International Finance Corporation (IFC) is using data and AI to build machine learning solutions that create analytical capacity to support the review of ESG issues at scale. This includes natural language processing and requires entity recognition and other applications to support the work of IFC’s experts and other investors working in emerging markets. These algorithms are available via IFC’s Machine Learning ESG Analyst (MALENA) platform to enable rapid analysis, increase productivity, and build investor confidence. In this manner, IFC, a development finance institution with the mandate to address poverty in emerging markets, is making use of its historical datasets and open source AI solutions to build custom-AI applications that democratize access to ESG capacity to read and classify text.
In this session, you will learn the unique flexibility of the Apache Spark™ ecosystem from Databricks and how that has allowed IFC’s MALENA project to connect to scalable data lake storage, use different natural language processing models and seamlessly adopt MLOps.
Talk by: Atiyah Curmally and Blaise Sandwidi
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