Research in forensic accounting and fraud detection: a systematic literature review

Gopal Kumar Singh & Vineeta Kumari

International Journal of Accounting, Business and Finance2025https://doi.org/10.55429/ijabf.v4i1.177article
ABDC C
Weight
0.50

What the paper says

This study employs a bibliometric analysis to map the intellectual structure and evolution of research in forensic accounting and fraud detection. Utilizing a search protocol in the Scopus database, a final corpus of 42 documents published between 1995 and 2025 was analyzed to identify publication trends, geographical distribution, and thematic clusters. Findings reveal a significant growth, particularly since 2017, driven by technological advancements and regulatory pressures. Geographically, research is clustered around a U.S.-influenced network and distinct regional hubs in the Middle East and Asia, reflecting a stratified evolution between developed and emerging economies. Thematic analysis uncovers three dominant clusters: the integration of technology and governance, foundational skills and macro-institutional influences, and pedagogical approaches. The review concludes by proposing future research agendas focused on the ethical governance of technology, empirical assessment of educational efficacy, cross-cultural studies, and the development of proactive, prescriptive forensic methodologies to address emerging financial crime vectors.

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https://doi.org/https://doi.org/10.55429/ijabf.v4i1.177

Or copy a formatted citation

@article{gopal2025,
  title        = {{Research in forensic accounting and fraud detection: a systematic literature review}},
  author       = {Gopal Kumar Singh & Vineeta Kumari},
  journal      = {International Journal of Accounting, Business and Finance},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.55429/ijabf.v4i1.177},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.