NDLI: Forensic Audit Using Process Mining to Detect Fraud

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Forensic Audit Using Process Mining to Detect Fraud

Content Provider	Scilit
Author	Bahaweres, Rizal Broer Trawally, Jainaba Hermadi, Irman Suroso, Arif Imam
Copyright Year	2021
Description	Journal: Journal of Physics: Conference Series 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.
Related Links	https://iopscience.iop.org/article/10.1088/1742-6596/1779/1/012013/pdf
ISSN	17426588
e-ISSN	17426596
DOI	10.1088/1742-6596/1779/1/012013
Journal	Journal of Physics: Conference Series
Issue Number	1
Volume Number	1779
Language	English
Publisher	IOP Publishing
Publisher Date	2021-02-01
Access Restriction	Open
Subject Keyword	Journal: Journal of Physics: Conference Series Information Systems Process Mining Detect Fraud
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy

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