chatReport: Democratizing Sustainability Disclosure Analysis through LLM-based Tools

Jingwei Ni, Julia Bingler, Chiara Colesanti Senni, Mathias Kraus, Glen Gostlow, Tobias Schimanski, Dominik Stammbach, Saeid Vaghefi, Qian Wang, Nicolas Webersinke, Tobias Wekhof, Tingyu Yu and Markus Leippold
Additional contact information
Jingwei Ni: ETH Zurich
Julia Bingler: University of Oxford
Chiara Colesanti Senni: ETH Zürich; University of Zurich
Mathias Kraus: University of Erlangen
Glen Gostlow: University of Zurich
Tobias Schimanski: University of Zurich
Dominik Stammbach: ETH Zurich
Saeid Vaghefi: University of Zurich
Qian Wang: University of Zurich
Nicolas Webersinke: Friedrich-Alexander-Universität Erlangen-Nürnberg
Tobias Wekhof: ETH Zürich
Tingyu Yu: University of Zurich
Markus Leippold: University of Zurich; Swiss Finance Institute

No 23-111, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: This paper introduces a novel approach to enhance Large Language Models (LLMs) with expert knowledge to automate the analysis of corporate sustainability reports by benchmarking them against the Task Force for Climate-Related Financial Disclosures (TCFD) recommendations. Corporate sustainability reports are crucial in assessing organizations' environmental and social risks and impacts. However, analyzing these reports' vast amounts of information makes human analysis often too costly. As a result, only a few entities worldwide have the resources to analyze these reports, which could lead to a lack of transparency. While AI-powered tools can automatically analyze the data, they are prone to inaccuracies as they lack domain-specific expertise. This paper introduces a novel approach to enhance LLMs with expert knowledge to automate the analysis of corporate sustainability reports. We christen our tool \textsc{chatReport}, and apply it in a first use case to assess corporate climate risk disclosures following the TCFD recommendations. ChatReport results from collaborating with experts in climate science, finance, economic policy, and computer science, demonstrating how domain experts can be involved in developing AI tools. We make our prompt templates, generated data, and scores available to the public to encourage transparency.

Keywords: Task Force for Climate-Related Financial Disclosures; Sustainability Report; Large Language Model; ChatGPT (search for similar items in EconPapers)
Pages: 32 pages
Date: 2023-11
New Economics Papers: this item is included in nep-ain, nep-big, nep-cmp and nep-env
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp23111

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