IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v10y2024i6id561.html

The Integration of Large Language Models in Financial Services: From Fraud Detection to Generative AI Applications

Author

Listed:
  • Snehansh Devera Konda

Abstract

This comprehensive article examines the transformative impact of artificial intelligence in the financial services sector, focusing on the evolution from traditional applications to advanced AI systems. Through systematic analysis of implementation frameworks and regulatory considerations, this article demonstrates the sector's technological leadership, evidenced by a 56% higher AI implementation success rate compared to other industries. The article reveals how Large Language Models have revolutionized customer interactions, achieving 92% query resolution accuracy and 89% improvement in user engagement. Documentation and compliance processes have been transformed through AI automation, demonstrating an 82% improvement in real-time compliance monitoring and 89% enhancement in automated reporting accuracy. Financial institutions' established regulatory frameworks and mature governance structures have enabled superior technology integration, with an 82% cloud adoption rate and 85% risk management effectiveness. The article’s analysis of software development infrastructure shows significant advancement, with a 73% improvement in deployment frequency and 82% enhancement in code quality metrics. The article highlights how financial institutions' robust regulatory expertise provides a significant competitive advantage, demonstrated by 89% security compliance and 76% stronger compliance protocols. Drawing from comprehensive industry analyses and empirical evidence, this article contributes to the growing body of literature on AI implementation in regulated industries while providing practical insights for organizations balancing innovation with compliance requirements.

Suggested Citation

  • Snehansh Devera Konda, 2024. "The Integration of Large Language Models in Financial Services: From Fraud Detection to Generative AI Applications," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(6), pages 1652-1665, November.
  • Handle: RePEc:jbh:ijsrcs:v10:y2024:i6:id:561
    DOI: 10.32628/CSEIT241061208
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT241061208
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/home/article/view/CSEIT241061208
    File Function: Article URL
    Download Restriction: no

    File URL: https://ijsrcseit.com/home/article/download/CSEIT241061208/CSEIT241061208
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32628/CSEIT241061208?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:jbh:ijsrcs:v10:y2024:i6:id:561. 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: Pankaj Sharma (USA) (email available below). General contact details of provider: https://ijsrcseit.com/home .

    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.