Milliman Analyzes ZestyAI’s Z-HAIL Model
Milliman Analyzes ZestyAI’s Z-HAIL Model
In a whitepaper commissioned by ZestyAI, Milliman performed an analysis of how ZestyAI’s Z-HAIL risk score could be used to identify property risk exposure to hail. To test the effectiveness of the model, Milliman used historical Texas loss experience from an insurance company, along with data from ZestyAI’s Z-HAIL model. Z-HAIL uses a variety of climatological data and property-specific attributes to understand and measure a property’s exposure to hail risk.
Milliman Analyzes ZestyAI’s Z-HAIL Model
Modernizing Homeowners Rate Plans in the Age of Changing Climate Risk
BackgroundIn a whitepaper commissioned by ZestyAI, Milliman performed an analysis of how ZestyAI’s Z-HAIL risk score could be used to identify property risk exposure to hail. To test the effectiveness of the model, Milliman used historical Texas loss experience from an insurance company, along with data from ZestyAI’s Z-HAIL model. Z-HAIL uses a variety of climatological data and property-specific attributes to understand and measure a property’s exposure to hail risk.
ResultsMilliman's analysis showed that ZestyAI’s Z-HAIL risk score could be used to segment properties based on exposure to hail risk. Over a period of seven years, properties with a Z-HAIL score of 10 had a reported loss ratio of 50.4% compared to only 2.4% for properties with a Z-HAIL score of 1, which corresponds to a highest to lowest loss ratio lift of 21X.
In addition, Milliman found that ZestyAI’s Z-HAIL property-level risk model also improved the insurance company’s ability to segment the risk more granularly than county or zip-code based territories, recognizing the difference in risk exposure within small geographical areas.
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