Insurance fraud evaluation: a fuzzy expert system

All the studies dealing with the Italian insurance market show that fraud is an increasingly relevant problem in that sector. Insurance companies are trying to embed real "fraud units" into their activities, in order to identify suspicious cases and fraudulent patterns either in the insuring phase or in the settlement of claims. The companies face three opposing problems: the high cost of expert activity, requests for fast settlements and (for the Italian market) the requirement to cover anyone who asks for a policy. Carrying out any audit analysis requires fraud experts. That's the reason why fast settlement tends to generate extra costs in fraud investigations. What companies need is a standard, automatic, fast control method to filter real suspicious cases to fraud experts, leaving the call centres free to pay the majority of claims immediately. Unsuspicious claims can thus be settled automatically, even by the non-expert call centre operators, while claims that exceed a fixed threshold value are investigated by fraud experts. Claim auditors can then dedicate their activities to potentially fraudulent claims only. This paper shows how a fuzzy logic control (FLC) model can efficiently evaluate an "index of suspects" on each claim, in order to stress fraudulent situations to be investigated by the experts.