Abnormal Behavior Detection in Health Insurance Assessment Process

Every insurance company plays various roles and so implements many processes. One of the essential processes is the assessment which occurs due to investigating bills and claims and may lead to cost deduction based on fraud or limitation rules. This process may go forward in one or more steps by one or more assessors; some last some minutes, and others last more. This study tries to investigate actions, durations, assessors, and everything related to this process to help the insurer companies know useless steps, verify assessor’s behaviors, and make better decisions for the assessment process. This paper aims to demonstrate the methods and efforts of each mining rule and its strengths and weaknesses. The clustering and association rules mining are proposed for this objective. The gathered dataset has about 110,000 records from the Rasa web portal and is selected from an Iranian insurer company’s one-year indirect assessment process. The results show that some steps are useless, some assessors do not assess at an appropriate duration, and some bills consider several times with one assessor, which is suspicious behavior.