2022 | Outstanding | Private Equity & Investment Firms | SDG1 | SDG10 | SDG11 | SDG12 | SDG13 | SDG14 | SDG15 | SDG16 | SDG17 | SDG2 | SDG3 | SDG4 | SDG5 | SDG6 | SDG7 | SDG8 | SDG9 | United States
MALENA (Machine Learning Environment, Social and Governance Analyst)

Company or Institution

International Finance Corporation (World Bank Group)


Private Equity & Investment Firms




United States

Sustainable Development Goals (SDGs)

SDG 1: No Poverty

SDG 2: Zero Hunger

SDG 3: Good Health and Well-being

SDG 4: Quality Education

SDG 5: Gender Equality

SDG 6: Clean Water and Sanitation

SDG 7: Affordable and Clean Energy

SDG 8: Decent Work and Economic Growth

SDG 9: Industry, Innovation and Infrastructure

SDG 10: Reduced Inequality

SDG 11: Sustainable Cities and Communities

SDG 12: Responsible Consumption and Production

SDG 13: Climate Action

SDG 14: Life Below Water

SDG 15: Life on Land

SDG 16: Peace and Justice Strong Institutions

SDG 17: Partnerships to achieve the Goal

General description of the AI solution

MALENA or Machine Learning Environment, Social and Governance Analyst is an artificial intelligence (AI) natural language processing (NLP) solution for rapid review of ESG text developed by the International Finance Corporation (IFC) to make SDG-integrated investments in emerging markets. MALENA can identify 1,200+ environmental, social and governance (ESG) risk terms and conducts sentiment analysis to assign positive, negative, or neutral sentiment to risk terms based on context. This risk term taxonomy maps to all 17 SDGs, 72 underlying targets, and 102 indicators.
Version 1.0 was launched in July 2022 for limited release to asset managers, development finance institutions, financial institutions, export credit agencies, and private equity funds. Version 1.0 performs at 90% accuracy and has profiles for 24,000 emerging market companies, 7 regions, 186 countries, 36 sectors, and 83 ESG topics. Over 2022, MALENA was updated to analyze corporate governance and climate risk terms making it an integrated ESG model.
By analyzing unstructured ESG data at scale, MALENA complements traditional ESG data providers where coverage is missing, increases analyst productivity, enhances risk identification, and improves ESG integration. IFC proposes to make MALENA available to investors to create SDG-aligned investment portfolios. MALENA’s business architecture is based on Azure Databricks, the World Bank Group Enterprise Architecture approved data science platform. IFC is exploring how to include Amazon Web Services in the technology stack to address optical character recognition needs. Version 2.0 is planned for wide release in July 2023 including a global public good version. IFC is pleased to continue to advance this original initiative which places AI at the center of a solution to address the investment gap needed to meet the SDGs. Continued recognition by IRCAI will amplify the message of the development role of data, data science, and AI while signaling the potential for development finance to drive innovation.

Github, open data repository, prototype or working demo



– Curmally, Atiyah, Blaise W. Sandwidi, and Aditi Jagtiani. “Artificial Intelligence solutions for environmental and social impact assessments.” In Handbook of Environmental Impact Assessment, edited by Alberto Fonseca. Cheltenham, UK: Edward Elgar Publishing Ltd., 2022.
– Curmally, Atiyah. “Harnessing AI to Drive Better Investment Outcomes.” IFC Insights, Issue 37, September 14, 2022.
– Amundi Asset Management and International Finance Corporation. Artificial Intelligence Solutions to Support Environmental, Social, and Governance Integration in Emerging Markets. Paris – Washington DC: Amundi Asset Management and International Finance Corporation, 2021.




Public Exposure


International Research Centre
on Artificial Intelligence (IRCAI)
under the auspices of UNESCO 

Jožef Stefan Institute
Jamova cesta 39
SI-1000 Ljubljana



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