Abstract. Process-Based Fraud (PBF) is fraud enabled by process deviations that
occur in business processes. Several studies have proposed PBF detection
methods; however, false decisions are still often made because of cases with low
deviation. Low deviation is caused by ambiguity in determining fraud attribute
values and low frequency of occurrence. This paper proposes a method of
detecting PBF with low deviation in order to correctly detect fraudulent cases.
Firstly, the fraudulence attributes are established, then a fuzzy approach is
utilized to weigh the importance of the fraud attributes. Further, multi-attribute
decision making (MADM) is employed to obtain a PBF rating according to
attribute values and attribute importance weights. Finally, a decision is made
whether the deviation is fraudulent or not, based on the PBF rating. Experimental
validation showed that the accuracy and false discovery rate of the method were
0.92 and 0.33, respectively.