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Data analytics in auditing: Opportunities and challenges

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  • Earley, Christine E.

Abstract

In this article, I provide background regarding a hot topic in the public accounting profession: the rise of big data and the related field of data analytics (DA). The tax and advisory practices of public accounting firms have embraced the use of DA, and firms have made significant investments in growing these practice areas. Although DA holds great promise for the auditing practice as well, the use of widespread DA on audit engagements has lagged behind other practice areas. This is due to the fact that auditing presents unique challenges in the adoption of DA that are not relevant for other practice areas. Despite the impression that DA is not being embraced as readily in auditing, public accounting firms are continuing to make significant investments in developing audit-related DA, and it is only a matter of time before we start to see the transformational impact of these efforts. The purpose of this article is (1) to explain how DA applies to financial statement audits and why it could represent a game changer in how audits are conducted, and (2) to provide a context for researchers in terms of problems to be addressed related to DA.

Suggested Citation

  • Earley, Christine E., 2015. "Data analytics in auditing: Opportunities and challenges," Business Horizons, Elsevier, vol. 58(5), pages 493-500.
    • Handle: RePEc:eee:bushor:v:58:y:2015:i:5:p:493-500
    DOI: 10.1016/j.bushor.2015.05.002
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    References listed on IDEAS

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    1. Gray, Glen L. & Debreceny, Roger S., 2014. "A taxonomy to guide research on the application of data mining to fraud detection in financial statement audits," International Journal of Accounting Information Systems, Elsevier, vol. 15(4), pages 357-380.
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