Case Study: Zurich achieves more transparent policy pricing and underwriting insights with Snowflake

Zurich Uses External Lidar Data to Deliver More Transparent Policy Pricing and Meaningful Underwriting Insights

Zurich, a global insurer, needed a better way to assess property risk and price policies more accurately using the UK’s vast external lidar data set. The company wanted to move beyond manual checks and slow, estimate-based underwriting, and used Snowflake to help process 300 billion data points from 10 TB of government lidar data.

With Snowflake’s H3 spatial indexing, Zurich turned lidar data into actionable underwriting insights, quickly analyzing building heights, roof types, and surrounding hazards such as flooding, wind damage, and falling trees. The result was near-instant property assessment, faster quote and onboarding processes, and improved pricing accuracy that helps Zurich reduce risk and attract customers who may have been overcharged elsewhere.

Zurich

Will Davis

Lead Machine Learning Engineer