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Winning the Fight Against Non-Weather Water Losses with AI

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"Winning the Fight Against Non-Weather Water Losses with AI"

Non-weather water damage is a top peril eroding profitability for insurers, and traditional risk models fall short. This guide explores how AI-powered, property-level data can improve underwriting, pricing accuracy, and proactive risk mitigation.

Non-weather water damage is the fourth costliest peril in homeowners' insurance, with claim severity up 80% over the past decade. Traditional models that rely on broad geographic data often miss the key drivers, leading to mispriced policies and rising loss ratios. 

This guide explores how AI-powered risk modeling helps insurers break that cycle. With predictive analytics and property-level data, carriers can segment risk with greater precision, improve pricing accuracy, and proactively mitigate future claims.

Download the guide and learn:

  • Why claim severity is rising while frequency remains steady
  • The overlooked property traits that are strong predictors of loss
  • How AI can improve risk prediction accuracy by up to 15x
  • Strategies to optimize pricing, inspections, and mitigation efforts


Offered Free by: ZestyAI
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