Using Rule Technology for Fraud Prevention in Government Insurance

In respect of the frequent fraud cases of social insurance by government organizations, the inspection procedure usually relies on experts’ experience for verification and experienced personnel in charge for checking. However, due to the heavy work load and the insufficiency of manpower and lack of experience, the ratio of miscarriages of justice is very high, leading to improper settlement of claims and the waste of social resources. In this paper, we employ rule technology to improve the above inefficiency. We employ a knowledge engineering methodology to analyze the problem and construct the knowledge model, including the domain schema and rules. We then implement the knowledge model along with the existing database applications. The benefits generated by the research are: (1) establishing a knowledge system with expertise reasoning to solve the review problems of massive cases, (2) significantly reducing the large labor cost and consumed time of the existing reviewing system, and (3) improving the application level of traditional database in the expert reasoning system.