Author(s)

Yifei Chen ¹

Affiliation(s)

¹ School of Accounting, Yunnan University of Finance and Economics, Kunming, Yunnan, China

Corresponding Author

Yifei Chen

ABSTRACT

This paper aims to explore the impact of AI on corporate ESG (environmental, social and governance) ratings. By analyzing the application of AI in ESG rating data collection, processing, index construction and model development, its role in improving rating efficiency and quality is expounded. At the same time, it also discusses the challenges of data privacy and model interpretability faced by the application of AI in ESG rating, and proposes corresponding countermeasures to promote the healthy development of enterprise ESG rating with the help of AI.

KEYWORDS

Artificial intelligence; Corporate ESG ratings; Sustainable development; Impact

CITE THIS PAPER

Yifei Chen, Research on the Impact of Artificial Intelligence on Corporate ESG Ratings. Accounting and Corporate Management (2024) Vol. 6: 43-49. DOI: http://dx.doi.org/10.23977/acccm.2024.060507.

REFERENCES

[1] Yang Helong. Methods and application of risk analysis and management of ESG [N]. Accounting Letter, 2024-07-01 (007). 
[2] Liang Yongchao. A Study on the impact of environmental, Social and Corporate Governance (ESG) on the financial performance of commercial banks [D]. Shanxi University, 2023.
[3] Deng Zongyi. Research on the optimization of internal audit and results [J]. China Internal Audit, 2024 (2): 81-86.
[4] Wu Xun, Yang Meiyi. Can ESG responsibility fulfillment strengthen enterprise value creation: based on the threshold effect of digital transformation [J /OL]. Science and science and technology management, 1-25 [2024-02-29].
[5] Anqi Zhao. Chinese and American enterprises are working together to explore the "new wind outlets" for green cooperation [N]. China Youth Daily, 2024-02-02 (6).
[6] Song Yan, Wu Jiaxuan. Digital transformation and corporate ESG performance: the dual perspective of media attention and executive overconfidence [J]. Chongqing Social Science, 2024 (1): 88-100.

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