IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-835-6_11.html

Big Data Enabling Risk Management in Supply Chain Finance

In: Proceedings of the 2025 3rd International Academic Conference on Management Innovation and Economic Development (MIED 2025)

Author

Listed:
  • Yuanchen Wang

    (Jiangxi University of Finance and Economics, School of Business Administration)

Abstract

The article delves deeply into how big data technology is applied in managing financial risks within the supply chain of commercial banks. Through the examination of various supply chain financial risks and their integration with real-world commercial bank scenarios, the study details the role of big data in refining risk management, boosting early warning capabilities, and refining the credit evaluation system. The study’s findings indicate that the application of big data technology markedly enhances the effectiveness and precision of financial risk management in the supply chain of commercial banks, offering robust backing for their robust growth in the evolving and intricate financial landscape.

Suggested Citation

  • Yuanchen Wang, 2025. "Big Data Enabling Risk Management in Supply Chain Finance," Advances in Economics, Business and Management Research, in: Barbara Siuta-Tokarska & Adriana Grigorescu & Md. Mamun Habib & Yifeng Zhu (ed.), Proceedings of the 2025 3rd International Academic Conference on Management Innovation and Economic Development (MIED 2025), pages 94-102, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-835-6_11
    DOI: 10.2991/978-94-6463-835-6_11
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:advbcp:978-94-6463-835-6_11. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.