Insurers are expanding their use of aerial imagery and AI-derived property data to track how roofs and other exterior materials deteriorate between major weather events. While catastrophe models estimate what hurricanes, hail, floods and other hazards could do, property-condition data can show what was already happening to a structure before a loss. That distinction could give carriers a more current view of risk at underwriting, renewal and claim.
An analysis of more than 2.8 billion AI-derived roof observations across nearly 2,100 U.S. counties found links between chronic weather exposure and roof longevity. Counties with the largest daily temperature swings showed roof aging about 23% faster than areas with more stable climates, while hotter and more humid regions generally had shorter roof lifespans. The analysis also found a large expansion in U.S. areas experiencing the highest rainfall intensity between the early 1980s and early 2020s.
For claims adjusters, more frequent property observations could provide useful evidence when evaluating pre-loss condition and causation. Historical imagery may help establish whether roof deterioration, moisture-related problems or other conditions were present before a reported storm loss. Comparing observations taken at different points in time could also help adjusters separate gradual deterioration from damage associated with a specific event.
The data could also create a stronger connection between underwriting, risk management and claims. Carriers may be able to identify properties deteriorating faster than expected, address vulnerabilities before losses occur and preserve condition information that later supports claim investigations. As climate exposure changes, understanding the condition of an individual property before severe weather arrives may become as important as modeling the catastrophe itself.
