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Lusk, EJ and Halperin, M (2014)

Using the Benford Datasets and the Reddy and Sebastin Results to Form an Audit Alert Screening Heuristic: An Appraisal

The IUP Journal of Accounting Research and Audit Practices, vol. XIII, issue 3, pp. 56-69.

ISSN/ISBN: Not available at this time. DOI: Not available at this time.



Abstract: Digital Frequency Testing (DFT) is a simple and potentially effective tool that can be used efficiently in the certification audit as well as in the service of forensic investigations to rationalize the use of extended audit procedures at the substantive phase of the audit. To further the hegemony of DFT, this paper summarizes certain aspects of the excellent treatment of DFT offered by Reddy and Sebastin (2012). In the following, the paper takes up the development of a Benford Screening Window (BSW) that can be employed to create alerts as to when datasets under audit examination do not seem to conform to the DFT profile as corrected from the Benford (1938) paper. The BSW is tested vis-à-vis the log10expectation function, two accounting industry datasets downloaded from COMPUSTATTM, and the 12 years of in-kind committee contributions dataset developed by Reddy and Sebastin (2012). The paper finds a reasonable fit for these datasets for the BSW and hence suggests an overall calibration cut-off taken from the results obtained by passing the Reddy-Sebastin datasets through the BSW. In this paper, the authors have programmed an ExcelTMVBAâ driven Decision Support System (DSS) to aid in the creation of these audit alerts which is available for free as a download with no restriction on its use.


Bibtex:
@ARTICLE{, title = {Using the Benford Datasets and the Reddy and Sebastin Results to Form an Audit Alert Screening Heuristic: An Appraisal}, author = {Lusk, Edward J and Halperin, Michael}, year = {2014}, journal = {The IUP Journal of Accounting Research and Audit Practices}, volume = {XIII}, number = {3}, pages = {56--69}, url = {http://EconPapers.repec.org/RePEc:icf:icfjar:v:13:y:2014:i:3:p:56-69} }


Reference Type: Journal Article

Subject Area(s): Accounting