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Smart Forensics: Tracing the Rise of Artificial Intelligence in Forensic Accounting, Fraud Detection and Risk Management

Author

Listed:
  • Zaiza Norsuriati Zainal Zakaria
  • Nor Haliza Che Hussain
  • Yunita Awang
  • Shazalina Mohamed Shuhidan

Abstract

This study examines the evolution of academic research at the intersection of artificial intelligence (AI), risk management, and forensic accounting by analysing publication trends, main themes, and knowledge gaps. A bibliometric analysis was conducted on 261 Scopus-indexed publications from 2002 to July 2025 using tools including Microsoft Excel, VOS viewer, and Publish or Perish to assess citation patterns, authorship networks, and keyword relationships. The results indicate a notable increase in publications after 2017. "Forensic accounting" and "fraud" appearing as the most recurrent keywords, along with growing academic attention on emerging technologies such as AI, blockchain, big data, and data analytics. Journal articles represent the predominant publication type, particularly in the Business, Management and Accounting subject area, while Jordan stands out as a leading contributor with several influential authors and institutions. The analysis identifies eight key research themes covering governance, fraud control, professional competency, financial crime, and technology-enhanced audit practices. Even though this study limited to English-language publications in the Scopus database, this research provides valuable insights into current developments and future directions, offering guidance for academic research, policy formulation, and practical applications in forensic accounting and fraud detection.

Suggested Citation

  • Zaiza Norsuriati Zainal Zakaria & Nor Haliza Che Hussain & Yunita Awang & Shazalina Mohamed Shuhidan, 2025. "Smart Forensics: Tracing the Rise of Artificial Intelligence in Forensic Accounting, Fraud Detection and Risk Management," Information Management and Business Review, AMH International, vol. 17(2), pages 51-68.
    • Handle: RePEc:rnd:arimbr:v:17:y:2025:i:2:p:51-68
    DOI: 10.22610/imbr.v17i2(I)S.4565
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    References listed on IDEAS

    as
    1. Mahmut Sami Öztürk & Hayrettin Usul, 2020. "Detection of Accounting Frauds Using the Rule-Based Expert Systems within the Scope of Forensic Accounting," Contemporary Studies in Economic and Financial Analysis, in: Contemporary Issues in Audit Management and Forensic Accounting, volume 102, pages 155-171, Emerald Group Publishing Limited.
    2. Li Yan & Wang Zhiping, 2023. "Mapping the Literature on Academic Publishing: A Bibliometric Analysis on WOS," SAGE Open, , vol. 13(1), pages 21582440231, March.
    3. Hellen Ogutu & Youssef El Archi & Lóránt Dénes Dávid, 2023. "Current trends in sustainable organization management: A bibliometric analysis," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 11-45, March.
    4. Hashem Alshurafat & Mohannad Obeid Al Shbail & Ebrahim Mansour, 2021. "Strengths and weaknesses of forensic accounting: an implication on the socio-economic development," Journal of Business and Socio-economic Development, Emerald Group Publishing Limited, vol. 1(2), pages 135-148, July.
    5. repec:eme:jbsed0:jbsed-03-2021-0026 is not listed on IDEAS
    6. Amani, Farzaneh A. & Fadlalla, Adam M., 2017. "Data mining applications in accounting: A review of the literature and organizing framework," International Journal of Accounting Information Systems, Elsevier, vol. 24(C), pages 32-58.
    7. Pham Quang Huy & Vu Kien Phuc, 2025. "Insight into how legal and ethical considerations of artificial intelligence enhance the effectiveness of cyber forensic accounting," Journal of Global Information Technology Management, Taylor & Francis Journals, vol. 28(2), pages 136-166, April.
    8. Rana Mustafa Airout & Sadam Abu Azam & Mohammad Airout, 2024. "Bibliometric insights into the intellectual dynamics of forensic accounting research," Cogent Business & Management, Taylor & Francis Journals, vol. 11(1), pages 2344748-234, December.
    Full references (including those not matched with items on IDEAS)

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