An ANN-based auditor decision support system using Benford's law

Bhattacharya, Sukanto, Xu, Dongming and Kuldeep, Kumar (2011) An ANN-based auditor decision support system using Benford's law. Decision Support Systems, 50 3: 576-584. doi:10.1016/j.dss.2010.08.011

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Author Bhattacharya, Sukanto
Xu, Dongming
Kuldeep, Kumar
Title An ANN-based auditor decision support system using Benford's law
Journal name Decision Support Systems   Check publisher's open access policy
ISSN 0167-9236
Publication date 2011-02
Year available 2010
Sub-type Article (original research)
DOI 10.1016/j.dss.2010.08.011
Open Access Status
Volume 50
Issue 3
Start page 576
End page 584
Total pages 9
Place of publication Amsterdam, The Netherlands
Publisher Elsevier
Collection year 2011
Language eng
Abstract While there is a growing professional interest on the application of Benford's law and "digit analysis" in financial fraud detection, there has been relatively little academic research to demonstrate its efficacy as a decision support tool in the context of an analytical review procedure pertaining to a financial audit. We conduct a numerical study using a genetically optimized artificial neural network. Building on an earlier work by others of a similar nature, we assess the benefits of Benford's law as a useful classifier in segregating naturally occurring (i.e. non-concocted) numbers from those that are made up. Alongside the frequency of the first and second significant digits and their mean and standard deviation, a posited set of 'non-digit' input variables categorized as "information theoretic", "distance-based" and "goodness-of-fit" measures, help to minimize the critical classification errors that can lead to an audit failure. We come up with the optimal network structure for every instance corresponding to a 3 × 3 Manipulation-Involvement matrix that is drawn to depict the different combinations of the level of sophistication in data manipulation by the perpetrators of a financial fraud and also the extent of collusive involvement. © 2010 Elsevier B.V. All rights reserved.
Keyword ANNs
Auditor decision support system
Benford's law
Genetic optimization
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Available online 18 August, 2010.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2011 Collection
UQ Business School Publications
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Citation counts: TR Web of Science Citation Count  Cited 7 times in Thomson Reuters Web of Science Article | Citations
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Created: Tue, 14 Dec 2010, 15:14:15 EST by Karen Morgan on behalf of UQ Business School