Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (21): 237-241.DOI: 10.3778/j.issn.1002-8331.1908-0165

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TLSTM-Based Medical Insurance Fraud Detection

CAO Luhui, QIN Fenglin, YAN Zhongmin   

  1. 1.Information Office, Shandong University, Jinan 250100, China
    2.School of Software, Shandong University, Jinan 250100, China
  • Online:2020-11-01 Published:2020-11-03



  1. 1.山东大学 信息化工作办公室,济南 250100
    2.山东大学 软件学院,济南 250100


Medical insurance fraud is a serious threat to the proper use of medical fund. With the development of information technology, more and more user attribute information and behavior information that make it possible to detect fraud by analyzing user behavior sequences are accumulated. However, in the context of medical insurance, fraudsters will try to imitate the behavior of legitimate users because of the serious information asymmetry between the supply and demand sides, and the proportion of fraudsters is small. The traditional classification-based fraud identification algorithm is no longer applicable. In addition, the patient’s medical behavior has certain sporadic and uneven time distribution. Aiming at the challenges of sample imbalance and uneven time distribution, this paper proposes a TLSTM-based medical insurance fraud identification framework, which takes the user’s historical medical treatment sequence as the input of the TLSTM model, predicts the reasons for the patient’s readmission and the diagnosis and treatment plan, and compares the model output with the user. The degree of difference in current medical treatment behavior to determine the possibility of fraud. Experiments show that the proposed algorithm is superior to the existing algorithm in fraud recognition accuracy.

Key words: TLSTM algorithm, fraud identification, behavioral pattern



关键词: TLSTM算法, 欺诈识别, 行为模式