Research on Extreme Weather Risk Management Based on Gray Prediction and Multi-Criteria Evaluation Models

Abstract

This study investigates the growing challenges faced by the insurance industry due to extreme weather events and climate change, with a focus on the widening global insurance gap. We propose a novel dual-model approach to address these complex issues. First, we develop a Gray Prediction-Based Risk Assessment Framework (GPRAF) that integrates multidimensional data on natural disasters, economic development, population dynamics, and agricultural trends. This framework enables insurance companies to make more informed underwriting decisions in the context of increasing climate-related risks. Through case studies in Japan and Mexico, we demonstrate the practical applications and implications of our approach. Our research contributes to the growing body of literature on climate risk management in the insurance sector and provides valuable insights for policymakers and industry practitioners. By bridging the gap between risk assessment and community preservation needs, this study offers a holistic perspective on adapting insurance strategies to the challenges of climate change while preserving community values.