Environmental, social, and governance (ESG) and artificial intelligence in finance: State-of-the-art and research takeaways
Study maps ESG and AI in finance, identifying research themes, trends, and AI techniques across eight domains.
What it examines
This study systematically maps the research landscape of ESG and AI in finance, identifying knowledge gaps and potential research areas. It focuses on key themes, research intensity, and AI techniques used, aiming to consolidate knowledge and offer insights for researchers and practitioners.
What it concludes
The study underscores the importance of integrating ESG and AI in finance for sustainable practices. Future research should explore emerging AI techniques and regulatory impacts. Potential applications include enhancing ESG data analysis and developing responsible AI solutions.
Evidence objects
The study underscores the importance of integrating ESG and AI in finance for sustainable practices. Future research should explore emerging AI techniques and regulatory impacts. Potential applications include enhancing ESG data analysis and developing responsible AI solutions.
key_findings bullet 1 · key_findings · validation V0
Raw abstract and provenance
Vol.:(0123456789)Artificial Intelligence Review (2024) 57:76 https://doi.org/10.1007/s10462-024-10708-3 1 3 Environmental, social, and?governance (ESG) and?artificial intelligence in?finance: State?of?the?art and?research takeaways Tristan?Lim1,2 Published online: 28 February 2024 ? The Author(s) 2024 Abstract The rapidly growing research landscape in finance, encompassing environmental, social, and governance (ESG) topics and associated Artificial Intelligence (AI) applications, presents challenges for both new researchers and seasoned practitioners. This study aims to systematically map the research area, identify knowledge gaps, and examine potential research areas for researchers and practitioners. The investigation focuses on three primary research questions: the main research themes concerning ESG and AI in finance, the evolu- tion of research intensity and interest in these areas, and the application and evolution of AI techniques specifically in research studies within
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