IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v18y2025i6p323-d1677116.html
   My bibliography  Save this article

AI and Financial Fraud Prevention: Mapping the Trends and Challenges Through a Bibliometric Lens

Author

Listed:
  • Luiz Moura

    (Faculdade de Administração e Ciências Contábeis (FACC), Universidade Federal do Rio de Janeiro (UFRJ), Av. Pasteur, 250–sala 242, Praia Vermelha, Urca, Rio de Janeiro 22290-240, Brazil)

  • Andre Barcaui

    (Faculdade de Administração e Ciências Contábeis (FACC), Universidade Federal do Rio de Janeiro (UFRJ), Av. Pasteur, 250–sala 242, Praia Vermelha, Urca, Rio de Janeiro 22290-240, Brazil)

  • Renan Payer

    (Departamento de Engenharia de Produção (TEP), Universidade Federal Fluminense (UFF), Rua Passo da Pátria, 156, Bloco D–sala 306, Campus da Praia Vermelha, Niterói 24210-240, Brazil)

Abstract

This study systematically reviews academic research on artificial intelligence (AI) in financial fraud prevention. Employing a bibliometric approach, we analyzed 137 peer-reviewed articles published between 2015 and 2025, sourced from Scopus, Web of Science, and ScienceDirect. Using Bibliometrix, we mapped the field’s intellectual structure, collaboration patterns, and thematic clusters. Research interest has surged since 2019, led mainly by China and India, though the literature is mostly technical, with limited social science engagement. Three main themes emerged: AI-based fraud detection models, blockchain and fintech integration, and big data analytics. Despite growing output, international collaboration and focus on ethical, regulatory, and organizational issues remain limited. These insights provide a foundation for advancing both research and practical AI-driven fraud mitigation.

Suggested Citation

  • Luiz Moura & Andre Barcaui & Renan Payer, 2025. "AI and Financial Fraud Prevention: Mapping the Trends and Challenges Through a Bibliometric Lens," JRFM, MDPI, vol. 18(6), pages 1-24, June.
    • Handle: RePEc:gam:jjrfmx:v:18:y:2025:i:6:p:323-:d:1677116
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/18/6/323/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/18/6/323/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:18:y:2025:i:6:p:323-:d:1677116. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.