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Explainable Artificial Intelligence (XAI) in auditing

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  • Zhang, Chanyuan (Abigail)
  • Cho, Soohyun
  • Vasarhelyi, Miklos

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are gaining increasing attention regarding their potential applications in auditing. One major challenge of their adoption in auditing is the lack of explainability of their results. As AI/ML matures, so do techniques that can enhance the interpretability of AI, a.k.a., Explainable Artificial Intelligence (XAI). This paper introduces XAI techniques to auditing practitioners and researchers. We discuss how different XAI techniques can be used to meet the requirements of audit documentation and audit evidence standards. Furthermore, we demonstrate popular XAI techniques, especially Local Interpretable Model-agnostic Explanations (LIME) and Shapley Additive exPlanations (SHAP), using an auditing task of assessing the risk of material misstatement. This paper contributes to accounting information systems research and practice by introducing XAI techniques to enhance the transparency and interpretability of AI applications applied to auditing tasks.

Suggested Citation

  • Zhang, Chanyuan (Abigail) & Cho, Soohyun & Vasarhelyi, Miklos, 2022. "Explainable Artificial Intelligence (XAI) in auditing," International Journal of Accounting Information Systems, Elsevier, vol. 46(C).
    • Handle: RePEc:eee:ijoais:v:46:y:2022:i:c:s1467089522000240
    DOI: 10.1016/j.accinf.2022.100572
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    2. Julia Brasse & Hanna Rebecca Broder & Maximilian Förster & Mathias Klier & Irina Sigler, 2023. "Explainable artificial intelligence in information systems: A review of the status quo and future research directions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-30, December.
    3. Wei Jie Yeo & Wihan van der Heever & Rui Mao & Erik Cambria & Ranjan Satapathy & Gianmarco Mengaldo, 2023. "A Comprehensive Review on Financial Explainable AI," Papers 2309.11960, arXiv.org.
    4. Diego Valentinetti & Michele A. Reaa, 2023. "Intelligenza artificiale e accounting: le possibili relazioni," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2023(2), pages 93-116.
    5. Goodell, John W. & Ben Jabeur, Sami & Saâdaoui, Foued & Nasir, Muhammad Ali, 2023. "Explainable artificial intelligence modeling to forecast bitcoin prices," International Review of Financial Analysis, Elsevier, vol. 88(C).
    6. Chen, Xun-Qi & Ma, Chao-Qun & Ren, Yi-Shuai & Lei, Yu-Tian & Huynh, Ngoc Quang Anh & Narayan, Seema, 2023. "Explainable artificial intelligence in finance: A bibliometric review," Finance Research Letters, Elsevier, vol. 56(C).
    7. Sutton, Steve G. & Arnold, Vicky & Holt, Matthew, 2023. "An extension of the theory of technology dominance: Capturing the underlying causal complexity," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).

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