AI-Powered ESG Rating of Russian Companies

The involvement of companies in Environmental, Social, and Governance (ESG) practices has garnered significant public interest in recent years. With the introduction of mandatory reporting requirements and the growing emphasis on sustainability in investment decisions, the demand for transparent and reliable ESG ratings is increasing. Despite the growing significance of ESG ratings, there remains a shortage of automated methods for predicting these ratings in the Russian market. Various rating agencies use different methodologies to calculate these scores, typically relying on extensive and time-consuming manual analysis of substantial reporting data for each company. This situation raises the question of whether automating the process of rating companies based on their ESG compliance is feasible. To explore this possibility, a study was conducted to replicate the ESG rating calculation process of the RAEX agency for Russian companies using publicly available data from company websites and machine learning techniques. The results suggest that this approach can accurately predict ESG ratings for Russian companies, indicating its potential as a valuable tool for automating ESG rating predictions and evaluating a company’s overall profile.