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ZestyAI Wins Z-WATER Approval in More Than 20 US States

1 reports · First detected 2026-08-15 · Last active 2026-08-15

Non-weather water damage from burst pipes, appliance failures and hidden leaks is a major source of US homeowners-insurance losses, costing carriers more than $13 billion annually. Conventional pricing often relies on broad territory and property-age proxies that can miss sharp differences between neighboring homes. ZestyAI’s Z-WATER uses verified claims, property characteristics, permit records, localized climate data and infrastructure conditions to estimate both the frequency and severity of losses at an individual address.

As of August 2026, insurance regulators in more than 20 US states had cleared Z-WATER for underwriting and rating, expanding from its first approval by Wisconsin regulators on Sept. 25, 2025. ZestyAI said the model provides 18 times the risk segmentation of traditional approaches. The approvals allow carriers to incorporate property-level scores into pricing, inspections and mitigation programs, including the targeted deployment of smart water sensors, while giving regulators visibility into the factors behind each assessment.

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ZestyAI Enters London Market in MAP Underwriting Deal2026-07-24 · 1 reports · similarity 0.84

Rising wildfire losses are pushing insurers and reinsurers to seek more granular data for underwriting, pricing and capital allocation. ZestyAI, a U.S. insurance risk-decision platform, uses artificial intelligence and high-resolution property data to assess exposure to climate-related hazards. Its Z-FIRE model is designed to help carriers distinguish risk at the individual-property level as wildfire threats intensify.

ZestyAI has agreed to provide Z-FIRE to Lloyd’s of London managing agency MAP Underwriting for its California property reinsurance business. The partnership marks ZestyAI’s first expansion outside the United States and gives the company an entry point into the London insurance market. The parties did not disclose financial terms, the signing date or a timetable for full deployment.

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