Process Mining and Fraud Detection
نویسندگان
چکیده
A case study on the theoretical and practical value of using process mining for the detection of fraudulent behavior in the procurement process Abstract This thesis presents the results of a six month research period on process mining and fraud detection. This thesis aimed to answer the research question as to how process mining can be utilized in fraud detection and what the benefits of using process mining for fraud detection are. Based on a literature study it provides a discussion of the theory and application of process mining and its various aspects and techniques. Using both a literature study and an interview with a domain expert, the concepts of fraud and fraud detection are discussed. These results are combined with an analysis of existing case studies on the application of process mining and fraud detection to construct an initial setup of two case studies, in which process mining is applied to detect possible fraudulent behavior in the procurement process. Based on the experiences and results of these case studies, the 1+5+1 methodology is presented as a first step towards operationalizing principles with advice on how process mining techniques can be used in practice when trying to detect fraud. This thesis presents three conclusions: (1) process mining is a valuable addition to fraud detection, (2) using the 1+5+1 concept it was possible to detect indicators of possibly fraudulent behavior (3) the practical use of process mining for fraud detection is diminished by the poor performance of the current tools. The techniques and tools that do not suffer from performance issues are an addition, rather than a replacement, to regular data analysis techniques by providing either new, quicker, or more easily obtainable insights into the process and possible fraudulent behavior. iii Occam's Razor: " One should not increase, beyond what is necessary, the number of entities required to explain anything " iv Contents
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