Development of the Fraud Detection Model for Injury in National Health Insurance using Data Mining -Focusing on Injury Claims of Self-employed Insured of National Health Insurance
Il-Su Park, So-Jeong Park, Jun‐Tae Han, Sung-Hong Kang · Journal of Digital Convergence · 2013
According to increasing number of injury claims, the challenge is reducing investigation of cases of injuries by selecting them more delicately, while also increasing the redemption rates and the amount of restitution. In this regards, we developed the fraud detection model for injury claims of self-employed insured by using decision tree after collecting medical claim data from 2006 to 2011 of the National Health Insurance in Korea. As a result of this model, subject types were classified into 18 types. If applying these types to the actual survey compared with if not applying, the redumption collecting rate will be increasing by 12.8%. Also, the effectiveness of this model will be maximize when the number of claims handlers considering their survey volume and management plans are examined thoroughly.