Bridging the gap in ESG measurement: Using NLP to quantify environmental, social, and governance communication

Tobias Schimanski, Andrin Reding, Nico Reding, Julia Bingler, Mathias Kraus and Markus Leippold

Finance Research Letters, 2024, vol. 61, issue C

Abstract: Environmental, social, and governance (ESG) criteria take a central role in fostering sustainable development in economies. This paper introduces a class of novel Natural Language Processing (NLP) models to assess corporate disclosures in the ESG subdomains. Using over 13.8 million texts from reports and news, specific E, S, and G models were pretrained. Additionally, three 2k datasets were developed to classify ESG-related texts. The models effectively explain variations in ESG ratings, showcasing a robust method for enhancing transparency and accuracy in evaluating corporate sustainability. This approach addresses the gap in precise, transparent ESG measurement, advancing sustainable development in economies.

Keywords: ESG analysis in financial markets; Natural language processing; BERT model (search for similar items in EconPapers)
JEL-codes: C8 G2 G38 M48 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:61:y:2024:i:c:s1544612324000096

DOI: 10.1016/j.frl.2024.104979

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