Environmental, Social, and Governance

Environmental, Social, and Governance (ESG) research focuses on developing methods for accurately assessing and utilizing ESG information to improve corporate sustainability and investment decision-making. Current research heavily employs large language models (LLMs), such as BERT and its variants, along with machine learning techniques like Support Vector Machines and Reinforcement Learning, to analyze textual data (e.g., news articles, corporate disclosures) and extract meaningful ESG insights. This work is significant because it addresses the challenges of incomplete and inconsistent ESG data, enabling more robust ESG scoring, improved risk assessment, and ultimately, more informed and responsible investment strategies.