A Tale of Two Californias: Managing Wildfire Risk in the Year 2030

For most of the 20th century, the insurance industry considered wildfires to be little more than a nuisance. They were frequent but rarely resulted in more than a handful of claims, and underwriters priced for them in the same way as other attritional sources of loss like theft, breakage and sewer back-up.

In 1991 everything changed. The 1991 Oakland Hills Fire ($4 billion insured loss) provided the first glimpse of the horrors that a wildfire could bring, killing 25 and destroying 2,900 structures in less than a day.

Wildfire losses accelerated over the next 25 years with the Cedar, Old, Witch, Butte, and Valley fires collectively destroying 8,300 structures and resulting in more than $5.7 billion in insured damages.

Then came the 2017 and 2018 seasons, when 11 huge fires wiped out entire neighborhoods and cities. In the end, the toll of these two seasons stood at 135 deaths and more than $30 billion insured damage suffered in all corners of California.

Now, everything has changed again.

With a warming climate, a growing population in high risk areas, and an overgrowth of burnable vegetation, wildfires aren’t going away — and we must adapt to this reality. A lot of work is needed to improve our wildfire safety, data and analytics, emergency response and resilience. We must begin now.

Ten years from now in 2030, California faces one of two futures. I present you both from the perspective of an analytics provider to the insurance industry.

The first is the Good California, where we rise to the challenges that face us today, and insurers have fundamentally changed their approach to underwriting wildfire risk.

Homeowners are given premium credits for safe behaviors like clearing vegetation, and screening vents (and penalties for the opposite). These credits and penalties are enabled by two technologies: computer algorithms that read satellite and aircraft imagery to detect safe behaviors; catastrophe models that quantify their impact.

Property data is abundant and accurate, enabling real-time underwriting decisions. Wildfire is treated as a peak peril, and its cat modeling is done with the same scientific rigor as hurricane, earthquake and flood.

The impact of climate change — and its statistical uncertainty — is baked into the cat models so we can better understand loss outcomes as the peril evolves. The models themselves are intensively validated by teams of experts and regulators. And the California Department of Insurance fully embraces the usage of data, analytics and cat models to support rate filings.

The fire insurance market is competitive and well capitalized, and excess and surplus lines and the California FAIR Plan play balanced roles as capacity providers for high risk homes. Homeowners are hyper-aware of fire risk, and they contribute to improving wildfire safety in partnership with the government and the insurance industry.

The Bad California is what happens when these things fail to occur. Insurers continue to use traditional mapping and hazard-scoring tools to underwrite wildfire risk, incorrectly identifying high risk areas as low risk, and they apply “broad-brush” underwriting rules that do not adequately distinguish safe properties from dangerous ones. The fire insurance market in the Bad California is a bifurcated one, with admitted carriers avoiding fire-prone areas, and E&S players with opportunistic exorbitantly priced offerings. Fire insurance becomes largely unaffordable to the working poor in small, high risk mountain communities. To those who can afford it, it is often one of their biggest household expenditures.

Insurers’ understanding of wildfire risk trails behind its technical expertise in other peak perils such as earthquake and hurricane, and because of this market capacity remains an ongoing challenge.

Insurers face many critical decisions over the next several years but if history is any indication, we are up to the task. The industry faced a similar crisis after six hurricanes pummeled Florida during the 2004 and 2005 seasons; since then hurricane risk analytics and mitigation have improved substantially. The same can be said about earthquake analytics in the wake of Loma Prieta, storm surge modeling following Hurricane Katrina and so on.

Today we must confront the difficulties of wildfire. With the right mix of legislation, planning and data analytics we can make California a safer place where fire insurance is affordably purchased and equitably priced.

I look forward to facing this challenge.