AI tackles the $208B problem of catastrophic storms: Allianz

Over the past three years, severe convective storms (SCS) totaled $208 billion in global insured losses, according to Allianz's latest severe convective storms analysis. Insurers have met this challenge by adapting and upscaling AI technologies in natural catastrophe model validation and refinement. 

While historically categorized as secondary perils, the surge in frequency and severity of SCSs involving wind, hail and tornadoes have established them as a significant driver for annual insured losses.

Allianz attributes the increase in SCS-related losses to several factors, including population growth and development into hazard-prone areas, aging infrastructure, inflation and the degradation of natural ecosystems. 

AI-driven natural catastrophe models can process large amounts of unstructured data to create highly granular analyses of risk exposures via satellite imagery, assessing factors such as roofing and construction aging patterns, vegetative exposure and local climate data, according to Allianz's industry analysis.

"As AI becomes embedded in core risk processes, its most meaningful benefit for customers is its ability to support smarter, evidence-based resilience strategies that adapt to changing weather patterns, rather than relying on historical norms," said Michael Bruch, global head of risk advisory consulting services at Allianz Commercial, in the press release."A data and AI-driven risk management approach is the future and will be essential for organizations aiming to thrive in an increasingly volatile climate environment."

A 2024 survey from property risk platform ZestyAI found that one in four insurers currently use AI to assess SCS risk exposures. Of the property and casualty executives surveyed, 73% say they believe that AI models will help to better manage climate-related losses and that carriers who adopt AI models will come out ahead of those who do not.