Overview
Property-level fire protection data and risk
Predict loss severity in the event of non-weather-related structural fires with Cotality’s Fire Resiliency — an address-level risk scoring model. This AI-driven solution analyzes unique structural characteristics, geographical and fire history data, and community fire response data to determine the probability of total loss in the event of a non-weather-related fire event.
Make data-driven decisions about risk
We plug in the AI risk management model plugs into Cotality’s property intelligence database to deliver insights on all in the continental U.S. This ensures address-level precision when in risk scores.
Reduce high-severity claim business
Get a complete portfolio analysis with Fire Resiliency. Insurers can identify areas of higher risk and adjust their rates accordingly. This helps with policy and avoiding costly losses due to fire damage.
Improve underwriting eligibility models
By providing a single variable rather than a lengthy set of data points, Fire Resiliency gives underwriters a simple mechanism to determine a property’s resiliency against non-weather , and set accurate policy pricing.
Make data-driven decisions about risk
We plug in the AI risk management model plugs into Cotality’s property intelligence database to deliver insights on all in the continental U.S. This ensures address-level precision when in risk scores.
Reduce high-severity claim business
Get a complete portfolio analysis with Fire Resiliency. Insurers can identify areas of higher risk and adjust their rates accordingly. This helps with policy and avoiding costly losses due to fire damage.
Improve underwriting eligibility models
By providing a single variable rather than a lengthy set of data points, Fire Resiliency gives underwriters a simple mechanism to determine a property’s resiliency against non-weather , and set accurate policy pricing.
Features
Make a difference with the right data
Fire Resiliency processes institutional quantities of fire protection and building characteristic data to give insurers a robust understanding of the probability of properties succumbing to total loss during a non-weather-related house fire.
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Enhanced usability with AI-Driven assessment
Our AI-driven Fire Resiliency scoring model analyzes large datasets to assess property resilience at the address level. This streamlines policy considerations, so you don't need to sift through massive data.
Leverage updated fire protection data
Our comprehensive U.S. fire station database, which contains over 53,000 fire stations and 29,000 fire response areas, is updated quarterly to provide the most accurate view of fire station location, staffing, and response jurisdictions.
Get accurate fire resiliency evaluation
Our model uses Property Enriched™, aligning multiple data sources to identify properties not in public records. This provides a “single source of truth” and identifies key building characteristics for accurate fire resiliency.
