Risk Assessment and Insurance Underwriting Decision Model: A Case Study of Gansu Province and Florida
DOI:
https://doi.org/10.54097/h55frr36Keywords:
Extreme weather, Insurance, Analytic Hierarchy Process, Exponentially Weighted Harmonic mean.Abstract
Extreme weather is driving up economic losses and insurance costs, underscoring the urgency for enhanced disaster risk management and policy reform for sustainability. This study presents a novel Risk Assessment Model for analyzing insurance underwriting risk in specific regions, driven by the increasing economic losses and insurance costs due to extreme weather. The model integrates a comprehensive evaluation system with four primary and twelve secondary indices, applying the Entropy Weighting Method (EWH) and Analytic Hierarchy Process (AHP) to allocate weights and quantify risk (Q_unfavourable) effectively. It also adopts the As Low as Reasonably Practicable (ALARP) principle for setting underwriting decision thresholds, based on risk and profitability. Case studies from Gansu Province, China, and Florida, USA, validate the model's practicality and its potential to enhance insurers' underwriting strategies and policy decisions across varied regions, marking a significant improvement in underwriting risk management and strategic insurance policy formulation.
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