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Big data techniques in auditing research and practice: Current trends and future opportunities

Author

Listed:
  • Adrian Gepp
  • Martina K. Linnenluecke
  • Terrence J. O’Neill
  • Tom Smith

Abstract

Keywords: Auditing, Big data, Data analytics, Statistical techniques

Suggested Citation

  • Adrian Gepp & Martina K. Linnenluecke & Terrence J. O’Neill & Tom Smith, 2018. "Big data techniques in auditing research and practice: Current trends and future opportunities," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 40(1), pages 102-115, February.
    • Handle: RePEc:eme:jalpps:j.acclit.2017.05.003
    DOI: 10.1016/j.acclit.2017.05.003
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    Citations

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    Cited by:

    1. Salonee Patel & Manan Shah, 2023. "A Comprehensive Study on Implementing Big Data in the Auditing Industry," Annals of Data Science, Springer, vol. 10(3), pages 657-677, June.
    2. Ha Nguyen, 2023. "Particle MCMC in forecasting frailty correlated default models with expert opinion," Papers 2304.11586, arXiv.org, revised Aug 2023.
    3. Helmi Hentati & Neila Boulila Taktak, 2023. "Unlocking Technological Capabilities to Boost the Performance of Accounting Firms," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 22(4), pages 631-656, December.
    4. Thorsten Sellhorn, 2020. "Machine Learning und empirische Rechnungslegungsforschung: Einige Erkenntnisse und offene Fragen [Machine Learning and Empirical Accounting Research: Some Findings and Open Questions]," Schmalenbach Journal of Business Research, Springer, vol. 72(1), pages 49-69, March.

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