This paper describes the potential approaches for institutional investors and asset managers to align their investment strategies for emerging markets with the Sustainable Development Goals through environmental, social, and governance (ESG)-integrated investments. Although the global ESG fund universe has tripled since 2015, most of this growth has been in the developed world.[1] A key challenge limiting the ability of institutional investors and asset managers to invest in emerging market issuances is the lack of ESG data.
Investors are making use of Artificial Intelligence (AI) and emerging technologies to support ESG data collection and analysis for both developed and emerging markets. Amundi and IFC are collaborating on ESG research, analytics, and tools to increase ESG data, advance issuer transparency, create reporting infrastructure for emerging markets, and support harmonization of reporting standards. In this paper, Amundi and IFC describe the results from developing and testing an ESG-domain-specific Natural Language Processing application (esgNLP) to support the analysis of the ESG performance of emerging market financial institution (FI) issuers of fixed income bonds. The results find the potential for esgNLP analysis to validate Amundi’s controversy and ESG scores, help identify gaps in performance and areas for improvement at the issuer level, and supplement information where scores are absent.
The paper recommends support for open-access ESG and impact data and analytical tools for emerging markets, reinforces the need to extend analytics to the development of additional AI and NLP solutions in the short term, and proposes cross-industry collaborations between big finance and big tech to address ESG integration.
[1] Source: Emre Tiftik et al., “IIF Green Weekly Insight: ESG Funds Deliver,” Institute of International Finance, 2020, https://www.iif.com/Portals/0/Files/content/200618WeeklyInsight_vf.pdf.
