LexisNexis Launches AI Model to Help Home Insurers Spot Property Risks
LexisNexis Risk Solutions released Location Intelligence for Home on May 14, an AI-driven tool that uses neural network modeling to assess property risk for U.S. home insurance carriers. The system combines industry claims data with predictive models to identify which properties are most likely to generate claims.
Properties scoring highest on the model are 20 times more likely to have a claim than those scoring lowest, according to the company's internal data.
What the tool does
Location Intelligence evaluates six perils: hail, wind, weather-related water damage, non-weather water damage, freeze, and collapse or falling objects. It integrates into LexisNexis Smart Selection, the company's automated data service, so underwriters can apply risk scores without building in-house models.
The system flags properties that warrant closer attention during underwriting and renewal decisions. It also provides portfolio-level visibility, letting carriers evaluate risk across their entire book of business.
Why insurers need it
Traditional property risk assessment often misses critical loss drivers. Non-weather water damage alone accounted for 24% of all home claims in 2025, yet exterior inspections and weather overlays typically don't catch it.
Rising repair costs and increasing catastrophic events have made traditional underwriting approaches less reliable. Carriers face pressure to improve accuracy while managing growing claims expenses.
George Hosfield, vice president of home insurance at LexisNexis, said the tool gives insurers "a more consistent way to assess personal property risk using deeper, location-based insights within the workflows they already use."
Next steps
Location Intelligence will be filed as a predictive model across various states in the coming months for use in underwriting and rating workflows. The company previously launched a version for commercial insurance.
For professionals working in insurance underwriting, claims, or risk assessment, understanding how AI for Insurance applications like this function can help you evaluate new tools your organization considers. The underlying approach-using AI Data Analysis to identify patterns across large claims datasets-is becoming standard across the industry.
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