Artificial intelligence applications for advancing sustainable green finance

Artificial Intelligence (AI) is increasingly pivotal in sustainable green finance, supporting risk analytics, investment management, environmental, social, and governance (ESG) assessment, and sustainable reporting. This review synthesizes recent literature on how machine learning, deep learning, and natural language processing enhance credit-risk modeling, portfolio optimization, and ESG evaluation. Key developments include default prediction using novel variables (e.g. household or climate data), deep learning for market forecasting and portfolio returns, and natural language processing to detect greenwashing and improve ESG ratings. AI tools also enable personalized green investment strategies and more automated reporting, but they raise challenges in ethical AI governance, algorithmic bias, regulatory compliance, and AI’s own carbon footprint. Two summary tables distill applications in (1) risk and investment management and (2) ESG and sustainability reporting. We conclude with a focused interdisciplinary research agenda for responsible AI in green finance.

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Publication Details

Journal
Discover Sustainability
Published
2026-03-26
DOI
https://doi.org/10.1007/s43621-026-02980-w
Primary Topic
Sustainable Finance and Green Bonds
Type
article
Field-Weighted Citation Impact
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article

Artificial intelligence applications for advancing sustainable green finance

Nuraini Desty Nurmasari, Muhammad Roil Bilad
Discover Sustainability
Sustainable Finance and Green Bonds
article

Artificial intelligence applications for advancing sustainable green finance

Nuraini Desty Nurmasari, Muhammad Roil Bilad
article en

Abstract

Artificial Intelligence (AI) is increasingly pivotal in sustainable green finance, supporting risk analytics, investment management, environmental, social, and governance (ESG) assessment, and sustainable reporting. This review synthesizes recent literature on how machine learning, deep learning, and natural language processing enhance credit-risk modeling, portfolio optimization, and ESG evaluation. Key developments include default prediction using novel variables (e.g. household or climate data), deep learning for market forecasting and portfolio returns, and natural language processing to detect greenwashing and improve ESG ratings. AI tools also enable personalized green investment strategies and more automated reporting, but they raise challenges in ethical AI governance, algorithmic bias, regulatory compliance, and AI’s own carbon footprint. Two summary tables distill applications in (1) risk and investment management and (2) ESG and sustainability reporting. We conclude with a focused interdisciplinary research agenda for responsible AI in green finance.

Discover Sustainability
University of Mataram (ID), University of Brawijaya (ID), Universiti Brunei Darussalam (BN)
Openalex Percentile: Top 8%
Sustainable Finance and Green Bonds
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Artificial intelligence applications for advancing sustainable green finance — Nuraini Desty Nurmasari, Muhammad Roil Bilad · Discover Sustainability (2026) | TGRS Research Map | TGRS