How Top Insurers Navigate the Escalating Risk of Severe Storms
Key Insights:
Enhanced Risk Segmentation: Z-HAIL and Z-WIND models delivered a 99.7% hit rate, enabling the insurer to identify high-risk properties and reduce exposure.
Strategic Application: Implementing across underwriting and rating, applying ACV endorsements, and adjusting deductibles reduced the combined ratio by over 4 points in the first year.
Localized Risk Management: The models identified intra-territory risk variability, allowing for more precise decision-making even within a zip code.
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Gain deeper insights into how advanced predictive models can support your risk management strategies.
This case study highlights the potential of AI-powered models in addressing the growing risks associated with severe convective storms.
By adopting ZestyAI’s innovative approach, the insurer was able to better manage their portfolio and navigate the complexities of an increasingly volatile climate.
Severe convective storms are becoming more frequent and intense, challenging the effectiveness of traditional risk models.
Case Study
This case study shows how a national insurer leveraged ZestyAI’s models to enhance risk management, resulting in significant financial improvements.
The Challenge:
Insights from a 5-year retrospective on ZestyAI’s models in action
