Fleet Insurability: Claims, Data and Vehicle Leakage

Consider telematics devices. They deliver a stream of data points, from GPS location and vehicle speed to engine hours, fuel consumption, hard braking, harsh acceleration and following distance. There is so much data that fleets can become overwhelmed quickly. They may not know which data is most important, and they might not have a set process for using that data to improve driver behavior and reduce accident risk.

Both carriers and brokers should look beyond a fleet's technology adoption when assessing a client's insurability. Underwriters should ask which data points a fleet monitors, who reviews them and what triggers an intervention. Fleets that manage their risks well will focus on a small handful of meaningful data points, then use them to tailor continuing training efforts to each driver based on individual behaviors.

Brokers have a complementary role. If they find a prospective client is experiencing data paralysis, they should partner with carriers with a proven track record of helping fleets make vehicle safety data actionable. Doing so positions brokers as trusted advisors to their clients while also helping their carrier partners write profitable business.

A fleet can look like a favorable risk when the policy is bound. It can become unfavorable six months later. Consider a carrier that insures 100 trucks, while the fleet actually has 150 power units operating on the road. If the policy is priced on a per-power-unit basis, the carrier is taking on extra exposure it never priced.

The challenge for most insurers is finding those extra vehicles before a claim or renewal exposes the problem. Some carriers are solving this by developing proprietary AI tools that compare scheduled vehicle data with inspection and operational records. If a vehicle identification number (VIN) shows up in the records but not on the policy, the carrier can talk with the client, find out why and add the vehicle to the policy midterm if applicable.

AI can stop leakage. Carriers should also realize technology should not replace human judgment. Predictive models can help insurers analyze more accounts and surface risk signals faster. Greater underwriting volume does not necessarily mean better underwriting. Experienced professionals must still determine which specific underwriting criterion matters the most.

Premiums and claims costs are rising. Carriers can no longer focus solely on rising rates. They must also reduce their losses. Insurers that thoroughly assess a fleet's loss history and claims processes, help it use data to improve driver safety, and check in regularly to prevent leakage will write good business and reduce claim frequency and severity, creating more value than pricing adjustments alone.