Overview
UrbanStat improves P&C insurance companies loss ratios by up to 7 points using geospatial analytics and machine-learning risk scoring.
Key Features
1.) Machine-Learning Risk Scoring: a risk-scoring algorithm for the risk selection process which has lowered loss ratios on average by 3 to 7 points. The algorithm is learning from insurance carriers' historical policy+claims information and also external data-sets that we have sourced to provide insurance companies with a predictive risk-selection score for new and renewal policies.
2.) Visualization: see your portfolio visually (total insured value heat maps, distance to coast, fire department response time maps, etc.) and draw polygons/shapes around specific areas to set underwriting parameters.
3.) External Data-Sets: see up to 30 sourced data points for an address/policy including crime, flood, tornadoes, sinkhole, and year built to name a few.
4.) Real-Time weather event tracking: see real-time weather events such as hurricanes overlaid onto your portfolio to see which policies will be affected in just a few seconds.
Key Benefits
Loss ratio improvement by 3 to 7 points.