Assessing the data challenges of climate-related disclosures in european banks. A text mining study

Angel Ivan Moreno, Teresa Caminero
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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.
评估欧洲银行披露气候相关信息的数据挑战。文本挖掘研究
政府间气候变化专门委员会(IPCC)估计,到 2050 年应实现全球净零排放。为此,许多私营企业承诺到 2050 年实现净零排放。气候数据指导委员会 (CDSC) 正致力于创建一个全球气候信息披露中央数字库,以应对当前的数据挑战。 本文评估了欧洲金融机构在克服气候数据指导委员会提出的数据挑战方面所取得的进展。我们采用文本挖掘方法,结合应用商业大型语言模型(LLM)进行上下文验证,通过分析欧洲央行直接监管下的大多数重要银行在 2019 年至 2021 年期间的环境、社会和公司治理报告中披露的 23 项高精细信息,计算出温室气体披露指数(GHGDI)。然后将该指数与 CDP 分数进行比较。结果表明,未按要求向 CDP 报告的机构与温室气体指数较低之间存在一定的相关性。CDP 分数高的机构并不一定与温室气体指数高相关。
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