Exploresearch (ISSN: 3048-815X) ( Vol. 03 | No. 3 | July - September, 2026 )

Advancing Green Finance through Artificial Intelligence for Sustainable Investment Decision-Making

Author: Ms. Shivangi Agrawal & Dr. Neha Sarin

This study investigates the integration of Artificial Intelligence (AI) into green finance investment strategies, with emphasis on renewable energy investment, Environmental, Social and Governance (ESG) assessment, portfolio optimization, and risk management. Historical financial and environmental data were analysed using Support Vector Machine (SVM), Random Forest, regression, predictive analytics, sentiment analysis, and Monte Carlo simulation. The AI-based approach achieved 98.65% accuracy and 98.75% recall in identifying profitable green investment opportunities. For renewable energy investments, the model predicted an expected return of 7.8%, risk of 8.3%, and a Sharpe ratio of 0.94. ESG analysis reported 92.5% classification accuracy and 93.5% precision in identifying sustainable companies. Risk analysis indicated a 5.5% probability of significant loss and a 7.2% risk-adjusted return. The model also projected annual green finance investment growth of 9.3% and an increase of $120 billion over five years. These findings indicate that AI can strengthen investment screening, ESG evaluation, risk-adjusted portfolio decisions, and the scalability of green finance while supporting the transition toward a low-carbon economy.

Agrawal, S. & Sarin, N. (2026). Advancing Green Finance through Artificial Intelligence for Sustainable Investment Decision-Making. Exploresearch, 03(03), 147–157. https://doi.org/10.62823/exre/03.03.272

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DOI:

Article DOI: 10.62823/exre/03.03.272

DOI URL: https://doi.org/10.62823/exre/03.03.272

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