The devastating impact of Hurricanes Helene and Milton in 2024 underscored the need for climate risk for insurers to reassess their risk management strategies in the face of increasingly extreme weather events. Helene struck North Carolina with force, causing widespread damage across 39 counties. Nearly half of the state’s small businesses were affected, and over a million residents faced disruptions to their daily lives. Recovery efforts involved significant mobilization, including the National Guard delivering more than 13,500 tons of humanitarian aid and assisting in restoring critical infrastructure such as water and electricity.
In Florida, Hurricane Milton unleashed destruction in areas like Tampa and St. Petersburg. Severe flooding and prolonged power outages left many homeowners and small businesses struggling, highlighting their vulnerability and the financial strain caused by such disasters.
As these catastrophic events become more frequent, it’s no surprise that 25% of U.S. property and casualty insurers are now turning to AI to improve their ability to predict and respond to extreme weather risks. This statistic comes from a survey of 200 top insurance executives conducted by ZestyAI, a provider of climate and property risk analytics.
Adapting to the Storm: How Insurers Leveraged AI During Major Weather Events
AI is proving invaluable not only for aiding customers during crises but also for enhancing catastrophe risk management. Following the devastation caused by Hurricanes Helene and Milton, insurers faced the challenge of handling over 400,000 claims, as reported by Florida’s Office of Insurance Regulation. By utilizing AI, insurers were able to forecast storm impacts and expedite claims processing, demonstrating the technology’s critical role in serving policyholders effectively.
Here are some examples of how leading insurers employed AI to their advantage:
USAA: This insurer adopted advanced AI-driven claims processing to significantly reduce the time it took to deliver funds to policyholders. Drones were deployed to assess damages in hard-to-reach areas, enabling faster inspections and repairs. This approach helped affected individuals and families recover more quickly.
Zurich North America: Zurich took a proactive stance by using AI-based risk modeling to predict hurricane impacts before they occurred. This allowed them to scale up staffing, deploy emergency response teams, and prepare for the surge in claims. The strategy optimized their operations during critical times.
Zurich’s CATIA Tool: Zurich also utilized its AI-powered tool, CATIA, to transform the way catastrophe claims were handled. CATIA streamlined the tagging of claims by analyzing loss causes and descriptions within minutes, improving the efficiency of reinsurance recoveries. According to Christian Westermann, Zurich’s Group Head of AI, CATIA combines traditional AI techniques with generative AI, enabling it to interpret unstructured and ambiguous claims data effectively.
