Journal of Finance and Accountancy An Analytical Approach To Detecting, Page 1 An Analytical Approach To Detecting Insurance Fraud Using Logistic Regression

Insurance fraud is a significant and costly problem for both policyholders and insurance companies in all sectors of the insurance industry. In this paper our focus is on auto insurance fraud, which occurs in both auto physical damage (APD-collision and comprehensive) and injury claims (Personal Injury Protection-PIP). We look at various situations within APD and PIP claims and various tactics that insured people use to defraud insurance companies. We then apply logistic regression as a statistical tool to help identify fraudulent claims. Insurance companies typically employ a claims investigation unit to investigate fraudulent activities. The investigation unit gathers supporting information to deny claims that are fraudulent, or to authorize payment to claims where there is insufficient supporting evidence to draw a fraud conclusion. By some industry estimates between 10 % and 15 % of all dollars spent on insurance premiums are spent supporting those that commit fraud. (Snider, 1996) Identifying and denying fraudulent claims may lead to increased corporate profitability and keep insurance premiums at a level below where they would be otherwise for insured’s