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The Synergistic Transformation of Auditing: Enhancing Fraud Detection and Efficiency through AI and Blockchain

In: Proceedings of the 13th International Conference on Business, Accounting, Finance and Economics (BAFE 2025)

Author

Listed:
  • Ally Salumu Mtupeni

    (Institute of Accountancy Arusha)

Abstract

The traditional, sample-based external audit model faces increasing pressure from the complexity of globalized commerce and the rising threat of sophisticated financial fraud. This paper addresses this challenge by empirically investigating the synergistic impact of Artificial Intelligence (AI) and Blockchain Technology (BT) on audit processes. BT provides an immutable, distributed ledger, inherently enhancing the reliability and completeness of transaction data for audit evidence. Complementarily, AI, through Machine Learning (ML) and Natural Language Processing (NLP), enables the analysis of this complete data population for continuous assurance and real-time anomaly detection. Our findings indicate that the combined adoption of these technologies significantly improves the accuracy of fraud detection, shifts the audit focus from transaction testing to internal control monitoring and results in considerable gains in audit efficiency, thereby enhancing overall audit quality. This necessitates a critical re-evaluation of current audit methodologies, auditor competency frameworks, and regulatory standards.

Suggested Citation

  • Ally Salumu Mtupeni, 2025. "The Synergistic Transformation of Auditing: Enhancing Fraud Detection and Efficiency through AI and Blockchain," Advances in Economics, Business and Management Research, in: Thurai Murugan Nathan & Abdelhak Senadjki & Hemaniswarri Dewi Dewadas & Siti Nur Amira Othman & Ravi (ed.), Proceedings of the 13th International Conference on Business, Accounting, Finance and Economics (BAFE 2025), pages 514-522, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-968-1_35
    DOI: 10.2991/978-94-6463-968-1_35
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