智绘未来:人工智能如何提升企业ESG报告质量

陈 敏
广东外语外贸大学南国商学院

摘要


ESG(环境、社会、公司治理)报告对企业可持续发展和投融资决策具有重要意义,但现阶段国内企业仍
以人工方式编制ESG报告,普遍存在产出效率偏低、主观判断占比高、数据精准度不足等缺陷。本文依托人工智能
(AI)大模型技术,搭建ESG报告质量优化方案:借助自然语言处理技术自动抓取年报、网络舆情等多渠道ESG数
据,提升信息采集效率;依托大模型数据分析能力挖掘核心指标与发展趋势,强化报告客观性与内容统一性。实测
结果显示,该智能方案能够有效提升ESG报告的整体质量与可信程度。

关键词


神经网络;ESG质量报告;人工智能优化研究

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参考


[1]李虹霖.基于改进Stacking模型融合的ESG评级预

测研究[J].社会科学Ⅱ辑,2023:45-58.DOI:10.27713/

d.cnki.gcqgs.2023.000271.

[2]梁岩,刘超,梁仲雄,李文涛.使用融合多注意

力神经网络的方面级情感分析[J].计算机工程与设计,

2023,44(03):894-900.DOI:10.16208/j.issn1000-

7024.2023.03.035.

[3]Aydin C R, Gungor T. Combination of recursive and

recurrent networks for aspect-based sentiment analysis using

inter-aspect relations [J]. IEEE Access, 2020, 8: 77820-77832.

[4]Berkery M, Zhang J. Artificial Intelligence for Sustainable

Finance: Exploring AI Applications in ESG Investing [J]. Journal

of Sustainable Finance & Investment, 2020, 10 (3): 215-229. D

OI:10.1080/20430795.2020.1838851.

[5]Krause A, Golub B, Varela E. Using Machine

Learning to Enhance ESG Performance Measurement

and Reporting [J]. Journal of Environmental Economics

and Management, 2021, 105: 102405. DOI:10.1016/

j.jeem.2020.102405.

[6]Miller J, Saad J, Zheng Y. AI-Driven ESG Analytics:

Opportunities and Challenges [J]. Journal of Financial Data

Science, 2022, 4 (1): 45-56. DOI:10.3905/jfds.2022.1.011.

[7]Sangeetha K, Prabha D. Sentiment analysis of student

feedback using multi-head attention fusion model of word

and context embedding for LSTM [J]. Journal of Ambient

Intelligence and Humanized Computing, 2021, 12 (6): 4117-

4126.

[8]Van der Maaten L, Hinton G. Visualizing data using

t-SNE [J]. Journal of machine learning research, 2008, 9 (11).

[9]Vaswani A, Shazeer N, Parmar N, et al. Attention Is

All You Need [J]. Advances in Neural Information Processing

Systems, 2017, 30: 5998-6008.


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