Insurance Risk Modeling with POI, Building Footprint, and Foot Traffic Data

Geospatial Data with the Accuracy, Precision, and Freshness Insurers Need


With SafeGraph Places data, insurance risk models can accurately and precisely measure how location and human mobility impact a property’s risk exposure, so policies can be priced accordingly.

Differing visitor profiles are essential information for insurers who are developing risk profiles for these businesses. While two businesses might be located near each other, the way consumers interact with them may indicate the need for drastically different insurance policies. This can only be analyzed using mobility data, like the SafeGraph Patterns data shown in this dashboard. Explore how consumers interact with different business locations in this interactive map, and see how SafeGraph data can inform your spatial analytics.

Explore how mobility data can impact general liability insurance
Xcel Energy

Accurately Model Co-Tenancy Risk with Precise Polygons

In an increasingly competitive and data-driven insurance market, insurers must stay on the cutting edge of risk assessment and modeling to win and retain customers. There is no room for error, or data that is “good enough.” Under-assessing a property’s risk can lead to increased exposure for the insurer, while over-assessing can lead to customer churn and dissatisfaction. Polygons give insurers the precision they need to ingest into their models to assess risk with confidence.

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Accurately Model Co-Tenancy Risk with Precise Polygons

Learn more about SafeGraph data for insurance

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