Data Lake / Data Warehouse Modernization · Document Processing · Risk Management
As emerging markets seek to attract more capital to spur economic development, investors are considering ESG issues such as impacts on local communities, value of goods generated, and greenhouse gas emissions when selecting investments. The International Finance Corporation (IFC) advances economic development and improves the lives of people by encouraging the growth of the private sector in developing countries.
Reported impact
International Finance Corporation (IFC) achieved measurable business impact on Databricks, including 19,000 Sentences analyzed per; 1,200 ESG risk terms; Previously reliant on manual processes and limited data processing tools, the operationalization of ML models to analyze roughly 21 million pages of text took months to complete..
As emerging markets seek to attract more capital to spur economic development, investors are considering ESG issues such as impacts on local communities, value of goods generated, and greenhouse gas emissions when selecting investments. The International Finance Corporation (IFC) advances economic development and improves the lives of people by encouraging the growth of the private sector in developing countries. Using MALENA — IFC’s AI-powered ESG analytics platform — users can extract meaningful insights from unstructured ESG data at scale, enabling rapid analysis, increasing productivity, and building confidence.
Unstructured documents and reference data lands in Databricks and is transformed through managed pipelines stored in Delta Lake under Unity Catalog governance
1,200 ESG risk terms
19,000 Sentences analyzed per
As emerging markets seek to attract more capital to spur economic development, investors are considering ESG issues such as impacts on local communities, value of goods generated, and greenhouse gas emissions when selecting investments.
IFC has successfully scaled the MALENA platform through the use of Databricks Data + AI Platform and leveraged the distinct advantages offered by the lakehouse architecture namely, optimal connectivity with Azure Data Lake coupled with GPU computing, features supporting the development of machine learning solutions, and robust and consistent infrastructure for data engineering and machine learning.
Previously reliant on manual processes and limited data processing tools, the operationalization of ML models to analyze roughly 21 million pages of text took months to complete.
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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