Financial Statement Fraud Detection

Financial Statement Fraud Detection is a methodological framework within financial accounting and forensic analysis that systematically identifies intentional misstatements in financial reports through analytical, statistical, or machine learning techniques to distinguish fraudulent from non-fraudulent reporting patterns.

772

Publications

48.2K

Citations

1.7K

Authors

756

Institutions

Publications per year

2017–2026

409

Authors

1.7K

  1. KJ
    Karim Jamal

    University of Alberta, Canada

    7 publications · 450 citations

    7

    h-index

  2. MS
    Mark S. Beasley

    North Carolina State University, United States

    6 publications · 569 citations

    6

    h-index

  3. JV
    Joseph V. Carcello

    University of Tennessee at Knoxville, United States

    6 publications · 661 citations

    6

    h-index

  4. ID
    Imang Dapit Pamungkas

    Universitas Dian Nuswantoro, Indonesia

    6 publications · 224 citations

    6

    h-index

  5. KL
    Keith L. Jones

    North Carolina State University, United States

    5 publications · 797 citations

    5

    h-index

1–5 of 1.7K

Venues

  1. SSRN Electronic Journal

    Repository · 44 publications · 1.9K citations

    23

    h-index

  2. Decision Support Systems

    13 publications · 3.3K citations

    13

    h-index

  3. Journal of Financial Crime

    15 publications · 505 citations

    13

    h-index

  4. Expert Systems with Applications

    12 publications · 1.9K citations

    12

    h-index

  5. Journal of Business Ethics

    11 publications · 1.4K citations

    11

    h-index

1–5