Every year in the United States, more than 100,000 wildfires consume the brush, trees, and homes in their paths impacting 4 to 5 million acres. While there have always been fires, the frequency and intensity of wildfires as well as the number of structures affected by fire are increasing. People are living in what used to be undeveloped wildlands turned housing developments, explained Chris White, COO of Anchor Point Group, a company that focuses on wildfire solutions. And because of this, insurers are having to change the way they asses risk and underwrite policy.
“What is starting to occur, is that these extreme events are becoming less random and more prevalent over time,” said White. “Fires are easier to fight when there is no built environment.”
With communities being built further into wildlands, firefighters must adjust their traditional priority of fighting fire in the wildlands to saving structures and preventing loss of life. “This, in combination with more severe fires directly impacts the insurance product that we have. It needs to be calibrated to the new abnormal,” explained White.
For Insurers this new reality makes writing policies for areas prone to wildfires more difficult and more costly. “You don’t want to calibrate to a rare, extreme event in defining risk for underwriting but, instead balance these rare events with the risk that occurs commonly,” said White.
So, how do insurance companies find the happy medium that covers both insurer and policyholder? Data-driven solutions could be the answer.
Using data intelligence solutions, insurers can look beyond the parcel data and utilize information like Anchor Point’s FireSheds, zip codes, street segments, and real-time location attributes to better assess risk. Assessing risk properly is a big issue for many insurers. After the California Wildfires, a study by Munich & Re found that only three percent of properties that made a claim following the wildfires had been identified as high risk, proving that traditional risk assessments are falling short. With insurance companies responsible for accurate coverage for millions, data quality becomes increasingly important.
“By putting data to work an insurer can improve the overall quality of their underwriting efforts by identifying key exposures that might otherwise have gone unnoticed but that need to be addressed and factored into pricing,” said Mike Hofert, Managing Director of Insurance Solutions at Pitney Bowes.
To learn more about data-driven risk assessments, click here.