Institutional investors and asset managers are increasingly turning to artificial intelligence (AI) to align their emerging market investment strategies with the United Nations’ sustainable development goals. AI is proving instrumental in bridging gaps in environmental, social, and governance (ESG) data disclosures, enabling a reshaping of business models that drive both economic growth and societal progress.
Emerging markets (EMs) present attractive investment opportunities, with the potential for financial returns combined with positive social impact. ESG-integrated assets under management in these markets are projected to grow significantly, rising from $18.4 trillion in 2021 to an anticipated $33.9 trillion by 2026. Although ESG disclosure practices in EMs still trail those in developed markets, there has been rapid progress. For instance, in 2023, out of 62 EMs issuing sustainable bonds, 51% had some form of ESG and climate-related disclosure requirements. The International Financial Reporting Standards’ framework is expected to further enhance reporting in this area.
Regulatory bodies in EMs, such as Brazil’s Comissão de Valores Mobiliários, are increasingly indicating their intention to mandate ESG disclosures. Additionally, frameworks like India’s Business Responsibility and Sustainability Reporting, which requires the top 1,000 listed companies to disclose standardised ESG data, highlight a growing commitment to transparency and accountability.
As the demand for robust ESG disclosures grows, so does the need for solutions that can efficiently structure and analyse this information. AI-powered solutions are becoming increasingly relevant in this context, particularly in the aftermath of advancements like ChatGPT. AI applications are being utilised for corporate reporting, investor analysis, and regulatory oversight, offering significant improvements in the speed and efficiency of the ESG disclosure process. Companies providing ESG data, analytics, and software-as-a-service solutions are leveraging AI to help issuers and investors meet regulatory requirements and manage risks.
Some firms, such as Risk Insights, have integrated AI, machine learning, and big data analysis at the core of their ESG rating and analysis services, focusing on markets in sub-Saharan Africa. Similarly, RepRisk combines AI and advanced data science with human intelligence to assess ESG risks across both developed economies and emerging markets.
In December 2023, the World Bank introduced MALENA, an AI as a service tool developed by the International Finance Corporation. This tool, trained on decades of sustainability and ESG data, utilises natural language processing to analyse over 1,000 climate, gender, and ESG-related terms, offering insights through sentiment analysis. MALENA is designed specifically for emerging markets and has demonstrated high accuracy in its results, thanks to its specialised training.
The development of large language models, such as Open AI’s GPT and Meta’s Llama, has significantly advanced text summarisation, content interpretation, and analysis capabilities. These models have been particularly effective in addressing ESG-specific queries and improving the quality of answers generated from company disclosures. Moreover, these AI applications can identify missing or erroneous information, helping regulators and investors streamline their processes, enhance peer-to-peer benchmarking, and expedite project approvals.
Fidelity Emerging Markets Limited (LON:FEML) is an investment trust that aims to achieve long-term capital growth from an actively managed portfolio made up primarily of securities and financial instruments providing exposure to emerging markets companies, both listed and unlisted.
