Hybrid Multi-Criteria Decision-Making

Prioritizing Risk Level Factors in Comprehensive Automobile Insurance Management: A Hybrid Multi-Criteria Decision-Making Model

: Authors

Simone Domenico Scagnelli , Meisam Ranjbari , Zahra Shams Esfandabadi

: Abstract

Predicting the risk level of newly proposed insurance policies, usually conducted based on historical data gathered from previously issued policies, is a vital activity for insurance companies. In the motor insurance market, evidence shows that most insurance companies around the World consider personal and behavioural characteristics of the driver(s) as well as the vehicle attributes when assessing their risk and therefore, price their policies accordingly. However, in Iran, motor insurance policies are assessed only based on the vehicle characteristics without accounting for the drivers’ attributes and driving history resulting in unfair pricing in most of the cases. Therefore, to identify and prioritize the important factors in the ratemaking of comprehensive automobile insurance policies, we propose a two-phase model based on Fuzzy Delphi Method (FDM) and Fuzzy Analytic Hierarchy Process (FAHP). Additionally, Similarity Aggregation Method (SAM) has been applied to combine the individual fuzzy opinions of the surveyed experts into a group fuzzy consensus opinion. The results of the empirical study provide the ranking of the relevant risk factors that can support decision and policy makers, helping insurance companies in assessing the risks more accurately, and be useful in designing more effective insurance proposals.