Rethinking the structural wildfire gap in modern housing
Featuring
A conversation with Jamie Knippen and Allie Barefoot
Traditional wildfire models rely on static inputs like slope and vegetation, creating a major blind spot when fires reach subdivisions and structures become the primary fuel source. Legacy maps also overlook property-level defenses—like fire-resistant roofing and defensible space—which can cut losses by up to 78%.
This disconnect distorts real vs. insured risk. Neighboring properties with the same base hazard score can see risk score swings of up to 40 points depending on structure density and mitigation efforts, leaving over $1.4 trillion in property value exposed to sudden premium spikes and coverage gaps.
In this episode of Data in Context, host Allie Barefoot sits down with Cotality’s Director of Hazard Insights, Jamie Knippen, to break down Cotality's 2026 Wildfire Risk Report.
In this episode:
1:33 - Why do hazard scores jump 40 points when wildfires hit subdivisions?
2:40 - Analyzing the ROI of property-level mitigation.
3:39 - How does wildfire risk affect escrow shocks and insurance premiums?
4:46 - What is the difference between pre-burn and post-burn modeling?
5:40 - Mapping $1.4 trillion in RCV across California, Colorado, and Texas.
Transcript:
Allie Barefoot: Welcome back to Data in Context. I'm Allie Barefoot with Cotality. When we look at natural perils, wildfires present one of the most rapidly evolving challenges for the housing, mortgage, and insurance markets. Cotality’s 2026 Wildfire Risk Report reveals that across the top 10 most exposed states alone, more than 2.5 million properties sit at moderate or greater risk. The real story isn't just the sheer scale of the numbers. It's that legacy models and traditional hazard maps are missing structural fire spread, property-level mitigations, and dynamic post-burn fuel recovery entirely. To help us explore the data-driven defenses needed to close these gaps, I'm joined today by Jamie Knippen, Cotality’s Director of Hazard Insights. Let's put the data into context. Jamie, welcome to Data in Context! So excited to have you here.
Jamie Knippen: Thanks so much, Allie. Looking forward to the conversation.
Allie Barefoot: Yeah, we're talking about wildfire risk here, and I want to start at the core of how physical hazard is modeled. Because traditional wildfire models, they evaluate slope, terrain, and natural vegetation, but step risk down as development starts to thicken. So why did these legacy models break down the moment fire reaches a developed subdivision, and how big is that hidden score jump?
Jamie Knippen: Completely. So when a wildfire-induced conflagration occurs, the fuel source ultimately switches from typical vegetation—so think of things like trees and bushes—to the structures themselves. In a lot of ways, even when they come into the neighborhoods, sparse vegetation like the tree in your front yard becomes irrelevant. Models really need to consider elements like structure density, structure characteristics, wind, and weather in addition to traditional wildfire drivers in order to comprehensively understand the wildfire peril. When this occurs, if a model is able to understand both the traditional hazard that's tied to the wildfire, as well as the drivers of conflagration, you can see a swing in terms of risk scores of almost 40 points.
Allie Barefoot: Wow, that's actually a pretty big jump.
Jamie Knippen: Completely. It's a big gap.
Allie Barefoot: Right. And so the scientific consensus points to the Home Ignition Zone—the building itself and the immediate 100-foot perimeter—as ground zero for structural survival. What does our 6.8 million property analysis reveal about the real return on investment for property-level mitigation?
Jamie Knippen: Yeah, so what we see is that model loss costs fall exponentially as property-level mitigation improves. In fact, the top 10% of most mitigated homes carry expected wildfire losses 78% below average, while the least prepared 10% face over 10 times the average risk. Breaking that down, that means that for every single dollar of expected loss on a well-prepared home, an unmitigated property is going to face $47 in terms of risk.
Allie Barefoot: Jeez, when you really put it into numbers, it's pretty eye-opening, yeah.
Jamie Knippen: Completely. It's a big gap.
Allie Barefoot: Right. And if we shift over to the insurance side of the conversation, that's where this exposure really starts to hit home, I feel like. As wildfire risk escalates, it's becoming harder for property owners to get and keep adequate insurance coverage. How are rising premium costs and coverage restrictions directly driving up monthly mortgage payments?
Jamie Knippen: Yeah, so when wildfire risk premiums spike or force homeowners into those expensive state residual markets, lenders often cover higher bills through escrow, which triggers sudden increases during annual reviews to cover both the new costs as well as past shortages. Additionally, when standard policies cap limits or restrict coverage, mandatory lender requirements force property owners to buy more expensive supplemental policies. Ultimately, all of these things combined drive up those total monthly housing payments.
Allie Barefoot: Right, and then once that wildfire starts to come in, there's always some unexpected damage that also comes along with it. So having those mitigations to really help make sure that you're not paying anything more out-of-pocket than you originally thought you were going to...
Jamie Knippen: Exactly. Mitigation does very much matter.
Allie Barefoot: Right. And natural vegetation is also very dynamic, especially after a burn. Why is holding two concurrent views—pre-burn and post-burn—so vital for underwriters looking at long-term risk?
Jamie Knippen: Yes, yes. So when an underwriter looks at a location that falls within a recent burn scar or a fire perimeter—so let's say the Palisades Fire that occurred in 2025 in Los Angeles—they see now a temporarily low-risk area because the natural vegetation in that area was burned during that event. However, what we know is that natural vegetation can regrow quickly. So holding a pre-burn view captures the long-term baseline hazard to prevent false security and sudden future shocks as that fuel does regrow. While a post-burn view captures the immediate, real-time exposure needed for accurate, present-day underwriting decisions. So combining both of these views really allows for carriers to price risk accurately without falling into those temporal gaps.
Allie Barefoot: Yeah. And looking at the macro picture across the country, Cotality evaluated properties with a post-burn risk of 51 or higher. How is this $1.4 trillion in Reconstruction Cost Value distributed across states and major metro areas?
Jamie Knippen: Yeah, so that $1.4 trillion in Reconstruction Cost Value (RCV) is heavily concentrated in California, which accounts for over $850 billion across nearly 1.3 million properties. This is then followed by Colorado, which sits at about $146 billion, and Texas, which sits at about $105 billion. As we look at the metropolitan areas, we actually see that California dominates with about six out of the ten top most exposed markets. This is led by Los Angeles, followed by areas like Riverside as well as San Diego. And then if we look outside of California, since we know that wildfires don't only exist there, we look into Texas, and Austin, Texas anchors that largest concentration with about $49.2 billion at-risk property value.
Allie Barefoot: Yeah, it's very important to think of states really outside of California. I know that when you look at the headlines, you tend to see California most frequently. But thinking of those drier lands like Texas and Arizona, like you said, is also extremely important.
Jamie Knippen: Exactly.
Allie Barefoot: Well, thank you so much, Jamie, for breaking down a little bit of the data from Cotality's 2026 Wildfire Risk Report. This has been super eye-opening, and definitely excited to dive deeper into the data with the report itself.
Jamie Knippen: Yes, my pleasure. And thanks for having me, Allie.
Allie Barefoot: Thank you again to Jamie for joining us here on Data in Context, and thank you so much for listening. If you haven't already, subscribe to Cotality's YouTube channel, and if you want to find out more information, as always, head on over to cotality.com.
