Safety mitigation measures for wildfire risks could herald a new era in disaster insurance

California has been left scorched by wildfires in recent years. In 2021, 8,619 wildfires were recorded, burning around 2.6 million acres and destroying 3,560 structures. Climate change is making the Southwest hotter and drier, driving a higher incidence of wildfires in the state, and increasing loss costs for insurers.

Out of the 20 largest fires to hit California, all but three have occurred since the turn of the century, with the majority occurring in the last three years. Because of this ever-increasing risk of wildfire damage, insurance premiums have skyrocketed.

With the protection gap rising as increasing numbers of Americans go uninsured, and 54% of citizens reporting that they cannot afford disaster debt, California lawmakers have been mulling over the idea of making insurers provide premium discounts for consumers who mitigate against wildfire risks. Under the newly passed rules, those who follow the Safer from Wildfires framework, created by the California Department of Insurance alongside state emergency preparedness agencies, will be rewarded with lower wildfire insurance premiums.

Insurance companies will have to submit rate filings that incorporate wildfire safety standards within 180 days. Under the first-in-nation insurance pricing regulations, they will also have to create a process for releasing wildfire risk determinations to residents and businesses.

Ricardo Lara’s legislation incentivizes homeowners to mitigate against wildfire risks, but it also leaves insurers unsure about what compulsory discounts will look like. They are, no doubt, wondering how safety measures at individual properties can help them manage risk. Fortunately, there is technology available to help identify the safety measures their customers are taking. If they can use artificial intelligence and aerial imagery to track what their customers are doing, they will be better able to manage risk and maintain profitable underwriting despite the mandatory discounting of premiums.

Using technology to identify risks

Advances in property intelligence technology will mean that it is easy to tell which customers are taking safety precautions, and which properties are more at risk than others. AI is revolutionizing the power of aerial imagery by automating the extraction of data that facilitates the creation of 3-D property models, enabling more efficient risk identification. With accurate, rich and reliable data, carriers will be able to gather wildfire risk insights, helping them determine the risk of wildfire damage.

Currently we see that carriers who classify their book of policyholders based on these kinds of insights reduce their claim losses by almost twice the average, with double-digit percentage reductions. By using new and richer data points, they will gain an advantage over their competitors because they have a better understanding of which of their clients are more exposed to wildfire risks, and they can also better estimate replacement costs.

Commissioner Lara’s legislation would cover the likes of buffer zones between trees and a property. Fortunately, the distance between vegetation and a property is exactly the type of information that is now identifiable using AI and aerial imagery. Insurers will know whether customers are really undertaking safety measures so they can set rates accordingly.

A data supplier can provide current information on how risk profiles evolve, with quarterly updates about a property’s risk score. In this way, insurers will be able to optimize the underwriting process, personalize premium pricing and provide more competitive prices for low-risk clients. Moreover, they can compensate clients who take preventive action.

This can go beyond simply monitoring wildfire risks to determine whether or not to provide a discount in accordance with the law. Insurers should also see an opportunity to advance beyond the boundaries set out by the California Department of Insurance. Carriers can be proactive and improve the experience of their customers by giving their clients personalized recommendations based on property intelligence about how to best protect themselves from wildfires.

Take the buffer zone example, where an insurer has access to data telling them that a property has vegetation within 15 feet of its walls. The carrier could automatically reach out to the customer to inform them of their wildfire risk and suggest steps to mitigate it. In this way, the carrier and the customer are collaborating to achieve a shared goal: mitigating future losses to save both parties from financial pain.

The ability to protect customers from the next possible wildfire, whether in California or another area elicits a surprisingly emotional reaction from customers. Currently, not everyone in the market understands just how powerful a retention tool this can be. A customer who gets a call from their carrier with an explanation of their risk and a recommendation about how to protect their property will begin to feel a real affinity with their insurer’s brand. By proactively protecting their policyholders, carriers can begin to push beyond a transactional relationship to develop a more emotional bond that boosts customer loyalty.

Innovative carriers are already using data at scale to personalize risk management and offer better terms to low-risk clients. In an environment where premiums are trending upwards, providing a more competitive offering to new and existing clients is a powerful way to improve their position in the market. It could be argued that because this trend has already taken off, Governor Lara’s proposals are unnecessary as the private insurance market is already beginning to provide personalized premiums based on a property safety score.

On the other hand, legislation which makes this practice more widespread could be beneficial. Either way, insurers will need access to the highest quality data possible as risk mitigation measures have a greater impact on premium pricing.

Izik Lavy is the co-founder and CEO at GeoX.

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