Data Mining Journal Entries for Fraud Detection: A Replication of Debreceny and Gray’s (2010) Techniques

Journal of Forensics and Investigative Accounting, Vol. 8(3) July-December 2016: 501-514

24 Pages Posted: 6 Feb 2016 Last revised: 10 Feb 2017

See all articles by Poh-Sun Seow

Poh-Sun Seow

Singapore Management University - School of Accountancy

Gary Pan

Singapore Management University - School of Accountancy

Themin Suwardy

Singapore Management University - School of Accountancy

Date Written: 2016

Abstract

There is limited published research to detect financial statement fraud using digital analysis to analyse journal entry data. As far as we are aware, Debreceny and Gray’s (2010) study is the first and only such study. In this study, we replicated and extended Debreceny and Gray’s (2010) work by examining generalizability of their techniques beyond subjects from USA. Besides Chi-Square test, we also explored the use of mean absolute deviation method during digital analysis. We found Debreceny and Gray’s (2010) techniques useful in facilitating cross-sectional analysis for journal entry data sets that are based on multiple organizations. Our results confirmed that their techniques offered a comprehensive and systematic way of applying digital analysis on journal entries in a new setting. Our analysis also found that researchers should not rely solely on Benford’s Law during digital analysis because of potential false alarms.

Keywords: fraud; journal entries; data mining; digital analysis; Benford’s Law

Suggested Citation

Seow, Poh-Sun and Pan, Gary and Suwardy, Themin, Data Mining Journal Entries for Fraud Detection: A Replication of Debreceny and Gray’s (2010) Techniques (2016). Journal of Forensics and Investigative Accounting, Vol. 8(3) July-December 2016: 501-514. Available at SSRN: https://ssrn.com/abstract=2728163

Poh-Sun Seow (Contact Author)

Singapore Management University - School of Accountancy ( email )

60 Stamford Road
Singapore, 178900
Singapore

HOME PAGE: http://accountancy.smu.edu.sg/faculty/profile/76099/SEOW-Poh-Sun

Gary Pan

Singapore Management University - School of Accountancy ( email )

60 Stamford Road
Singapore 178900
Singapore

Themin Suwardy

Singapore Management University - School of Accountancy ( email )

60 Stamford Road
Singapore 178900
Singapore

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