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Audit technologies used in practice and ways to implement these technologies into audit courses

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  • Felski, Elizabeth

Abstract

Data analysis has revolutionized the auditing profession. The use of data analytics tools has allowed auditors to plan and complete more thorough, accurate, and efficient audits. Pressures from the accounting profession and AACSB have placed an urgency to include these analytics tools into the accounting curriculum. For many instructors, navigating this new realm of analytics tools can be overwhelming and difficult to pare down to the essentials of what emerging accountants need to know. While prior research has developed suggestions for how to implement audit analytics into accounting curricula (Qasim et al., 2020 & Dzuranin, 2018), institutions are ultimately left on their own to decide if and how to integrate audit analytics tools into their curricula. This paper aims to assist instructors looking to implement audit analytics tools into their courses by presenting survey results from audit professionals on the analytics tools they use at both the entry-level and management position as well as the skills and tools they expect and would like accounting graduates to possess. This information can be used by accounting instructors to tailor their data analytics coverage to include the tools and skills emerging graduates are most likely to use in their profession. The second phase of this paper serves as a reference tool as it provides a collection of the resources, cases, and assignments available for faculty members interested in adding a data analytics component to their current audit course. This repository is focused on tools identified in the survey as useful to accounting graduates.

Suggested Citation

  • Felski, Elizabeth, 2023. "Audit technologies used in practice and ways to implement these technologies into audit courses," Journal of Accounting Education, Elsevier, vol. 62(C).
    • Handle: RePEc:eee:joaced:v:62:y:2023:i:c:s0748575122000616
    DOI: 10.1016/j.jaccedu.2022.100827
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    References listed on IDEAS

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    1. Fay, Rebecca & Negangard, Eric M., 2017. "Manual journal entry testing: Data analytics and the risk of fraud," Journal of Accounting Education, Elsevier, vol. 38(C), pages 37-49.
    2. Presley, Theresa J., 2019. "A risk based approach to large datasets: Analysis of time series data for a large merchandising firm," Journal of Accounting Education, Elsevier, vol. 49(C).
    3. Watty, Kim & McKay, Jade & Ngo, Leanne, 2016. "Innovators or inhibitors? Accounting faculty resistance to new educational technologies in higher education," Journal of Accounting Education, Elsevier, vol. 36(C), pages 1-15.
    4. Dzuranin, Ann C. & Jones, Janet R. & Olvera, Renee M., 2018. "Infusing data analytics into the accounting curriculum: A framework and insights from faculty," Journal of Accounting Education, Elsevier, vol. 43(C), pages 24-39.
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    Cited by:

    1. Booker, Danielle D. & Pelzer, Josette R.E. & Richardson, Jeremy R., 2023. "Integrating data analytics into the auditing curriculum: Insights and perceptions from early-career auditors," Journal of Accounting Education, Elsevier, vol. 64(C).

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