Wildfire risk models struggle to predict LA-style fires

(Bloomberg) — Among natural disasters, wildfires are the most unknown. Even the most sophisticated scientific models fail to capture all the risk factors or properly account for the growing impact of climate change.

This is a big problem for homeowners, insurers and investors, as shown by the Los Angeles fires this month, which partially or completely burned more than 14,000 structures, including several thousand homes, according to local officials.

Although the dangers of wildfire were widely known in the area, what surprised almost everyone was the magnitude of the disaster. That’s when specialized analysts will have to fill the void by finding new ways to anticipate the threats of an increasingly turbulent world.

Wildfire risk is extremely difficult to predict due to factors such as increasing temperature levels, as well as varying vegetation, wind speed, and topography. It is one of the few natural disasters where human intervention – for example, the use of fire retardants – can significantly change the outcome.

Tammy Nichols Schwartz, senior director of analytics at Guidewire Software Inc., said, “When there is little or no inherent risk in an area, you don’t need a lot of variables to assess the level of risk, and the model Agree.” Insurance solutions provider. As the perceived threat in an area becomes greater, “the accuracy of the models can vary significantly.”

Moody’s RMS Event Response estimates insured losses from the Los Angeles wildfires at $20 billion to $30 billion. That’s on top of the $79 billion, or 60% of the $132 billion, of total wildfire losses that insurers paid out globally in the last decade, according to Munich Re.

Wildfires are “a complex hazard to model,” said Julia Borman, an industry expert at Verisk Analytics Inc., who works with the insurance industry on disaster modeling. What makes the process particularly challenging, he said, is that the homes and buildings that “you’re trying to protect are often providing fuel for the threat.”

In high-risk areas, models work best when there are large amounts of granular data. How close are the houses to each other? Is there a “protectable space” between a structure and the surrounding area so that the fire department can safely protect a structure? Are there holes through which wind-blown embers can enter?

Global warming adds another layer of complexity when forecasting the frequency and intensity of wildfires. “Every year or two the models have to be updated because the climate is changing so rapidly,” said Daniel Ward, director of model development at Karen Clark & ​​Company.

California, where wildfire risk levels are particularly high, recently launched the nation’s first “public wildfire risk assessment” with the goal of improving loss forecasts and helping insurers set fair and accurate insurance rates. Has announced plans to create a “risk model”. Verisk said earlier this month it was the first step in requesting a review of its wildfire model by the California Department of Insurance.

According to Guidewire’s Schwartz, two wildfire-risk models dominated the market between 1997 and 2020. Each used only three variables, he said, and the results did not always agree.

Today’s risk-assessment tools, including one developed by Guidewire, include too many variables, such as wildfire history, fire-suppression capacity and maximum annual temperatures, Schwartz said.

This is not always enough. Guidewire’s 2023 model included estimates of peak winds, but not hurricane-force winds. The devastating fire in Hawaii that year taught a big lesson. In that fire, it was discovered that winds from an offshore hurricane played a large role in rekindling the fire that destroyed the city of Lahaina.

“Our new wildfire model will incorporate maximum wind speeds at each location, regardless of cause,” Schwartz said.

Still, investors doubt whether risk modelers will ever eliminate all the factors behind fires like the one in Los Angeles.

Ecosa Investments rarely invests in disaster bonds with wildfire risk, said Chief Executive Officer Florian Steiger. “When you look at the models, there is a gap between the modeled deficit and the economic reality,” he said.

According to managing director Sophie Ware, Neuberger Berman will invest in multi-risk “cat bonds” that are issued by large insurers such as Allstate Corp.

Still, Neuberger is concerned about “inadequate pricing given the known unknowns in the modeling,” she said.

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