Evaluate the sustainable reuse strategy of the corporate financial management based on the big data model
Journal of Enterprise Information Management
ISSN: 1741-0398
Article publication date: 1 December 2021
Issue publication date: 20 June 2022
Abstract
Purpose
The purposes are to explore corporate financial management optimization in the context of big data and provide a sustainable financial strategy for corporate development.
Design/methodology/approach
First, the shortcomings of the traditional financial management model are analyzed under the background of big data analysis. The big data analytic technology is employed to extract financial big data information and establish an efficient corporate financial management model. Second, the deep learning (DL) algorithm is applied to implement a corporate financial early-warning model to predict the potential risks in corporate finance, considering the predictability of corporate financial risks. Finally, a corporate value-centered development strategy based on sustainable growth is proposed for long-term development.
Findings
The experimental results demonstrate that the financial early-warning model based on DL has an accuracy of 90.7 and 88.9% for the two-year financial alert, which is far superior to the prediction effect of the traditional financial risk prediction models.
Originality/value
The obtained results can provide a reference for establishing a sustainable development pattern of corporate financial management under the background of big data.
Keywords
Acknowledgements
This research was supported by 2019 Henan Province Undergraduate University Young Key Teacher Funding Project of “Research on the Training Mode of Accounting Professionals and Future Social Adaptability under the Background of Industry, Finance and Taxation Integration.”
Citation
Yang, W., Zhou, Y., Xu, W. and Tang, K. (2022), "Evaluate the sustainable reuse strategy of the corporate financial management based on the big data model", Journal of Enterprise Information Management, Vol. 35 No. 4/5, pp. 1185-1201. https://doi.org/10.1108/JEIM-04-2021-0169
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited