Insurance Claims Fraud: Optimal Auditing Strategies in Insurance Companies

Insurance claims fraud is one of the major concerns in the insurance industry. According to many estimates, excess payments due to fraudulent claims account for a large percentage of the total payments affecting all classes of insurance. In this study, we develop a model framework based on a costly state verification setting in which, while policyholders observe the amount of loss privately, the insurance company can decide to audit incoming claims at some cost. In particular, optimization problems are formulated from both stakeholders' positions considering that for each of them willing to sign an insurance contract, certain participation constraints need to be fulfilled. Besides deriving analytical solutions regarding optimal auditing strategies, we provide a numerical approach based on Monte Carlo methods. The simulation results illustrate the acceptance range that consists of all valid fraud and auditing probability combinations both stakeholders are willing to tolerate. We discuss the impact of different valid probability combinations on the insurance company's and policyholder's objective quantities respectively and analyze the sensitivity of the acceptance range with respect to different input parameters