• ISSN: 2010-023X (Print)
    • Abbreviated Title: Int. J. Trade, Economics and Finance.
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    • DOI: 10.18178/IJTEF
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HOME > Archive > 2026 > Volume 17 Number 1 (2026) >
IJTEF 2026 Vol.17(1): 162-169
DOI: 10.18178/ijtef.2026.17.1.786

Transforming Auditing with Artificial Intelligence: A Framework for Fraud Detection and Responsible Adoption

Hong Yang
Hong Yang
Faculty of Business and Law, Curtin University, Perth, Australia
Email: yhzzywzy@gmail.com

Manuscript received January 21, 2026; accepted March 31, 2026; published April 15, 2026.

Abstract—This study investigates how Artificial Intelligence (AI) can transform auditing by improving fraud detection and audit quality. However, traditional methods, limited by sampling and manual inspection, failed to detect   complex frauds such as Luckin Coffee. Using the   Technology–Organization–Environment (TOE) framework and Socio-Technical Systems (STS) theory, the research adopted a qualitative case study design. Audit failures were reconstructed through triangulated evidence and counterfactual reasoning, assessing how Machine Learning (ML) and Natural Language Processing (NLP) could have detected anomalies in real time. Findings show AI provides broader coverage, timeliness, and granularity while preserving professional skepticism. The study contributes by situating AI adoption within socio-technical and organizational contexts and proposing a framework for responsible implementation, and it is crucial to position AI as a tool that complements, rather than substitutes, human auditors. 


Keywords—auditing, artificial intelligence, data analytics, machine learning, fraud detection, natural language processing


Cite: Hong Yang, "Transforming Auditing with Artificial Intelligence: A Framework for Fraud Detection and Responsible Adoption," International Journal of Trade, Economics and Finance, vol.17, no.1, pp. 162-169, 2026.


Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).


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