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Managing audits to manage earnings: The impact of diversions on an auditor’s detection of earnings management

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  • Luippold, Benjamin L.
  • Kida, Thomas
  • Piercey, M. David
  • Smith, James F.

Abstract

This study examines an aspect of earnings management that we refer to as audit management. We define audit management as a client’s strategic use of diversions to decrease the likelihood that auditors will discover earnings management during the audit. Specifically, we examine whether diverting auditors’ attention to either clean financial statement accounts or accounts that contain other errors affect an auditor’s ability to uncover earnings management. Auditors performed analytical review, searching financial statements for unusual fluctuations suggestive of errors. Following prior studies, we seeded an intentional accounting error which created an unusual fluctuation that allowed the client to meet an earnings target. We manipulated whether management provided a diversionary statement that explicitly identified risk in other areas of the audit, and whether those areas were clean or contained other detected errors that had no impact on earnings. We find that auditors’ earnings management detection is worst when they are diverted to clean accounts and best when auditors are diverted to accounts that contain other errors. Our results suggest that managers can potentially exploit an audit management tactic as simple as a diversion to a clean area to reduce auditors’ effectiveness at detecting earnings management. The implications of these findings for audit and decision making research are discussed.

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  • Luippold, Benjamin L. & Kida, Thomas & Piercey, M. David & Smith, James F., 2015. "Managing audits to manage earnings: The impact of diversions on an auditor’s detection of earnings management," Accounting, Organizations and Society, Elsevier, vol. 41(C), pages 39-54.
  • Handle: RePEc:eee:aosoci:v:41:y:2015:i:c:p:39-54
    DOI: 10.1016/j.aos.2014.07.005
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    2. Ausloos, Marcel & Cerqueti, Roy & Mir, Tariq A., 2017. "Data science for assessing possible tax income manipulation: The case of Italy," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 238-256.
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    5. Christensen, Brant E. & Newton, Nathan J. & Wilkins, Michael S., 2021. "How do team workloads and team staffing affect the audit? Archival evidence from U.S. audits," Accounting, Organizations and Society, Elsevier, vol. 92(C).

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