FutureProof applies AI to create a model that quantifies current property risk and projects how risk declines when specific property features are improved. The system evaluates granular attributes like roof condition and building materials instead of relying on zip code-based risk maps or subjective judgment. The technology produces instantly bindable, property-specific underwriting quotes that reflect resilience and mitigation investments. The approach aims to lower insurance costs for more resilient properties and address gaps in traditional underwriting that can deny coverage based on broad neighborhood-level exposure.
What we decided to do was ultimately use AI in order to create a new model that could tell property owners not just what their risk looked like today given their property features, but also how their risk would go down if those property features were altered, she said. The company's biggest innovation lies in moving away from traditional underwriting practices that often paint entire neighborhoods with a broad brush.
Instead of relying on broad zip code-based risk maps and subjective human judgment, FutureProof's algorithm analyzes details such as roof condition and building materials. Our AI enabled technology can look at a very specific address and take all those property features into account and generate essentially the algorithmic underwriting, an instantly bindable quote that is particular for that property, Valderrama said.
The goal is to reward resilient construction and mitigation measures with lower premiums. For the properties that are more resilient, or for property owners that have made investments to make their properties more resilient, they should be able to benefit from lower cost property insurance, Valderrama said. That's something that the industry has not really been able to produce at this point.
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