Wildfire risk: When a secondary peril shapes primary underwriting decisions

Authors:

Emily Prestley, Associate Director - Product Management, Moody's

Victoria Boreham, Associate Director - Product Marketing, Moody's

Oliver Smith, Associate Director - Product Management, Moody's

Long treated as a secondary peril, wildfire in the U.S. has sometimes been unfairly placed behind hurricanes and earthquakes in many property portfolio evaluations. This placement may well change, as in recent years wildfires have been on a par with peak-peril catastrophes, producing US$10 billion or more in insured losses, challenging long-held assumptions about how this risk behaves.

With longer fire seasons, hotter and drier conditions, and the rapid growth of communities within the wildland–urban interface (WUI), the scale and volatility of wildfire losses have both materially shifted.

This has left traditional underwriting tools and techniques, such as ZIP code-based rules, distance‑to‑fuel heuristics, or historical losses, looking insufficient for sustainable growth.

For instance, traditional ZIP-code-based rules would fail to reflect what has been witnessed in recent wildfire events. Two homes just five or ten feet (1 to 3 meters) apart can face materially different outcomes due to property-specific conditions such as the surrounding vegetation, building proximity, or construction features that impact vulnerability. These small differences at the property level can materially influence portfolio outcomes.

For underwriters, wildfire has shifted from a marginal rate-loading consideration to a risk selection and accumulation challenge. For property carriers overall, these material differences in vulnerability are no longer a marginal issue; they directly affect how risks are selected, priced, and managed across the lifecycle from the first quote through to renewal and portfolio steering. 

These risk decisions must also then stand up to regulatory scrutiny, distribution partner challenges, and renewal-time assessment, placing greater emphasis on transparent, repeatable underwriter logic.

Underwriting gaps at the point of quote

At present, many underwriting workflows struggle to evaluate wildfire risk at the necessary resolution that the exposure demands. Operational evidence further reveals the challenges property lines face: fragmented data, slow workflows, and a lack of unified analytics are major factors contributing to underwriting errors and inefficiencies.

Examining these factors more closely, you see that the use of property-level hazard and vulnerability data can be too aggregated, inconsistent, or incomplete, and portfolio‑level catastrophe modeling data rarely flows smoothly into day-to‑day underwriting. Where anomalies occur, manual checks, referrals, and disparate systems all slow quote turnaround and increase the risk of inconsistent decisions.

All these pressures are bearing down on underwriters, who are being asked to make faster risk decisions in a more unpredictable peril environment, all while still staying aligned to portfolio steering and reinsurance constraints.

Without a consistent, defensible, property‑level view of wildfire risk that can be applied at quote, carried through to portfolio monitoring, and then revisited at renewal without slowing the workflow, these risk-decision pressures will remain.

Moody's Peril Metrics and Property Intelligence: Enabling precise, consistent decisions

Delivering a consistent, underwriting-ready view of risk directly in the underwriter workflow, our new Moody’s Peril Metrics and Property Intelligence solutions combine CAPE’s property-level attributes with Moody’s RMS™ catastrophe model analytics.

Helping ease the pressures faced by underwriters, Peril Metrics supports decision-making by translating catastrophe‑model science into three underwriting‑ready signals that can be applied consistently, helping teams work from a shared view of risk across geographies.

In practice, each of the three signals plays a distinct role, helping underwriters understand the specific factors driving a property’s hazard, vulnerability, and mitigation period, including how vegetation reduction or structural improvements would change the underlying risk signals.

• Hazard describes the physical wildfire exposure around a property (environment and peril intensity), e.g., surrounding fuels/vegetation, defensible space/vegetation encroachment, risk of urban conflagration, historical wildfire activity, and proximity to nearby structures (structure density).
• Risk scores (1–10) translate catastrophe-model losses into a simple, comparable measure to support fast triage, segmentation, and appetite rules that consider both the hazard and vulnerability risk landscape, informed by property attributes such as roof material (e.g., wood shake) and features like wood decks.
• Loss costs express the expected annual loss from wildfire at that location, leveraging the Moody’s RMS™ U.S. Wildfire HD catastrophe models' 100,000-year simulation period to help underwriters sense‑check premium adequacy and support technical pricing decisions, and quantify how actions like vegetation reduction/defensible space improvements or structural changes may move expected loss.

Looking ahead

Wildfire remains a defining underwriting challenge as exposure grows and climate pressures intensify. To help, using wildfire-specific attributes provides underwriters with sound reasons for their triage decisions and mitigation requests. The attributes also assist with sharper risk appetite control, clearer technical pricing alignment, more efficient triage, and better portfolio steering.

Carriers who adopt property‑specific, model‑consistent analytics across the entire wildfire risk lifecycle will be best positioned to achieve this fine balance between growth and volatility control.

To learn more, click here Moody's Peril Metrics – or contact your Moody’s sales representative.