like set up for most of these product lines. We're going to see very big variability and I think a lot of underlying kind of risk takers within the space people underwriting the risk are going to ask more questions for them to price the policies. So I think that's going to be the evolution of insurance.

Speaker 1: 31:51

And who do you think are going to be the biggest winners in this? When do you think about the future of insurance and all these trends and changes and so on?

Speaker 2: 32:00

We're going to be the biggest winners, I think, people who could get the scale, and I know it's a cop out, but I really like the rollout model and the insurance. I think that's very, very interesting. So I think that there's a group called XPT Insurance which is out in New York. So they've been buying a lot of specialty wholesalers and this is more traditional kind of offline, but they've done extremely well. I think what you realize is that the back office operations and the distributions are very similar across different types of businesses but none of them have ever got the scale because insurance is still a very outside of the top kind of few carriers, wholesalers and MTAs still a very, very fragmented market. So I think this whole strategy of a rollout play in insurance it's going to be a very interesting one.

Speaker 1: 32:44

Very cool. That's it for most of my questions. I'm going to ask about the trends and so on. I don't know if you have anything else that you want to share or add that we haven't covered.

Speaker 2: 32:57

No, this is super fun, ali. I had a lot of fun chatting about insurance and I know a lot of different trends have happened over the last two years, but still very excited about the future of insurance.

Speaker 1: 33:07

Perfect, no well. So thank you so much for sharing all your insights and thank you everyone for listening TX. It was great having you on the podcast.

Speaker 2: 33:18

Thank you again, Ali.

Speaker 1: 33:20

Thanks, thank you.