Publication Type
Journal Article
Publication Date
7-2016
Abstract
The alarming frequency of fraud occurrences suggests that corporations continue to face persistent threat of fraud (Cecchini et al., 2010a; Summers and Sweeney, 1998). According to Association of Certified Fraud Examiner (ACFE)’s 2014 Report, a typical organization may lose five percent of its revenue to fraud every year. As such, the consequences of fraud may impact the shareholders, creditors, auditors and the public’s confidence in the integrity of corporations’ financial systems (Rezaee, 2005).
Keywords
fraud, journal entries, data mining, digital analysis, Benford’s Law
Discipline
Accounting | Corporate Finance
Research Areas
Accounting Information System
Publication
Journal of Forensic and Investigative Accounting
Volume
8
Issue
3
First Page
501
Last Page
514
ISSN
2165-3755
Publisher
National Association of Certified Valuators and Analysts
Citation
SEOW, Poh Sun; PAN, Gary; and SUWARDY, Themin.
Data mining journal entries for fraud detection: A replication of Debreceny and Gray's (2010) techniques. (2016). Journal of Forensic and Investigative Accounting. 8, (3), 501-514.
Available at: https://ink.library.smu.edu.sg/soa_research/1515
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