Underwriters’ reliance on blanket models is contributing to underinsurance, Nearmap chief product officer Dave Tobias warns.

He adds a growing insurance gap is not just a result of rising climate risk but how that risk is assessed.

“When underwriting relies on broad, regional models, outcomes are blunt – lower‑risk properties often overpay, while higher‑risk ones lose access to coverage altogether.

“Risk is evolving at a highly local, property‑level pace, while many models remain generalised, backward‑looking and slow to adapt. This disconnect is becoming impossible to ignore.”

Aerial imaging group Nearmap says the future of insurability hinges on a move away from generalisation to precision, as reliance on postcode-level or regional data obscures differences between individual properties, producing “pricing that feels arbitrary and unresponsive”.

Until risk can be understood at property level, insurers and policyholders are “left without clear signals on exposure or resilience”.

Mr Tobias says high-resolution aerial imagery – combined with AI analytics capturing factors such as vegetation, property condition and exposure history – enables more accurate underwriting, faster claims and fairer pricing.

Speed is “equally critical”, and insurers can now assess thousands of properties in days or hours after disasters.

“The greatest opportunity lies in prevention,” he added. “With better data, insurers can identify hotspots, simulate scenarios and collaborate with governments and communities to reduce impact before disasters strike.” 

AI supports better decisions and shared evidence across insurers, governments and communities, enabling clearer communication, more targeted resilience investment and stronger alignment between pricing and real-world risk, he says.