ZestyAI, a risk decision platform for the insurance industry, has confirmed that regulators in more than 20 US states have accepted its Z-WATER™ model for non-weather water risk, allowing carriers to use the tool in their rate and rule filings.
Recent approvals include Nevada, Oregon, Ohio, South Carolina and Oklahoma, adding to a growing list of states permitting insurers to apply the model when pricing policies.
The approvals let carriers assess non-weather water exposure at the level of individual properties rather than relying on broader regional assumptions, with ZestyAI stating the tool delivers 18 times sharper risk segmentation than conventional methods based on territory and property age.
Non-weather water damage has become the fourth most expensive cause of loss in home insurance, generating in excess of $15bn each year from more than a million claims, while the average cost per claim has climbed by 80%, it said. ZestyAI noted such losses typically stem from everyday issues within a property, such as a burst pipe, ageing plumbing, a faulty appliance or a concealed leak, which can cause extensive damage before being noticed.
According to ZestyAI, insurers have long struggled to identify which properties carry the greatest exposure to water damage, since conventional underwriting tends to depend on wide geographic zones, the age of a building and other indirect indicators that can mask real differences between comparable homes.
Z-WATER aims to close this gap by assessing risk at the level of a single property. The model, trained and tested against insurers claims data, applies computer vision to aerial imagery and considers how a property’s characteristics, permit records, local climate patterns and surrounding infrastructure combine to influence both how often and how severely non-weather water claims occur.
ZestyAI senior director of regulatory and government affairs Bryan Rehor said, “Non-weather water losses place real pressure on carriers’ books, but they’re also highly preventable when you understand where the risks actually lie. The growing regulatory acceptance of Z-WATER reflects a broader shift toward models that can identify meaningful differences in risk from one home to the next while providing the transparency regulators expect.”
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