Climate and property risk analytics provider ZestyAI has launched Z-WATER, a new AI-driven model designed to predict the frequency and severity of non-weather water and freeze claims for properties across the US.
This development comes as non-weather water claims continue to be the third-leading cause of insurance losses nationwide, highlighting the need for a property-specific predictive model.
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So far, insurers have faced challenges in accurately assessing and mitigating the risk of non-weather water damage on an individual property basis, outlines ZestyAI.
Z-WATER aims to address this gap by incorporating property-specific construction and architectural details, local infrastructure and water distribution networks into its assessments, providing a holistic understanding of risk.
According to the vendor, ZestyAI’s new model is poised to assist the insurance industry in setting fair rates and lowering risks with preventative measures such as deploying water sensors at high-risk properties.
It is also said to enhance operations by prioritising inspections at vulnerable properties.
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By GlobalDataZ-WATER has been trained, tested and validated on a vast catalogue of actual insurance loss data from various carriers across the country.
ZestyAI co-founder and chief product officer Kumar Dhuvur commented on the current landscape of non-weather water claims, noting: “The landscape of non-weather water claims is shifting, with a concerning trend towards increased claim severity.”
He highlighted factors such as the increasing cost of building materials and labour, as well as the design of modern homes, which contribute to higher costs when water damage occurs.
ZestyAI offers a range of products for property risk assessment, including models for wildfire, hail, wind and severe convective storms.
Last year, the company expanded its capabilities by integrating with Cytora, a digital risk processing platform, to enhance commercial insurance underwriters’ assessment of climate-related risks.
