Sustainable artificial intelligence in finance: impact of ESG factors.

IF 3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Frontiers in Artificial Intelligence Pub Date : 2025-03-06 eCollection Date: 2025-01-01 DOI:10.3389/frai.2025.1566197
Paolo Giudici, Lunshuai Wu
{"title":"Sustainable artificial intelligence in finance: impact of ESG factors.","authors":"Paolo Giudici, Lunshuai Wu","doi":"10.3389/frai.2025.1566197","DOIUrl":null,"url":null,"abstract":"<p><p>There is a growing concern about the sustainability of artificial intelligence, in terms of Environmental, Social and Governance (ESG) factors. We contribute to the debate measuring the impact of ESG factors on one of the most relevant applications of AI in finance: credit rating. There is not yet conclusive evidence on whether EGS factors impact on credit rating. In this paper, we propose several machine learning models to measure such impact, and a set of metrics that can improve their ability to do so. In this way, machine learning models and, more generally, decisions based on artificial intelligence, can become more sustainable.</p>","PeriodicalId":33315,"journal":{"name":"Frontiers in Artificial Intelligence","volume":"8 ","pages":"1566197"},"PeriodicalIF":3.0000,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11922921/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frai.2025.1566197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

There is a growing concern about the sustainability of artificial intelligence, in terms of Environmental, Social and Governance (ESG) factors. We contribute to the debate measuring the impact of ESG factors on one of the most relevant applications of AI in finance: credit rating. There is not yet conclusive evidence on whether EGS factors impact on credit rating. In this paper, we propose several machine learning models to measure such impact, and a set of metrics that can improve their ability to do so. In this way, machine learning models and, more generally, decisions based on artificial intelligence, can become more sustainable.

金融领域的可持续人工智能:环境、社会和治理因素的影响。
在环境、社会和治理(ESG)因素方面,人们越来越关注人工智能的可持续性。我们为衡量ESG因素对人工智能在金融领域最相关的应用之一——信用评级——的影响的辩论做出贡献。EGS因素是否影响信用评级尚无确凿证据。在本文中,我们提出了几个机器学习模型来衡量这种影响,以及一组可以提高他们这样做的能力的指标。通过这种方式,机器学习模型,更普遍地说,基于人工智能的决策,可以变得更加可持续。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信