Theoretical Foundations of Climate Risk Actuarial Modelling for African Insurance Markets

This study develops a theoretical framework for climate risk actuarial modelling specifically designed for African insurance markets, with empirical application to Nigerian agricultural and property insurance loss data. Conventional catastrophe risk models used by global reinsurers are built on European and North American historical loss experience and climate physical models that have limited accuracy in African climatic systems. For African insurers and governments seeking to manage climate-related risks, an appropriate local actuarial framework is both practically necessary and theoretically distinct from existing international approaches. This study proposes a climate-conditional loss model framework that integrates IPCC regional climate projection outputs, local hazard intensity functions calibrated to Nigerian meteorological data, exposure vulnerability curves developed from household surveys and property damage assessments, and Bayesian updating mechanisms for incorporating new climate observational data. The framework is applied to flood and drought loss estimation for Nigeria's six geopolitical zones using historical loss data from NEMA and NAIC for 2000 to 2023. Stochastic uncertainty decomposition separates natural variability, parameter, and climate scenario uncertainty in loss projections. Findings demonstrate that climate trend adjustment materially changes 50-year return period loss estimates for all zones, with upward revisions of 35 to 65 percent in flood loss projections compared to stationary historical models. The study contributes an original African climate risk actuarial framework and calibrated Nigerian hazard model, recommending adoption by NAICOM as the reference framework for climate risk capital requirements.

Keywords: climate risk, actuarial framework, Africa, catastrophe modelling, Bayesian updating.