JOURNAL ARTICLE

Analysis of Influencing Factors of Economic Management Decision of Commercial Banks Based on Big Data Intelligent Decision.

  • Published In: International Journal of Cooperative Information Systems, 2025, v. 34, n. 2. P. 1 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Yang, Weijian; Yang, Han 3 of 3

Abstract

Since the 1970s, China's economy has been changing rapidly, especially after joining the World Economic and Trade Organization, and with the increase in multinational enterprises, the development of overseas markets has become more convenient, contributing to the further strengthening of our economic power. The financial industry plays an essential role in the development of a country, and commercial banks are the leaders in the financial sector. They have made significant contributions to national economic growth. Under the background of substantial economic development, the economic management decisions of commercial banks have become more complex, which makes the risks faced by commercial banks increase continuously. The rapid growth of global informatization has effectively boosted the development of all walks of life. Based on the intelligent characteristics of big data, this paper analyzes the influencing factors of economic management decisions of commercial banks based on wise choices of big data, hoping to enable commercial banks to achieve the ideal expectation of financial management of "reducing risk and creating value" to enhance the competitiveness of commercial banks in the whole market. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Cooperative Information Systems. 2025/06, Vol. 34, Issue 2, p1
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2025
  • ISSN:0218-8430
  • DOI:10.1142/S0218843024500114
  • Accession Number:185105955
  • Copyright Statement:Copyright of International Journal of Cooperative Information Systems is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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