The risk selection differentiator

Fresh from launching an E&S habitational program alongside its established admitted offerings, Honeycomb is looking to translate its low loss ratio built on data-driven risk selection to other areas, according to founder Itai Ben-Zaken.

What characteristics of the market opportunity in habitational business appealed to Honeycomb?

Honeycomb from the beginning has been pretty consistent with our strategy in that we started in a market that has a relatively deep challenge. The problem we set out to solve is this is a market that a lot of insurers have basically just categorically said no to, or they've started carving out some big pieces of what they don't do to remain with a very small piece where most of the insureds don't really have an option.

We said listen, let's try to figure out what really is the root cause of the underlying problem. Is California a place where you cannot write business at all? We don't think so. But yet, a lot of the carriers when something is starting to happen in California, very quickly, they say, “You know what, let's just not deal with that”, which, again, maybe for them makes a lot of sense.

And for that, we started building a deeper mousetrap for risk selection and for risk pricing. But a lot of it really comes down to risk selection, so how do you look at the 30-something million people in California, or the 10-something million units in California, [and be able to say], “This one is great, I'd love to take it and the other one might not fit my appetite at that level of granularity.”

How do you differentiate through that risk selection and risk pricing?

It goes into the individual roofs that we assess, it goes into all the data points that we collect about the landlords and about the level of maintenance of the property and the remote inspection and the AI that we put in place to do the actual assessment work. Once you have the imagery, that's a lot of the heavy lifting.

I see us continuing doing that. It's been proven to be very effective for us in the initial market we launched in, which is the market for multifamily homes. We're running at a 30 percent loss ratio inception to date on an incurred basis, and on an ultimate basis, probably we'll end up somewhere in the low 40s. I think the idea is to continue to do two things. One is to continue to deepen that advantage – we don't want to stay where we are. We have something good going, but the level of innovation that we can continue to create on street-level photography, on remote-inspection-level photography, there's a lot more work that we can do there. A decent chunk of our underwriting right now is still being done manually, and there's still room to automate a lot more of the process.

How transferable is the mousetrap you’ve built to other areas?

We have built something that is an end-to-end process that works really well. Right now it works only in one vertical, which is multifamily property or landlords and HOAs. But there are other markets that we want to start approaching. We'll do it slowly and steadily and we’re going to stay close to core, but there are some pretty nice complementary offerings, just like the E&S product we just launched.

So the next thing would be to launch a few more of those complementary products, potentially excess liability. We look at it from a customer standpoint. Our typical customer is a real estate professional who might have a few apartment buildings, but they also probably have other types of real estate. So if you think about the other lessor's risk only policies for retail or for any other type of commercial property, those probably are the most likely that we'd expand into.

We’re also going to be investing more in deepening what we have, because we're still just scratching the surface. There are many more states that we could expand into that we're not live in, or we’re just starting in.

How easy will it be to translate the low loss ratios you’ve generated so far to adjacent products?

In excess casualty, we believe it is [transferable] because a lot of it has to do with the level of maintenance of the property, who's living in the property, who is the landlord, how reliable they are, what reputation they have in the market and a lot of this is correlated.

There are verticals, there are products where we would need to build another layer. I think excess liability does have quite a lot of correlation with the underwriting we already do now. We already underwrite quite deeply for liability and we offer $1mn/$2mn or $2mn/$4mn limits. So to offer $5mn, I think we already do a lot of the underwriting. If you go into a business where a lot of the general liability claims are originating from foot traffic of customers entering a store, there is a layer that we would need to build on top of what we have.

I think that anything that is the building itself, the roofs are a pretty big component of it, and we've invested a lot in the roof component, and that's also where a lot of the industry is seeing a ton of losses, and we're not, because I think we're doing a much better job in underwriting roofs, and in managing the exposure for severe convective storm (SCS) particularly. We have a pretty unique approach to that, and that should be pretty transferable to anything else with a roof.

Tell us more about your approach to SCS and why it’s been successful so far?

The beauty of it is that our secret sauce is something that is not really secret. What we are doing with SCS is really executing a lot of the best practices that make common sense, but that are very hard to execute when you're a legacy carrier doing multiple lines. When you're only doing what we are doing, then you can invest 100 percent of your efforts into creating the best system.

It starts with writing good roofs. We can really precisely assess the age of the roof. We have the ability, from aerial photography and from our algorithms, to exactly know what the age of the roof is. And it sounds obvious, but it's something that the industry doesn't really do.

And then not every building is made equal in terms of the [type of] roof. The hail footprint is very different from building to building. It sounds like common sense but it's hard to execute when you're sitting on top of legacy systems, when you're doing everything manually. We focus on one thing, and we built that level of granularity where everything is coded in one system, the data sits in one place, so we can compute the hail footprint for every building.

And then we flex the deductibles and the pricing in a more advanced way. A lot of carriers basically say, “You know what, we probably need 2 percent for hail.” We say, you know, it’s 2 percent for some buildings, but some other buildings it’s 1.5 percent, and then I win a good building that’s going to be much more profitable. And then some other buildings we might say, 7 percent. It's not just price differentiation, it’s also deductible differentiation.

The last piece is that we also control our radial aggregations very, very carefully. That's not something the industry doesn't know exists. It's a secret sauce that's not really secret, but it is about having a system that, in real time, can tell you which assets you have, not only insured, but those that are out-quoted, and whenever it gets bound, it gets off the table. We know exactly at every moment how much aggregation for hail we have in every radial in every zone.

Really the secret sauce is in the execution. How do you do that consistently at a growing scale, in multiple states that have different characteristics, and with multiple underwriters.