Strategies for addressing wildfire risk

Using data and technology at three critical customer touchpoints can help carriers underwrite risks and settle claims more effectively.

Wildfires contributed to a 46% increase in fire severity for U.S. carriers in 2018 and making it critical for them to factor an extended fire season into their predictive models. (Photo: Shutterstock)

U.S. insurance carriers are challenged to reduce their exposure to loss as wildfires consume ever-larger areas of the country. While carriers have gotten better at analyzing claims, a possible new recurring pattern of headline-making wildfires, like the most recent one in Australia, could keep many carriers in a stalemate in their ability to assess, price and underwrite risks effectively.

While 2017 is regarded as one of the worst years for wildfires, 2018 proved to be even deadlier and more destructive. In 2017, fire claim severity increased by 22% as compared to 2016, while 2018 saw an increase of nearly 80% as compared to 2016 according to the LexisNexis Home Trends Report. The aggregated fire loss in 2018 is the highest we have seen in a decade. In its wake, carriers saw fire loss cost spike by 51% compared with 2017 — which itself experienced another record-breaking wildfire season. Wildfires also contributed to a 46% increase in fire severity for U.S. carriers in 2018.

The 2019 U.S. wildfire season was not as active as 2018, and the total impact of 2019’s wildfire activity is still being calculated; however, early findings suggest that increasing fire loss cost and severity may continue to challenge carriers. For instance, the Kincade fire in October 2019 burned more than 76,000 acres in California’s Sonoma Country, destroying or damaging 434 buildings, according to the California Department of Forestry & Fire Protection (“CalFire”).

While the impact of wildfires will always be uncertain, carriers should consider taking a more data-driven approach to their underwriting analysis. In contrast to other kinds of insurance, the new business fire risk for an area has been typically classified with simple, non-analytic rules or expert opinions, whereas renewal fire risk management requires data aggregation and modeling that most carriers simply do not have. A data-driven strategy leveraging fire trend data can bring greater consistency in enabling carriers to ensure that policy premiums and underwriting guidelines effectively reflect the peril.

With the insights from the data, carriers should then forge a more proactive partnership with policyholders and their communities in mitigating the potential risks of wildfires. There are three critical customer touchpoints in time when this data-driven engagement will have the maximum effect and help to reduce the severity of claims — before, during and after the wildfire event.

Before the fire

Losses from wildfires can be severe as entire homes, possessions and lives are at risk. Unlike other types of homeowner loss, fire losses rely on the community’s fire response capabilities. To accurately classify the risk, carriers must be able to quantify the community’s ability to respond to future wildfires.

It’s not an easy task. A confluence of new factors is driving up the destructive footprint of wildfires. As a starting point, the National Park Service finds that nearly 85% of wildfires in the U.S. are caused by humans as a result of campfires left unattended, intentional acts of arson, burning of debris, equipment use and malfunctions or negligently discarded cigarettes.

Compounding matters even further, we continue to build more housing in or near forested areas — what the industry calls the Wildland-Urban Interface (WUI) — increasing the density of homes and people in more difficult-to-reach areas. Today, more than one-third of the U.S. population lives in a WUI area, according to the latest USDA figures. In addition, building costs are steadily rising, and after a wildfire event “surge pricing” can also occur in the areas, which can make the cost to rebuild a home even more expensive. These trends add two risk factors to the data: a probable increase of wildfires due to human ignitions and greater destructive potential due to the density of buildings and cost to rebuild.

Consequently, carriers will need to frequently reassess their geographic exposure. Predictive analytics could include data points such as true driving time and historic response time by first-responders, as well as other factors that affect responsiveness such as volunteer fire stations. The tools can incorporate cutting-edge geospatial technology, historic fire department responses, true drive times from responding fire stations, historic loss data and other data sources to help precisely model the peril of wildfire. Employing new technologies like digital mapping and remote sensing with drones can add relevant landscape factors to the analysis as well.

Analytics can also help carriers understand their cumulative risk for a particular neighborhood or area, making sure they haven’t insured a disproportionate amount of properties in a wildfire-prone locale.

Carriers need to factor an extended fire season into their predictive models as well. The traditional fire season in western states corresponded with the time winter precipitation dampened combustible vegetation. According to CalFire, the California fire season has lengthened by 75 days over the past decade. California experienced the deadliest and most destructive wildfires in its history in 2017 and 2018.

A prescient understanding of all these factors can give carriers a more accurate assessment of the frequency and the extent of potential wildfire damage in the area.

During the fire

When an active wildfire poses an imminent threat, carriers can reduce the severity of the risk by becoming more engaged with their policyholders. Carriers can become real-time agents during the crisis, keeping homeowners informed with up-to-date information about the fire’s progress and educating them on the steps they should take to protect their homes and loved ones.

Carriers can help distribute and activate disaster preparedness plans, for example. They can also advise on how to create a zone around structures to slow or even re-direct the wildfire around the property. For higher value homes, some may recommend activating permanent wildfire protection systems or calling a dispatch service to help protect the home during the fire, like WDSresponse, who can use fire-retardant foam typically used by aerial firefighting aircraft.

Drone technology is also increasingly being used to provide situational awareness during and immediately after a wildfire. Drones can provide a real-time bird’s eye view of a wildfire and its destruction, as well as collect valuable data that can be analyzed to better protect the properties in its path and help more accurately predict future fires.  

Insurers should also use this crucial time to prepare and pre-stage field staff and adjusters to ensure that they can get on-site quickly post-fire to help expedite the claims assessment and process and get homeowners back in homes as soon as possible. Recent wildfire claims data can also be further analyzed to identify trends that might be helpful in filing claims resulting from the current fire underway.

After the fire

It’s critical to help affected homeowners recover as fast as possible after a wildfire damages their home. The key is in balancing the execution claims processing with empathy. Data and automation can play a critical role in improving insurance claims outcomes and making customers whole again through better resource allocation.

Yet, while carriers have incorporated data and analytics into their underwriting processes, few have integrated analytics into their claims handling processes. Doing so not only lowers loss adjustment expenses, but it also builds greater customer loyalty by resolving claims faster so that they can repair and rebuild.

Utilizing data prefill technology, for example, can gather and deliver wildfire claims-related information directly into a carrier’s claims management system in near real-time. It can verify existing data and provide missing information both at the first notice of loss and as additional information is gathered by the adjuster. These technologies fill in the missing pieces by drawing information from a variety of external sources such as public records and drone data. As a result, distressed homeowners need only supply limited information to initiate the process, which can also help with customer satisfaction in the long run.

Final thoughts

Pricing wildfire risks correctly is critical for an insurer’s profitability, especially since fire losses tend to be severe. Based on LexisNexis research, in general, the payout for 77% of fire claims exceeds $100,000. However, due to the severe nature of losses in 2017 and 2018, that metric jumped up to 85%. To reduce exposure to loss, carriers must ensure that premiums and underwriting guidelines accurately match the potential destruction.

The future of wildfires is uncertain, especially as development continues to expand into WUI areas. Consequently, loss exposure will continue to increase for carriers.

Using technology and data at the critical touchpoints of a wildfire event will help carriers reduce costs, increase efficiencies, and improve customer satisfaction by resolving claims faster.

Bill Brower (william.brower@lexisnexisrisk.com) is vice president, claims for LexisNexis Risk Solutions. George Hosfield (george.hosfield@lexisnexisrisk.com) is senior director, home insurance for LexisNexis Risk Solutions.

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