Assessing the Data Challenges of Climate-Related Disclosures in European Banks. A Text Mining Study
23 Pages Posted: 5 Oct 2023 Last revised: 2 Dec 2023
Date Written: September 26, 2023
Abstract
The Intergovernmental Panel on Climate Change (IPCC) estimates that global net-zero should be achieved by 2050. To this end, many private firms are pledging to reach net-zero emissions by 2050. The Climate Data Steering Committee (CDSC) is working on an initiative to create a global central digital repository of climate disclosures, which aims to address the current data challenges.
This paper assesses the progress within European financial institutions towards overcoming the data challenges outlined by the CDSC. Using a text-mining approach, coupled with the application of commercial Large Language Models (LLM) for context verification, we calculate a Greenhouse Gas Disclosure Index (GHGDI), by analysing 23 highly granular disclosures in the ESG reports between 2019 and 2021 of most of the significant banks under the ECB’s direct supervision. This index is then compared with the CDP score. The results indicate a moderate correlation between institutions not reporting to CDP upon request and a low GHGDI. Institutions with a high CDP score do not necessarily correlate with a high GHGDI.
Keywords: ESG, sustainability, environment, climate change, carbon emissions, natural language processing, climate data challenges, OpenAI’s ChatGPT, Google’s text-bison
JEL Classification: C88, G32, Q56
Suggested Citation: Suggested Citation