Big Data in Financial Management

DOI

10.2991/978-94-6463-642-0_14How to use a DOI?

Keywords

big data; financial management; significance; application

Abstract

In the current digital era, data has risen to be one of the most precious resources for enterprises. The rapid progress of information technology and its wide application have prompted enterprises to accumulate a huge amount of data in their daily operation activities, which cover multiple dimensions such as internal financial information system, external market information and macroeconomic indicators. Mastering the systematic collection, storage, analysis and application of such information through big data technology to strengthen the decision-making process of enterprise financial management has become a major issue and potential opportunity for enterprises. In addition, this direction of application of big data technology has far-reaching significance. The article begins by defining the connotation and characteristics of big data, then discusses its diversified applications in financial management practice, involving financial forecasting, decision-making assistance, financial supervision and in-depth analysis, and finally puts forward strategies and reflections on the challenges that may be encountered in the implementation of big data technology in financial management.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Tingyi Wang
PY  - 2025
DA  - 2025/01/24
TI  - Big Data in Financial Management
BT  - Proceedings of 2024 6th International Conference on Economic Management and Cultural Industry (ICEMCI 2024)
PB  - Atlantis Press
SP  - 133
EP  - 138
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-642-0_14
DO  - 10.2991/978-94-6463-642-0_14
ID  - Wang2025
ER  -