Quantifies impact of model assumptions on reinsurance pricing metrics, suggesting strategic trade-offs for climate change adaptation.
Using a representative multiperil catastrophe model applicable to a US nationwide industry portfolio, this paper quantifies the sensitivity of reinsurance technical pricing metrics to model assumptions. We show that shifting risk profiles from low to high catastrophe excess of loss layers (or vice versa) involves clear trade-offs. These trade-offs are useful in formulating strategy under climate change. Our findings are applicable to reinsurers whose portfolios mimic a proportional slice of the US nationwide industry portfolio, but the framework developed here can also be applied to general cases. Additionally, this work yields insights into recent property catastrophe market dynamics.
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Khare et al. (2026) studied this question.
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