Education, Science, Technology, Innovation and Life
Open Access
Sign In

Reconstruction and Application of Corporate Financial Core Indicator System in the Digital Context

Download as PDF

DOI: 10.23977/accaf.2025.060105 | Downloads: 22 | Views: 324

Author(s)

Xie Ning 1

Affiliation(s)

1 Choice Properties Real Estate Investment Trust, Toronto, Canada

Corresponding Author

Xie Ning

ABSTRACT

With the advancement of digital transformation, enterprises are facing the bottlenecks and challenges of traditional financial management models, and the financial core indicator system urgently needs to be reconstructed to meet the demands of the new era. This paper discusses the reconstruction and application of the corporate financial core indicator system in the context of digital transformation. It first analyzes the impact of digital transformation on financial management and the main challenges faced by enterprises. Then, it proposes methods for reconstructing the financial core indicator system, emphasizing the integration of data-driven approaches and intelligent technologies, and designs financial core indicators that adapt to digital transformation. The paper further explores the application of the reconstructed financial core indicator system in areas such as budget management, cost control, and financial analysis. Finally, the paper summarizes the implementation path and challenges faced during the reconstruction process, proposes strategies to address these challenges, and forecasts the future digital development trends of financial management. This paper provides theoretical references and practical guidance for optimizing financial management during the digital transformation of enterprises.

KEYWORDS

Digital transformation, financial management, core indicator system, data-driven, intelligent technology

CITE THIS PAPER

Xie Ning, Reconstruction and Application of Corporate Financial Core Indicator System in the Digital Context. Accounting, Auditing and Finance (2025) Vol. 6: 27-34. DOI: http://dx.doi.org/10.23977/accaf.2025.060105.

REFERENCES

[1] Yang, Weige, et al. "Evaluate the sustainable reuse strategy of the corporate financial management based on the big data model." Journal of Enterprise Information Management 35.4/5 (2022): 1185-1201.
[2] Xia, Yanchun, Zhilin Qiao, and Guanghua Xie. "Corporate resilience to the COVID-19 pandemic: The role of digital finance." Pacific-Basin Finance Journal 74 (2022): 101791.
[3] Deng, Yuenan. "Construction of a digital platform for enterprise financial management based on visual processing technology." Scientific Programming 2022.1 (2022): 7666110.
[4] Liu, Jiajia, et al. "The effect of financial digital transformation on financial performance: the intermediary effect of information symmetry and operating costs." Sustainability 15.6 (2023): 5059.
[5] Tang, Wei, and Shuili Yang. "[Retracted] Digital Transformation and Firm Performance in the Context of Sustainability: Mediating Effects Based on Behavioral Integration." Journal of Environmental and Public Health 2022.1 (2022): 8220940.
[6] Ren, Shaomin. "Optimization of Enterprise Financial Management and Decision‐Making Systems Based on Big Data." Journal of Mathematics 2022.1 (2022): 1708506.
[7] Lin, Yibin, et al. "Financial risk assessment of enterprise management accounting based on association rule algorithm under the background of big data." Journal of sensors 2022.1 (2022): 8041623.
[8] Wang, Fatao, et al. "Big data analytics on enterprise credit risk evaluation of e-Business platform." Information Systems and e-Business Management 18.3 (2020): 311-350.
[9] Yang, Yang, and Jinmian Han. "Digital transformation, financing constraints, and corporate environmental, social, and governance performance." Corporate Social Responsibility and Environmental Management 30.6 (2023): 3189-3202.
[10] Stalmachova, Katarina, Roman Chinoracky, and Mariana Strenitzerova. "Changes in business models caused by digital transformation and the COVID-19 pandemic and possibilities of their measurement—case study." Sustainability 14.1 (2021): 127.

Downloads: 10820
Visits: 136684

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.