IDEAS home Printed from https://ideas.repec.org/a/mnb/finrev/v24y2025i2p47-72.html
   My bibliography  Save this article

Latest Trends in the Use of Artificial Intelligence in the Banking Sector

Author

Listed:
  • Gergely Lulok

    (Budapest University of Technology and Economics)

  • Zoltan Sebestyen

    (Budapest University of Technology and Economics)

Abstract

The study examines the latest trends in the application of artificial intelligence (AI) in the banking sector, with a focus on bank failure prediction, risk management and customer relationship optimisation. The research is based on a systematic literature search of relevant publications in the Scopus and Web of Science databases, using the PRISMA methodology for source selection and analysis. The results show that Unsupervised Learning Models dominate in bankruptcy prediction and risk analysis, while Natural Language Processing and Deep Learning techniques are mainly focused on improving customer relationships and increasing bank efficiency. The research shows that AI is playing an increasingly important role in banking decision-making, but that the different application areas face different regulatory and ethical challenges. The results underline the importance for financial institutions to improve the transparency and interpretability of AI and to develop adaptive regulatory frameworks to balance innovation and security.

Suggested Citation

  • Gergely Lulok & Zoltan Sebestyen, 2025. "Latest Trends in the Use of Artificial Intelligence in the Banking Sector," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 24(2), pages 47-72.
    • Handle: RePEc:mnb:finrev:v:24:y:2025:i:2:p:47-72
    as

    Download full text from publisher

    File URL: https://hitelintezetiszemle.mnb.hu/sw/static/file/fer-24-2-st3-lulok-sebestyen.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    artificial intelligence; banking sector; financial services; trend analysis;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    Statistics

    Access and download statistics

    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:mnb:finrev:v:24:y:2025:i:2:p:47-72. 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: Morvay Endre The email address of this maintainer does not seem to be valid anymore. Please ask Morvay Endre to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/mnbgvhu.html .

    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.