IDEAS home Printed from https://ideas.repec.org/a/dba/ejbema/v1y2025i2p150-157.html
   My bibliography  Save this article

Research on the Application of Machine Learning in the Pricing of Cash Deposit Products

Author

Listed:
  • Jing, Xiao

Abstract

In the context of interest rate marketization and the vigorous development of financial technology innovation, the pricing of cash deposit products has a dilemma of real-time responding and personalization. Based on machine learning technology, this paper designs a price model path of data acquisition, attribute construction, algorithm screening and model practice. Through neural network, supply and demand curve optimization and other means, it quantitatively analyzes consumer behavior and product fit, empirically analyzes the effectiveness and operability of the model, and provides technical support for banks to optimize capital pricing efficiency and customer loyalty.

Suggested Citation

Handle: RePEc:dba:ejbema:v:1:y:2025:i:2:p:150-157
as

Download full text from publisher

File URL: https://pinnaclepubs.com/index.php/EJBEM/article/view/178/180
Download Restriction: no
---><---

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:dba:ejbema:v:1:y:2025:i:2:p:150-157. 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: Joseph Clark (email available below). General contact details of provider: https://pinnaclepubs.com/index.php/EJBEM .

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.