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Electronic Chat with John Siegman

John Siegman is CCA and Founder at HazardHub, the only third-generation provider of risk databases for U.S. property-level natural and man-made hazards. The company’s team of scientists translates geospatial digital data to provide risk assessments that can be used to make real-world decisions.

Tell us a little about your professional background, and how you came to become involved with insurance and cat risk. 

I’ve been involved with data my entire professional career.  I started doing market research at San Diego Gas & Electric and moved to a geodemographic targeting company, National Decision System, where I met my cofounder Bob Frady.  From there I went to QMSoft where I met Brady Foust, my other cofounder (I refer to Bob and Brady as my two BFs). QMSoft built the first single disc geocoder and along with that the first set of geospatial insurance data. Through a number of acquisitions, QMSoft ended up at Pitney Bowes. From there, I rejoined Brady at a company called Proxix that built out the second set of insurance geospatial data. That company ended up being a part of CoreLogic, where I brought Bob in to run major accounts. We all eventually left and about five years ago, got together over lunch, looked at the lack of choice in the market, and decided to form HazardHub. We thought the market was looking for a cost-effective data solution and we knew there was a lot of data that needed to be made that no one was tackling.

Based on your past career experience, dating back to San Diego Gas & Electric, you have always been involved in data collection and analysis. How dramatically has the data industry changed since the 1990s, and where do you predict it will go in the future?

It’s massively changed. Data collection used to worry about which data to save as storage costs were prohibitive. Now, we have over 3.5 terabytes of data in the cloud and we’re always adding more and no thought is given to if it will be “worth anything.” We don’t have to make those decisions; we let our customers make them. Also, everyone now is a data generation point.  Through IoT, remote sensors, your phone, and more, the amount of data can be overwhelming. We try to distill massive amounts of data into a usable format that provides an answer to very specific questions.

You are based in California, where earthquakes and wildfires play a dramatic role in everyday life. How has your background impacted your current career?

HazardHub is headquartered in San Diego; it’s a dirty job, but somebody has to live here. No matter where you are, the hazards that you’re exposed to do not run your life. Yes, you might think about them on occasion, you might even mitigate for them, but you don’t get up every day fretting about them. What we’ve probably learned most is that, in general, most people have very little knowledge about the hazards they are exposed to. Since you mentioned wildfire, only 17% of California is a concern. And of that, about two-thirds is only a moderate concern. However, about 7% of structures in the state are seriously at risk and score an F in our model. F scores will face wildfire events on average every 15 years. If I lived in an F scoring dwelling, I’d make sure I mitigated to the nth degree. 

HazardHub is in its third generation of building geographic data risk maps. What are some of the biggest changes between the first and third versions?

HazardHub’s first generation was QMSoft, the second was CoreLogic, the third is HazardHub. Like most people, the first time you do something you’re okay at it, the second time you do something you’re better, the third time you do something, you really know what you’re doing. So, while we’re a relatively new company, we have over 120 years of experience building hazard data sets.  Because we’re constantly working on improvements, some of our data sets have gone through three iterations.

There are two big differences between us and our core competition. The first is that we want people to see the data behind the models. We do not believe in the black box mentality. A lot of our customers use our grades, but a growing number are using our data inputs and creating their own models. The second is we score everything dynamically. We have no points that are pre-scored. What this means to our customers is that our data is constantly fresh. For example, we update our hydrant database every week. Our fire station database gets updated every other week. If we get an updated water file today, tomorrow every model that uses it will produce an updated answer. We’re not afraid of change and work every day to improve what we deliver. 

What sort of technology do you use to gather data on risk specifics? How has this changed over the years, and what emerging technologies will affect data collection in the future?

We collect data from all sorts of different places and use a lot of daily feeds to keep the information we provide current. We use a lot of satellite data, a lot of incident data, tons of imagery, and massive amounts of GIS files, to create data and answers. It used to be that the government was the only source for this information. That has changed dramatically. There are so many collection sources and points that the problem is no longer a lack of data, it’s finding the relevant data. I think that AI is an emerging technology that will impact data collection. For AI to work best it requires vast amounts of data as an input. We have vast amounts of data.

Based on your experience with risk data, in what areas are you seeing the most dramatic increases in risk – and can you speculate on why – climate change, overbuilding, loss of wetlands, etc.?

When you look at the data -- and we do all day, and sometimes all night -- there are some noticeable trends. Storms are getting stronger. Hurricanes are not only stronger, but slower.  Tornadoes are moving eastward. And there seem to be a lot more events. To the last point, I think the number of events seems to be increasing because our ability to report on them is better. We have more sensors, Doppler radar, and cell phones to capture events. We’re working on a sea level rise model, so we do believe that climate change is having an effect. A recent hurricane had winds over 180 mph. It was only a Category 5 storm because the scale stops at 5. Places flood because of overbuilding, both at the location of the overbuilding and further downstream. Part of the genesis for HazardHub came when Bob’s mother-in-law’s house flooded. She wasn’t in a flood zone, but she was close to one, and nobody ever told her. At HazardHub, we want everyone to know what hazards, natural and manmade, they’re exposed to.  

I took HazardHub’s free property risk analysis and was immediately terrified! Any advice for homeowners to mitigate risk in the areas where they live?

It’s great to see that you went to and ran a FreeHomeRisk report. The first piece of advice I’d give you, you’ve already done. You’ve run the report, so you know what to mitigate for. On the report we provide a high-level summary of the data behind our models. Our customers get all of the data that goes into our models as we don’t believe in the black-box approach, but that would be too overwhelming for the consumer. Once someone knows what to be prepared for, they know how to mitigate. As you mentioned, I live in California, land of earthquakes and wildfires. At my house, water heaters are strapped to the wall, big furniture is properly secured, there are no open eaves, there are 100 feet of defensible space, double baffle vents -- we’re mitigated. Can bad things still happen? Sure. But they will be less bad at my address. The other aspect is that once you know what can happen, you know how to properly insure for it. A growing number of our customers use our data to help educate their customers on the types of coverage they really do need.

You’re also involved in Fun Cars of San Diego, a car dealership specializing in the purchase and sale of contemporary and classic collector cars. Please tell us a bit about it.

Everybody needs a hobby; mine happens to be as a licensed car dealer in California. The only difference between men and boys is the price of their toys. From Mini-Motorifics, to Hot Wheels, to AFX slot cars, to a driver’s license, I’ve always liked cars. Fun Cars focuses on fun cars (just like HazardHub focuses on hazards). It has allowed me to experience a lot of cars and then send them on to permanent owners. I refer to it as car dating. It’s taken a significant back burner to HazardHub over the past five years, but I still get to do three or four cars a year. At Fun Cars we believe that life is too short to drive boring cars. 

Prior to starting Fun Cars, my family and I had to evacuate from the 2007 Witch Creek fire; flames came within 1,000 feet of our home. At that time, we had three cars and two drivers. Which car stayed home? The most expensive one we owned, because it had two seats, a convertible top, and couldn’t carry anything. Hazard data isn’t just for homeowners any more.





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