IS BENFORD’S LAW EFFECTIVE IN FRAUD DETECTION FOR EXPENSE CYCLE?

Year 2020, , 316 - 326, 31.12.2020

Emre Ergin İlkay Ejder Erturan

https://doi.org/10.14780/muiibd.854444

Abstract

Despite measures taken by firms to prevent fraud, it has been found in recent studies that losses derived
from fraudulent activities are increasing on a global basis. International standards on auditing do not define
which analytical approaches and technological tools to be used in performing audit. Decisions are left
on the auditor’s judgment. Auditors try to use digital techniques to deal with mass data sets generated
by firms. Academic research may mislead practitioners as controversial outcomes exist in literature
concerning empirical research. Benford’s Law (BL) is one of the methods used frequently in digital analysis.
Although some researchers defend the use of BL in audit, especially in fraud detection, this paper disputes
its effectiveness for expense cycle. Different firm’s data are tested to conclude that the use of BL is not
appropriate for expense items. The reasons of this deficiency are explained in this paper.

Keywords

Benford’s Law, Audit, Fraud, Expense Cycle

References

• ACFE (2020). Report to the Nations: 2020 Global Study on Occupational Fraud and Abuse. Austin, USA: Association of Certified Fraud Examiners. Retrieved from https://acfepublic.s3-us-west-2.amazonaws.com/2020-Report-to-the-Nations.pdf
• BAMEY, B.B., Schulzke, K.S. (2016). Moderating “Cry Wolf ” events with excess MAD in Benford’s law research and practice, Journal of Forensic Accounting Research, 1(1): A66–A90. https://doi.org/10.2308/jfar-51622
• BEARDSLEY, E.L., Lassila, D.R., Omer, T.C. (2018). How Do Audit Offices Respond to Audit Fee Pressure? Evidence of Increased Focus on Nonaudit Services and their Impact on Audit Quality, Contemporary Accounting Research, 36(2): 999-1.027. https://doi.org/10.1111/1911-3846.12440
• BELLA, B., Eloff, J.H., Olivier, M.S. (2009). A fraud management system architecture for next-generation networks, Forensic Science International, 185(1): 51-58. DOI:10.1016/j.forsciint.2008.12.013
• BENFORD, F. (1938). The law of anomalous numbers, Proceedings of the American Philosophical Society, 78(4): 551-572.
• Bhattacharya, S., Xu, D., Kumar, K. (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
• Busta, B., Weinberg, R. (1998). Using Benford’s law and neural networks as a review procedure, Managerial Auditing Journal, 13(6): 356-366. https://doi.org/10.1108/026.869.09810222375
• Carslaw, C. (1988). Anomalies in income numbers: Evidence of goal oriented behavior, The Accounting Review, 63(2): 321-327.
• Cerioli, A., Barabesi, L., Cerasa, A., Perrotta, D. (2019). Newcomb–Benford law and the detection of frauds in international trade, Proceedings of the National Academy of Sciences of the United States of America, 116(1): 106-115. https://doi.org/10.1073/pnas.180.661.7115
• Cressey, D.R. (1973). Other people’s money. Patterson Smith: Montclair.
• Da Silva, S.B. (2020). Benford or Not Benford: A systematic but not always well-founded use of an elegant law in experimental fields, Communications in Mathematics and Statistics, 8:167-201. DOI: 10.1007/s40304.018.00172-1
• Debreceny, R.S., Gray, G.L. (2010). Data mining journal entries for fraud detection: an exploratory study, International Journal of Accounting Information System, 11(3): 157-181. DOI: 10.1016/j.accinf.2010.08.001
• Dey, R.M., Lim, L. (2018). Audit fee trends from 2000 to 2014, American Journal of Business, 33(1/2): 61-80. https://doi.org/10.1108/AJB-10-2016-0033
• Drake, P.D., Nigrini, M.J. (2000). Computer assisted analytical procedures using Benford’s Law, Journal of Accounting Education, 18(2): 127-146. DOI:10.1016/S0748-5751(00)00008-7
• Durtschi, C., Hillison, W.A., Pacini, C. (2004). The Effective Use of Benford’s Law to Assist in Detecting Fraud in Accounting Data, Journal of Forensic Accounting, 1524-5586/Vol.V.: 17-34.
• Gauvrit, N., Delahaye J.P. (2009). Loi de Benford généralisée (Generalized Benford’s law), Mathématiques et Sciences Humaines, 186: 5-15.
• Gonzales, F. (2020). Self-reported income data: are people telling the truth?, Journal of Financial Crime, in printing. https://doi.org/10.1108/JFC-08-2019-0113
• Gökçen, G., Tipi, O. (2019). A Research in Interior Controls and BIST Manufacturing Sector Towards Preventing Potential Frauds in Business, Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 41(1): 145-169. DOI: 10.14780/muiibd.582316
• Hogan, C.E., Rezaee, Z., Riley, R.A., Velury, U.K. (2008). Financial statement fraud: insights from the academic literature, Auditing: A Journal of Practice and Theory, 27(2): 231–252. https://doi.org/10.2308/aud.2008.27.2.231
• ISAs. International Standards on Auditing issued by International Auditing and Assurance Standards Board. (ISA 200: Overall Objectives of the Independent Auditor and the Conduct of an Audit in Accordance with International Standards on Auditing; ISA 320: Materiality in Planning and Performing an Audit; ISA 505: External Confirmations)
• Istrate, C. (2019). Detecting earnings management using Benford’s Law: the case of Romanian listed companies, Journal of Accounting and Management Information Systems, 18(2): 198-223.
• Kumar, K., Bhattacharya, S. (2007). Detecting the dubious digits: Benford’s law in forensic accounting, Significance: Magazine of the Royal Statistical Society, 4(2): 81-83. https://doi.org/10.1111/j.1740-9713.2007.00234.x
• Newcomb, S. (1881). Note of the frequency of use of the different digits in natural numbers, American Journal of Mathematics, 4: 39-40.
• Nigrini, M.J. (1996). A taxpayer compliance application of Benford’s law, Journal of the American Taxation Association, 18(1): 72-92.
• Nigrini, M.J. (2017). Audit sampling using Benford’s law: a review of the literature with some new perspectives, Journal of Emerging Technology Accounting, 14(2): 29-46. https://doi.org/10.2308/jeta-51783
• Nigrini, M.J. (2020). The patterns of the numbers used in occupational fraud schemes, Managerial Auditing Journal, 34(5), 606-626. https://doi.org/10.1108/MAJ-11-2017-1717
• Nigrini, M.J., Mittermaier, L. (1997). The use of Benford’s law as an aid in analytical procedures, Auditing, 16(2): 52-67.
• PwC (2018). Global Economic Crime and Fraud Survey 2018. https://www.pwc.com.tr/fraud-survey
• PwC (2020). Global Economic Crime and Fraud Survey 2020. www.pwc.com/fraudsurvey
• Spathis, C. (2002). Detecting false financial statements using published data: some evidence from Greece, Managerial Auditing Journal, 17(4): 179–191. DOI: 10.1108/026.869.00210424321
• Tackett, J.A. (2013). Association rules for fraud detection, Journal of Corporate Accounting and Finance, 24(4): 15-22. https://doi.org/10.1002/jcaf.21856
• Thomas, J.K. (1989). Unusual Patterns in Reported Earnings, The Accounting Review, 64(4): 773-787.