Abstract

Environmental, Social, and Governance (ESG) factors are critical for investors and financing institutions like the Brazilian Development Bank (BNDES). Such institutions are currently working on setting up a framework to assess companies' ESG factors in their financing evaluation. In this study, we identify an opportunity to use Natural Language Processing (NLP) to improve the framework. This opportunity stems from the fact that the key documents for ESG analysis, such as the company's activity report (RAA), Environmental Impact Study (EIA), and Environmental Impact Report (RIMA), undergo manual screening and decomposition whilst being analyzed by specialists. By incorporating NLP, we aim to automate the classification of text passages from these reports and enhance the efficiency of the analysis process.

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