ZestyAI, a provider of AI-driven insurance risk analytics, has announced that regulators in Minnesota and Maryland have approved Z-WATER™, its AI-powered non-weather water risk model, for use in carrier rate and rule filings.
ZestyAI’s Z-WATER™ is now accepted for rating and underwriting in 22 states.
Non-weather water has become the fourth-costliest peril in homeowners insurance, accounting for more than $15 billion in annual losses across more than one million claims. These losses often stem from everyday incidents such as burst pipes, plumbing deterioration and appliance failures. However, traditional rating approaches, which rely heavily on geographic territories and property age, provide limited insight into which individual homes are most susceptible to these losses.
To address this, Z-WATER combines computer vision, aerial imagery, property characteristics, permitting history, localised climatology and infrastructure context to predict the frequency and severity of non-weather water claims.
Trained and validated using insurer loss data, the model delivers 18x risk segmentation lift compared with traditional territory- and age-based approaches, enabling insurers to more accurately differentiate risk across their portfolios.
Bryan Rehor, Senior Director of Regulatory and Government Affairs at ZestyAI, said, “The continued expansion of Z-WATER’s regulatory footprint reflects growing recognition that non-weather water risk can be assessed with far greater precision than traditional methods allow.
“With each new approval, more carriers have a pathway to incorporate property-level insights into their rating strategies, helping them better distinguish risk across the homes they insure.”
The latest approvals build on ZestyAI’s broader regulatory momentum. In September, the company surpassed 500 regulatory approvals across 317 carrier rate and rule filings in 44 states, spanning models for wildfire, severe storms, hail, wind, non-weather fire, non-weather water and property intelligence.
The approvals also expand the opportunities for insurers to incorporate property-level risk insights into their pricing strategies, helping align pricing more closely with the characteristics and exposures of individual properties.
