IDEAS home Printed from https://ideas.repec.org/a/eme/jfcpps/jfc-01-2023-0011.html
   My bibliography  Save this article

Artificial intelligence and deep learning: considerations for financial institutions for compliance with the regulatory burden in the United Kingdom

Author

Listed:
  • Charanjit Singh

Abstract

Purpose - Artificial intelligence (AI), machine learning (ML) and deep learning (DL) are having a major impact on banking (FinTech), health (HealthTech), law (RegTech) and other sectors such as charitable fundraising (CharityTech). The pace of technological innovation and the ability of AI systems to think like human beings (simulate human intelligence), perform tasks independently, develop intelligence based on its own experiences and process layers of information to learn ever-complex representations of data (ML/DL) means that improvements in the rates at which this technology can undertake complex, technical and time-consuming tasks, identify people, objects, voices, patterns, etc., screen for ‘problems’ earlier, and provide solutions, provide astounding benefit in economic, political and social terms. The purpose of this paper is to explore advents in AI, ML and DL in the context of the regulatory compliance challenge faced by financial institutions in the United Kingdom (UK). Design/methodology/approach - The subject is explored through the analysis of data and domestic and international published literature. The first part of the paper summarises the context of current regulatory issues, the advents in deep learning, how financial institutions are currently using AI, and how AI could provide further technological solutions to regulatory compliance as of February 2023. Findings - It is suggested that UK financial institutions can further utilise AI, ML and DL as part of an armoury of solutions that ease the regulatory burden and achieve high levels of compliance success. Originality/value - To the best of the author’s knowledge, this is the first study to specifically explore how AI, ML and DL can continue to assist UK financial institutions in meeting the regulatory compliance challenge and the opportunities provided for financial institutions by the metaverse.

Suggested Citation

  • Charanjit Singh, 2023. "Artificial intelligence and deep learning: considerations for financial institutions for compliance with the regulatory burden in the United Kingdom," Journal of Financial Crime, Emerald Group Publishing Limited, vol. 31(2), pages 259-266, April.
  • Handle: RePEc:eme:jfcpps:jfc-01-2023-0011
    DOI: 10.1108/JFC-01-2023-0011
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/JFC-01-2023-0011/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://www.emerald.com/insight/content/doi/10.1108/JFC-01-2023-0011/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1108/JFC-01-2023-0011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:eme:jfcpps:jfc-01-2023-0011. 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: Emerald Support (email available below). General contact details of provider: .

    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.