Data analytics can be used to create fraud prediction models that help auditors improve audit planning decisions. It can also be used to help regulators identify firms for potential fraud investigation. In particular, the SEC is investing resources to develop better fraud risk models and the results of this study could be useful.
Perols, Johan L., R. M. Bowen, C. Zimmermann, and B. Samba. 2017. “Finding Needles in a Haystack: Using Data Analytics to Improve Fraud Prediction”. The Accounting Review. 92.2 (2017): 221.
http://commons.aaahq.org/groups/e5075f0eec/summary
This paper incorporates important organizational theory into the fraud literature by reporting the presence of an instrumental climate when fraud is being perpetrated within an organization. Internal auditors and those charged with governance could adapt this climate measure as a red flag for potential fraud.
Murphy, P. R. and C. Free. 2016. Broadening the Fraud Triangle: Instrumental Climate and Fraud. Behavioral Research in Accounting 28 (1): 41-56.
This paper examines how the auditor’s evaluation of internal control impacts substantive testing in a two-location setting with correlated internal control strengths. When control strengths are independent, internal control strength pairings have no effect on the manager’s probability choice to commit fraud or on the auditor’s substantive test effort. This study shows how the manager’s opportunity to commit fraud and informational characteristics of internal control tests impact the manager’s probability choice of fraud and the auditor’s choice of substantive test effort.
Patterson, E.R. and J.R. Smith. 2016. The Strategic Effects of Auditing Standard No. 5 in a Multi-Location Setting. Auditing: A Journal of Practice and Theory 35 (1): 119-138.
This paper presents a fraud-detection tool developed based on textual analysis of the MD&A sections in public companies’ annual and quarterly reports. This tool correctly classifies reports into truthful and fraudulent more than 82% of the time. Compared with other fraud-detection approaches documented in prior literature, this tool has the highest predictive power for both annual reports and quarterly reports. Using the tool to analyze a sequence of reports of a company further increases the accuracy of predictions. This paper provides insights for regulators and practitioners in designing fraud-detection tools. As the tool is “trained” using the AAER database, one limitation is the tool may not detect fraudulent reports if the SEC fails to discover certain types of frauds and/or has bias in selecting firms to investigate.
Purda, L. and D. Skillicorn. 2015. Accounting Variables, Deception, and a Bag of Words: Assessing the Tools of Fraud Detection. Contemporary Accounting Research 32 (3): 1193–1223.
The auditor needs a different model for audits of internal control. The auditor needs to apply two different models in an integrated audit, the original model for the opinion on the financial statements and a different model for the opinion on internal controls.
The author believes standard setters should sponsor research on an appropriate risk model for audits of internal control. Even before the research is completed, the standards could be enhanced in the following ways:
• indicate that the original audit risk model is intended for use only in financial statement audits, not internal control audits;
• write standards that consistently use risk terminology and are clear as to which risk they are discussing; and
• provide guidance on the use of models in integrated audits.
Akresh, A. D. 2010. A Risk Model to Opine on Internal Control. Accounting Horizons 24 (1): 65-78.
The findings have important implications for auditors and other individuals responsible for assessing fraud risk and detecting and preventing fraud. First, for certain types of organizations aggregate fraud levels can vary tremendously over time. Furthermore, the effectiveness of mechanisms to prevent and detect fraud can be contingent on the type of organization and related individual susceptibilities to social influence. Therefore, it may be inappropriate for auditors to evaluate fraud prevention and detection mechanisms in a uniform manner. The results suggest that the same fraud prevention and detection mechanisms implemented in a similar manner in two different organizations cannot be expected to be equally effective without considering the average susceptibilities to social influence of the individuals therein.
Davis, J. S., and H. L. Pesch. 2013. Fraud dynamics and controls in organizations. Accounting, Organizations & Society 38 (6/7): 469-483.
The authors contribute to digital analysis by formulating two alternative mathematical programming models that can assist auditors in selecting audit samples, using Benford’s law. The models consider multiple conformity tests and test statistics simultaneously, taking into account the interdependencies between the conformity tests, and allow the auditor either to identify a subset of nonconforming records in a dataset or to define a specific number of records to audit. This approach is new in the literature.
da Silva, C. G., and P. R. Carreira. 2013. Selecting Audit Samples Using Benford's Law. Auditing: A Journal of Practice & Theory 32 (2): 53-65.
The findings suggest that such sensitization is not merely a “main effect” that shifts the risk-to-resource mapping upward. Rather, human intent appears to exert an interactive effect that flattens the risk-to-resource mapping by changing the cognitive mindset of risk from a magnitude-based calculation. For audit practice, the interaction the authors detect relates to the PCAOB’s efforts to differentiate fraud risks from the more general logic that risks should be evaluated based on magnitudes and likelihoods. The study suggests that people are more comfortable conditioning audit resources on risk magnitudes for unintentional reporting risks than for the same risks arising from human intent.
Kachelmeier, S. J., Majors, T., & Williamson, M. G. 2014. Does Intent Modify Risk-Based Auditing? Accounting Review 89 (6): 2181-2201.
While other fraud research syntheses focus primarily on research that has been published in accounting journals, this synthesis surveys academic literature from non-accounting publications related to fraud and financial crimes: (1) to better understand the nature and extent of fraud acts; (2) to share with accounting researchers and practitioners ideas, theories, variables, constructs, and research designs used in other fields that might inform anti-fraud research and actions in accounting; and (3) to highlight opportunities for future research. In this review and synthesis of the literature, the authors move beyond the fraud triangle to consider a broader spectrum of factors that researchers and practitioners may consider in an effort to provide a more complete perspective on fraud and related financial crimes.
For more information on this study, please contact Gregory M. Trompeter.
Trompeter, G., T. Carpenter, K. Jones, and R. Riley. 2014. Insights for Research and Practice: What We Learn about Fraud from Other Disciplines. Accounting Horizons 28 (4): 769-804.
What appears as a technical and neutral device, that is to say the fraud triangle, actually promotes a vision of fraud anchored in both the individual and the organization, while downplaying the social, political and cultural explanations of fraud. At the end of the day, we are confronted with a series of representations, which lie at the heart of the professional work of a range of actors in the economy, that lead us to view fraud through the lens of individual transgressions being perpetrated while leaving the systemic and socio-political aspects of fraud unchallenged. Would fraud prevention gain in effectiveness if these neglected aspects were dealt with more explicitly? The paper provides reflexivity to practitioners that might help them understand and question the normative and moralizing assumptions that underlie the devices they use.
For more information on this study, please contact Jérémy Morales.
Morales, J., Gendron, Y. and H. Guénin-Paracini. 2014. The construction of the risky individual and vigilant organization: A genealogy of the fraud triangle. Accounting, Organizations and Society 39 (3): 170-194