When the historical data your models are trained on no longer reflects the physical reality of current and future risk, the models are telling you something important: they need to be rebuilt.
Climate pattern shifts are altering the frequency and severity distributions of natural perils in ways that historical loss experience, however extensive, may not capture. Wildfire in previously low-risk areas, secondary perils producing losses previously associated only with major named storms, and compounding drought-then-flood sequences are straining model assumptions.
Forward-looking climate science is increasingly being integrated into catastrophe models, supplementing historical data with physical climate projections. The challenge is translating climate science uncertainty into probability distributions that actuaries and underwriters can work with practically.
Carriers that engage directly with catastrophe model vendors on climate integration and develop internal validation processes for climate-adjusted outputs will be better positioned than those who accept vendor outputs without scrutiny.
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