Forensic Audit Using Process Mining to Detect Fraud

Abstract

Companies have been involved in scandals relating to financial fraud which present a large financial loss to their stakeholders. As high technology devices and online systems makes accounting transactions more complicated and easier to manipulate, process mining techniques to detecting fraud are under intense scrutiny by forensic auditors. The author analyses data of a Dutch Financial institute proposed by the Business Process Intelligence Challenge (BPIC) 2017, the BPIC provides a real life event logs. The process consists of 193849 events and 42995 cases. Various tools such as ProM (Process Mining) are been used for data analysis. The author choose process mining over other techniques because the data is recorded independently from the auditee, it an automated solution, less prone to human error, and less time consuming.