Fraud detection is an important issue in service industries. Its technical challenges include the existence of complex patterns, its multivariate nature, and the incompleteness of records. As similar problems are observed in batch manufacturing process analysis, existing batch manufacturing techniques can be adapted and mapped to the fraud detection problem in the service sector. In particular, the batch library method can be modified to incorporate new information into incomplete customer records for analysis, while controlling the overall type I error rate. A real case is used to demonstrate the effectiveness of this approach, and simulation results are presented to show that the proposed approach consistently outperforms existing approaches.
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