Overcoming Complexity in ESG Investing : The Role of Generative AI Integration in Identifying Contextual ESG Factors

The integration of GPT 3.5, an advanced language model, with Environmental, Social, and Governance (ESG) criteria has the potential to revolutionize the investment industry by providing accurate and relevant information to investors. This study explores GPT 3.5's capabilities in responding to ESG-related prompts and its applications in ESG investing. By developing an ESG classifier module, GPT 3.5 can identify relevant ESG factors for companies, enabling investors to make informed decisions aligned with their values. The module also allows analysis of industries' ESG performance, aiding in selecting sustainable and socially responsible investments. Following the data collection, cleaning, and analysis, the results reveal a 20% dependence of stock returns on ESG-related news, leading to the development of a tool that tracks this relationship, complementing quantitative strategies and facilitating ESG-informed investment decisions. This research showcases GPT 3.5's ability to generate accurate responses to ESG prompts, emphasizing the importance of high-quality training data. The study also contributes to the growing literature on AI in ESG research and presents a framework for future investigations. The integration of AI with ESG criteria holds promise for improving decision-making in investments and promoting sustainability and social responsibility practices