Fuzzy MADM Approach for Rating of Process-Based Fraud
Process-Based Fraud (PBF) is fraud enabled by process deviations thatoccur in business processes. Several studies have proposed PBF detectionmethods; however, false decisions are still often made because of cases with lowdeviation. Low deviation is caused by ambiguity in determining fraud attributevalues and low frequency of occurrence. This paper proposes a method ofdetecting PBF with low deviation in order to correctly detect fraudulent cases.Firstly, the fraudulence attributes are established, then a fuzzy approach isutilized to weigh the importance of the fraud attributes. Further, multi-attributedecision making (MADM) is employed to obtain a PBF rating according toattribute values and attribute importance weights. Finally, a decision is madewhether the deviation is fraudulent or not, based on the PBF rating. Experimentalvalidation showed that the accuracy and false discovery rate of the method were0.92 and 0.33, respectively.
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