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Do Strategic Reasoning and Brainstorming Help Auditors Change Their Standard Audit Procedures in Response to Fraud Risk?

The Accounting Review 2009 84(3), 811-837
The Public Company Accounting Oversight Board recently reported that its inspections show that auditors fail to effectively modify their standard audit procedures in response to fraud risk. Prior academic research is consistent with this finding. Our study examines the effects of two interventions on auditors' planning decisions in a high-fraud-risk setting: strategic reasoning and brainstorming in groups. Both interventions are predicted to lead auditors to more effectively modify their planned audit procedures. We use a panel of fraud experts to identify effective modifications to the audit plan of a specific fraud case. The experts' recommendations are then used to evaluate the effectiveness of practicing auditors' audit plans with and without the two interventions. We predict and find that each intervention leads to more effective modifications to the standard audit procedures and that the combination of the interventions is not significantly more effective than either intervention used alone.

Using Nonfinancial Measures to Assess Fraud Risk

Journal of Accounting Research 2009 47(5), 1135-1166 open access
This study examines whether auditors can effectively use nonfinancial measures (NFMs) to assess the reasonableness of financial performance and, thereby, help detect financial statement fraud (hereafter, fraud). If auditors or other interested parties (e.g., directors, lenders, investors, or regulators) can identify NFMs (e.g., facilities growth) that are correlated with financial measures (e.g., revenue growth), inconsistent patterns between the NFMs and financial measures can be used to detect firms with high fraud risk. We find that the difference between financial and nonfinancial performance is significantly greater for firms that committed fraud than for their nonfraud competitors. We also find that this difference is a significant fraud indicator when included in a model containing variables that have previously been linked to the likelihood of fraud. Overall, our results provide empirical evidence suggesting that NFMs can be effectively used to assess fraud risk.