Aon chooses Zesty.ai for Property Risk Assessment & Insurance Underwriting

Artificial Intelligence News

Aon-chooses-Zesty.ai-for-Property-Risk-Assessment-Insurance-Underwriting Aon chooses Zesty.ai for Property Risk Assessment & Insurance UnderwritingAon, a London-based professional services company that specializes in risk, retirement, and health consulting, as per recent reports, has chosen Zesty.ai, a San Francisco, California-based AI-optimized property analytics service provider, to offer support on insurance underwriting.

The San Francisco-based Zesty.ai will be offering Aon access to 130 billion data points on buildings and their surroundings to make property risk assessments and pricing the property. Zesty’s AI-optimized data points engine gathers satellite and aerial imagery data, providing a holistic view of the property without ever setting foot on the premises.

According to George deMenocal, president and US CEO of Aon’s Reinsurance Solutions business, instant risk insights are critical for insurers as they scale up modernizing their insurance underwriting platforms.

And furthermore, Jobay Cooney, senior managing director and head of insurtech for Aon, explains that Zesty.ai, with its underwriting accuracy, inspection cost savings, and post-event claims analysis, is ideal for customer engagement.

Aon plans to provide its insurer customers a distribution network, which empowers insurers to make risk evaluations through Zesty.ai’s wildfire risk model, helping them with high fidelity property insights for insurance underwriting, which includes both catastrophic and attritional risk. Moreover, Aon’s Impact Forecasting team, which assessed the recent California wildfires said that the wildfire resulted in insured losses of $16 billion in 2017 and up to $18 billion in 2018. Aon, reckoning wildfire as a challenging model, says fire hazard severity zone maps lack the level of granularity that’s needed for the physical attribution of properties, for insurers to accurately price each risk. Zesty.ai’s new wildfire model (Z-FIRE) addresses this granularity challenge by leveraging the machine learning technology to combine property details.