Fraud Risk Analytics

Fraud Risk Analytics is a subfield of risk analytics that applies statistical, machine learning, and data-mining methods to transactional and contextual data to identify, quantify, and predict the likelihood and impact of fraudulent activities.

322

Publications

20.9K

Citations

1K

Authors

477

Institutions

Publications per year

2017–2026

189

Authors

1K

  1. TM
    Taghi M. Khoshgoftaar

    Florida Atlantic University, United States

    11 publications · 616 citations

    11

    h-index

  2. RA
    Richard A. Bauder

    Florida Atlantic University, United States

    8 publications · 520 citations

    8

    h-index

  3. GL
    Guanjun Liu

    Tongji University, China

    3 publications · 368 citations

    3

    h-index

  4. AN
    André Nunes de Souza

    Universidade Estadual Paulista (Unesp), Brazil

    3 publications · 353 citations

    3

    h-index

  5. DS
    Deepti Sisodia

    National Institute of Technology Raipur, India

    3 publications · 71 citations

    3

    h-index

1–5 of 1K

Venues

  1. Expert Systems with Applications

    27 publications · 3.1K citations

    23

    h-index

  2. Decision Support Systems

    10 publications · 1.9K citations

    10

    h-index

  3. arXiv (Cornell University)

    Repository · 7 publications · 259 citations

    7

    h-index

  4. SSRN Electronic Journal

    Repository · 5 publications · 83 citations

    5

    h-index

  5. IEEE Access

    5 publications · 375 citations

    5

    h-index

1–5