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Innovative approaches in forensic accounting: The role of data analytics

Author

Listed:
  • Kapo Amra

    (University Sarajevo, School of Economics and Business)

  • Turulja Lejla

    (University Sarajevo, School of Economics and Business)

  • Vidačak Zorana

    (PhD candidate in Management, University of Sarajevo, School of Economics and Business)

Abstract

The integration of data analytics into forensic accounting has revolutionized the detection and prevention of financial fraud. This paper conducts a comprehensive analysis of recent advancements in this field, highlighting the application of machine learning, data mining, and big data techniques in identifying fraudulent activities. By reviewing the latest research and examining case studies, we demonstrate the enhanced accuracy and efficiency these technologies offer over traditional methods. The findings suggest that financial institutions should adopt these advanced tools to mitigate fraud risks and improve overall financial security. The paper also explores future research directions, emphasizing the need for developing hybrid models and real-time detection systems to further enhance fraud detection capabilities.

Suggested Citation

  • Kapo Amra & Turulja Lejla & Vidačak Zorana, 2024. "Innovative approaches in forensic accounting: The role of data analytics," Journal of Forensic Accounting Profession, Sciendo, vol. 4(1), pages 1-14.
    • Handle: RePEc:vrs:jfaccp:v:4:y:2024:i:1:p:1-14:n:1001
    DOI: 10.2478/jfap-2024-0001
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    References listed on IDEAS

    as
    1. Donthu, Naveen & Kumar, Satish & Mukherjee, Debmalya & Pandey, Nitesh & Lim, Weng Marc, 2021. "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, Elsevier, vol. 133(C), pages 285-296.
    2. Jessen L. Hobson & William J. Mayew & Mohan Venkatachalam, 2012. "Analyzing Speech to Detect Financial Misreporting," Journal of Accounting Research, Wiley Blackwell, vol. 50(2), pages 349-392, May.
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