IDEAS home Printed from https://ideas.repec.org/a/ids/ijbbmi/v3y2024i2p182-205.html
   My bibliography  Save this article

Fraud and anomaly detection models in banks: a systematic analysis and literature connection

Author

Listed:
  • Alex Cerqueira Pinto
  • Mathias Schneid Tessmann
  • Alexandre Vasconcelos Lima

Abstract

This paper seeks to analyse and verify existing connections in the literature on fraud detection in banks. For this, 227 papers published until September 2022 in the Web of Knowledge through the PRISMA protocol are analysed and classified. The works were identified using the keywords 'fraud', 'model', 'detection', 'banking' and 'risk' and classified into 12 categories, such as type of study, approach, cut, design, nature, the purpose of study, method, spatial scope, period of study, focus, data used and results. Based on the classification, statistics of complex networks are also used to identify the existing citation connections between them. The results show that there is a dissemination of the use of machine learning techniques together with business rules to detect possible cases of fraud and a growing increase in cases of fraud with social engineering. These findings are useful for the scientific literature that investigates operational risk professionals of banks.

Suggested Citation

  • Alex Cerqueira Pinto & Mathias Schneid Tessmann & Alexandre Vasconcelos Lima, 2024. "Fraud and anomaly detection models in banks: a systematic analysis and literature connection," International Journal of Bibliometrics in Business and Management, Inderscience Enterprises Ltd, vol. 3(2), pages 182-205.
    • Handle: RePEc:ids:ijbbmi:v:3:y:2024:i:2:p:182-205
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=140372
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijbbmi:v:3:y:2024:i:2:p:182-205. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=447 .

    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.