Climate Risk8 min read

Wildfire Underwriting in Property Insurance

By Jonas Adam Mohamed Osman, known as Yonas Osman

CEO of Quantica Risk

60 Rue François Ier, 75008 Paris, France

Published 15 October 2026

Wildfire losses are outpacing historical models; property insurers are rebuilding underwriting around granular hazard data and dynamic risk zoning.

Executive answer

Wildfire losses in several regions have repeatedly exceeded what historical catastrophe models predicted, forcing property insurers to rebuild underwriting practices around more granular, dynamic hazard assessment rather than static fire-zone maps. Vegetation density, terrain, prevailing wind patterns, and proximity to wildland-urban interface areas all materially affect loss potential at a level of detail that postcode-based pricing cannot capture.

Insurers that continued pricing wildfire risk on outdated zoning have in some cases faced solvency pressure or been forced to withdraw from entire markets, which has in turn created availability problems for policyholders and drawn regulatory attention to the adequacy of underwriting practices in fire-prone regions.

Granular hazard modelling

Modern wildfire risk models incorporate parcel-level data including vegetation type and density, defensible space around structures, building material and roof type, and local topography, moving well beyond the broad fire-hazard-severity zones used historically. These models also increasingly incorporate dynamic inputs such as drought indices and seasonal fuel moisture content, since wildfire risk varies materially year to year, not just by location.

Insurers need to validate these models against actual claims experience regularly, since wildfire behavior is sensitive to local conditions that can diverge from model assumptions calibrated on different geographies. A model built on historical fires in one region may not transfer well to a new area with different vegetation or climate characteristics without recalibration.

Mitigation incentives and underwriting conditions

Because individual property-level mitigation measures, such as clearing vegetation, upgrading roofing materials, or installing ember-resistant vents, can meaningfully reduce loss likelihood, insurers are increasingly building mitigation credits directly into underwriting criteria rather than treating all properties in a hazard zone identically. This creates a financial incentive for policyholders to invest in resilience measures that also reduce community-wide risk.

Some insurers now require proof of defensible space maintenance or community-level firewise certification as a condition of renewal in high-hazard areas, shifting from purely actuarial pricing toward active risk engineering. This approach requires closer coordination with local fire authorities and consistent inspection processes to verify claimed mitigation measures.

Market availability and regulatory response

Where private insurance capacity withdraws from high-hazard wildfire zones, residual market mechanisms such as state-backed fair access plans have absorbed demand, often at the cost of thinner risk pools and higher premiums that can themselves become politically contentious. Regulators in several wildfire-prone jurisdictions have responded by allowing insurers to use more forward-looking catastrophe models in rate filings, recognising that purely historical loss data understates current risk.

This regulatory shift reflects a broader tension between affordability and actuarial soundness: premiums that fully reflect current wildfire risk can price out policyholders in high-hazard areas, while premiums that do not reflect current risk threaten insurer solvency and ultimately market availability for everyone.

Conclusion

Wildfire underwriting has moved from a static, zone-based exercise to a dynamic, parcel-level discipline that blends hazard modelling, mitigation incentives and close regulatory engagement. Insurers that invest in granular data and build mitigation into their pricing structure are better positioned to sustain capacity in increasingly fire-prone markets.

Yonas Osman, CEO of Quantica Risk, emphasises validating wildfire models against local claims experience before relying on them for pricing, since model transferability across regions is one of the most common failure points he has observed in catastrophe risk practice.

Primary sources

wildfireunderwritingproperty insurancecatastrophe risk