Green Intelligence in Finance: Artificial Intelligence-Driven ESG Analytics and Sustainable Investment Performance

Abstract

This study examined the role of artificial intelligence (AI)-driven Environmental, Social and Governance (ESG) analytics in enhancing sustainable investment performance. While traditional ESG ratings had been widely used in responsible investment strategies, they often suffered from data inconsistency, subjectivity and limited coverage of unstructured sustainability information. AI-based ESG systems were increasingly applied to extract deeper sustainability signals from corporate disclosures, reports and external data sources. Using portfolio-level analysis, this study compared the financial outcomes of portfolios constructed using AI-driven ESG indicators with those based on conventional ESG ratings. The results showed that AI-enhanced high-ESG portfolios achieved higher mean returns and superior Sharpe ratios than both AI-based low-ESG portfolios and traditionally rated ESG portfolios. In addition, AI-driven high-ESG portfolios demonstrated lower downside-risk exposure and smaller maximum drawdowns during market stress, indicating stronger resilience. Regression analysis further revealed that AI-derived ESG scores were more strongly associated with excess returns than traditional ESG metrics. These findings suggested that AI improved the informational efficiency of ESG assessment by capturing more accurate, forward-looking sustainability risks and opportunities. The study concluded that AI-driven ESG analytics strengthened the financial relevance of sustainability integration and supported better-informed investment decision-making. The results carried important implications for investors, regulators and corporations seeking to align AI deployment with high-integrity sustainable finance practices, while also highlighting the need for ethical and transparent AI governance in financial markets.

References

Albuquerque, R., Koskinen, Y., Yang, S., & Zhang, C. (2020). Resiliency of environmental and social stocks: An analysis of the exogenous COVID-19 market crash. The Review of Corporate Finance Studies, 9(3), 593–621. https://doi.org/10.1093/rcfs/cfaa011

Ali, A., & Rafiq-uz-Zaman, M. (2025). Institutional inertia vs. ethical innovation: A comparative analysis of AI governance at The Islamia University of Bahawalpur and Cambridge University Press. Contemporary Journal of Social Science Review, 3(4), 91–102. https://doi.org/10.63878/cjssr.v3i4.1695

Alshareef, M. N. (2025). Artificial intelligence-enhanced environmental, social, and governance disclosure quality and financial performance nexus in Saudi listed companies under Vision 2030. Sustainability, 17(16), Article 7421. https://doi.org/10.3390/su17167421

Bai, J., & Ng, S. (2023). Machine learning and finance. Journal of Economic Perspectives, 37(2), 195–216. https://doi.org/10.1257/jep.37.2.195

Berg, F., Kölbel, J., & Rigobon, R. (2022). Aggregate confusion: The divergence of ESG ratings. Review of Finance, 26(6), 1315–1344. https://doi.org/10.1093/rof/rfac033

Broadstock, D. C., Chan, K., Cheng, L. T. W., & Wang, X. (2021). The role of ESG performance during times of financial crisis: Evidence from COVID-19 in China. Finance Research Letters, 38, Article 101716. https://doi.org/10.1016/j.frl.2020.101716

Cao, J., Li, J., Li, W., & Zhou, Y. (2023). ESG, big data and investment decision-making. Journal of International Financial Markets, Institutions and Money, 85, Article 101757. https://doi.org/10.1016/j.intfin.2023.101757

Carlei, V. (2025). Outperforming ESG stocks portfolios: A machine learning approach to generate alpha on the S&P 500. Expert Systems with Applications, 260, Article 120157. https://doi.org/10.1016/j.eswa.2025.120157

Chen, M. A., Wu, Q., & Yang, B. (2019). How valuable is FinTech innovation? Review of Financial Studies, 32(5), 2062–2106. https://doi.org/10.1093/rfs/hhy130

Christensen, D. M., Hail, L., & Leuz, C. (2021). Mandatory CSR and sustainability reporting: Economic analysis and literature review. Review of Accounting Studies, 26(3), 1176–1248. https://doi.org/10.1007/s11142-021-09609-5

Dorfleitner, G., Halbritter, G., & Nguyen, M. (2022). The risk-return-ESG profile of sustainable mutual funds. Journal of Asset Management, 23(3), 177–192. https://doi.org/10.1057/s41260-021-00229-3

Drempetic, S., Klein, C., & Zwergel, B. (2020). The influence of firm size on the ESG score: Corporate sustainability ratings under review. Journal of Business Ethics, 167(2), 333–360. https://doi.org/10.1007/s10551-019-04164-1

Fatemi, A., Glaum, M., & Kaiser, S. (2018). ESG performance and firm value: The moderating role of disclosure. Global Finance Journal, 38, 45–64. https://doi.org/10.1016/j.gfj.2017.03.001

Fernando, G. D., Tripathy, A., & Truong, C. (2022). Corporate sustainability and firm performance: Evidence from global firms. Journal of Business Research, 153, 38–52. https://doi.org/10.1016/j.jbusres.2022.08.011

Friede, G., Busch, T., & Bassen, A. (2015). ESG and financial performance: Aggregated evidence from more than 2,000 empirical studies. Journal of Sustainable Finance & Investment, 5(4), 210–233. https://doi.org/10.1080/20430795.2015.1118917

Gibson Brandon, R., Krueger, P., & Schmidt, P. S. (2021). ESG rating disagreement and stock returns. Financial Analysts Journal, 77(4), 104–127. https://doi.org/10.1080/0015198X.2021.1950807

Grewal, J., Hauptmann, C., & Serafeim, G. (2023). Material sustainability information and stock price informativeness. Journal of Accounting and Economics, 75(1), Article 101430. https://doi.org/10.1287/mnsc.2021.4302

Hamdouni, A. (2025). The role of artificial intelligence in enhancing ESG performance. Journal of Risk and Financial Management, 18(10), Article 572. https://doi.org/10.3390/jrfm18100572

Huang, D., Huang, J., & Wan, J. (2023). ESG investment: A review of the literature. Pacific-Basin Finance Journal, 76, Article 102047. https://doi.org/10.1016/j.pacfin.2022.102047

Huang, R., & Renneboog, L. (2020). The effects of ESG ratings on firm performance. European Corporate Governance Institute - Finance Working Paper No. 722/2020. https://doi.org/10.2139/ssrn.3722732

Krueger, P., Sautner, Z., & Starks, L. T. (2020). The importance of climate risks for institutional investors. Review of Financial Studies, 33(3), 1067–1111. https://doi.org/10.1093/rfs/hhz137

Kumar, S., Managi, S., & Matsuda, A. (2022). Stock market response to COVID-19: Evidence from sustainability indices. Economic Analysis and Policy, 74, 44–58. https://doi.org/10.1016/j.eap.2022.01.004

Li, F., Mai, F., Shen, R., & Yan, X. (2020). Measuring corporate culture using machine learning. Review of Financial Studies, 33(5), 2326–2376. https://doi.org/10.1093/rfs/hhz080

Li, Z., Liao, G., & Wang, Z. (2023). ESG performance and financial performance: Evidence from global firms. Technological Forecasting and Social Change, 189, Article 122337. https://doi.org/10.1016/j.techfore.2023.122337

Lim, T. (2024). Environmental, social, and governance (ESG) and artificial intelligence in finance: State-of-the-art and research takeaways. Artificial Intelligence Review, 57(4), Article 76. https://doi.org/10.1007/s10462-024-10708-3

Liu, Y., Song, J., Zhou, B., & Liu, J. (2025). Artificial intelligence applications and corporate ESG performance. International Review of Economics & Finance, 104, Article 104559. https://doi.org/10.1016/j.iref.2025.104559

Pedersen, L. H., Fitzgibbons, S., & Pomorski, L. (2021). Responsible investing: The ESG-efficient frontier. Journal of Financial Economics, 142(2), 572–597. https://doi.org/10.1016/j.jfineco.2020.11.001

Rafiq-uz-Zaman, M. (2022). Redesign for 21st-century skills: Preparing learners for a rapidly changing workforce. Journal of Business Insight and Innovation, 1(2), 89–102. https://doi.org/10.5281/zenodo.17844804

Rafiq-uz-Zaman, M. (2023). Teacher training needs for skill-based education: A review of competencies, barriers, and professional development gaps. Inverge Journal of Social Sciences, 2(3), 166–182. https://doi.org/10.63544/ijss.v2i3.212

Raghunandan, A., & Rajgopal, S. (2022). Do ESG funds make stakeholder-friendly investments? Review of Accounting Studies, 27(3), 822–863. https://doi.org/10.1007/s11142-021-09636-y

Walz, U., & Wranik, P. (2023). Artificial intelligence in finance: Applications, risks and regulation. Journal of Banking Regulation, 24(1), 125–143. https://doi.org/10.1057/s41261-022-00194-5

Whelan, T., Atz, U., Van Holt, T., & Clark, C. (2021). ESG and financial performance: Uncovering the relationship. Journal of Sustainable Finance & Investment, 11(4), 311–330. https://doi.org/10.1080/20430795.2021.1920510

Widyawati, L. (2020). A systematic literature review of socially responsible investment and environmental social governance metrics. Business Strategy and the Environment, 29(2), 619–637. https://doi.org/10.1002/bse.2393

Wong, W., & Zhang, X. (2022). Is ESG investing a fad or the future? Evidence from global stock markets. Journal of International Financial Markets, Institutions and Money, 80, Article 101618. https://doi.org/10.1016/j.intfin.2022.101618

Xiao, Y., & Xiao, L. (2025). The impact of artificial intelligence-driven ESG practices on sustainable development performance of Chinese central state-owned enterprises. Scientific Reports, 15, Article 8548. https://doi.org/10.1038/s41598-025-17046-6