Incorporating ESG in Decision Making for Responsible and Sustainable Investments using Machine Learning

Abstract

Over the years, the number of firms measuring and reporting environmental, social, and governance data has seen a massive shift due to the overwhelming demand and pressure from different stakeholders. The introduction of various international regulatory bodies like the Corporate Sustainability Reporting Directive (CSRD), has also been intentional in encouraging companies to disclose publicly documents like annual reports, integrated reports in regards to topics like social, environmental, employee affairs and human rights. When it comes to investing, ESG issues take into account a firm’s operational influence on the native environment. Customers, policy makers, investors, and regulators are exerting huge amount of pressure on Companies to carry out Environmental, Social, and Governance ("ESG") reporting also known as non-financial reporting. Sustainability reporting has previously exhibited numerous advantages to businesses as accurate data collection and reporting are essential for managing the company’s sustainability performance as well as improving financial decision making. It is vital for a company’s long-term performance to actively disclose and communicate its non-financial practices and approaches. Therefore, in order to answer questions like; “Is it vital for developing market firms to disclose non-financial information, such as that relating to environmental, social, and governance (ESG)?”, this paper will attempt to provide a deeper insight into ESG disclosure and the impact it has on Firm Performance using Machine Learning techniques (Regression) and performance Ratios (Return On Assets & Return On Equity).