BIS Addresses Data Gaps and Macro-Prudential Policy for Climate Risks

The FSI paper discusses the challenges associated with designing and implementing macro-prudential policies to address the system-wide effects of climate-related financial risks, with a focus on measures that target banks’ underwriting practices with a view to containing the accumulation of systemic risks over time. The paper first reviews the core features of macro-prudential policies, including definitions, objectives, and potential tools. It then discusses the challenges and trade-offs that stem from the unique features of the climate-related financial risks that have a bearing on the design, implementation, and effectiveness of the macro-prudential policies for addressing such risks. Finally, the paper discusses policy options and the complexity associated with their implementation, before concluding that implementing such a macro-prudential policy for climate-related financial risks, which could helpfully complement an adequately adjusted micro-prudential framework, will not be an easy task. This is because such a framework would be based on the existence of sufficiently clear and granular data and taxonomies that would allow banks and supervisors to determine the scope of application of this instrument. While meeting such complex requirements is likely to be challenging, at least at this stage, failure to adjust the scope of application of macroprudential policies for addressing climate-related financial risks might render such macro-prudential policies ineffective and potentially counterproductive for financial stability..

The Project Gaia will establish an open, web-based tool to facilitate climate and environmental risk assessments based on a large corpus of publicly available corporate reports. Along with the Eurosystem project partners, the Bank of Spain, the Deutsche Bundesbank, and the European Central Bank are involved in this project. Besides classical machine learning approaches, Project Gaia will explore how large language models (such as GPT) might be integrated into a reliable workflow for fact-finding. Project Gaia will explore the possibilities of standardizing different globally recognized Environmental, social, and governance (ESG) disclosures as well as the potential of using natural language processing, including the use of large language models to extract and structure climate-related data. These state-of-the-art tools will make unstructured data more usable, facilitating climate risk assessments. The first project output will be a repository of textual corporate reports, coupled with a full-text and semantic search engine to identify specific sustainability-related disclosures. In the second stage, the project will build a graphical user interface (GUI) to access the company-level climate-related database. The GUI will include data visualization tools to facilitate climate and environmental risk assessments. Project Gaia will explore the possibilities of standardizing different globally recognized ESG disclosures, using the publicly available company reports as its core sources of information. The prototype will consist of a data-agnostic model that meets the needs of the central banking community. It will feature the required flexibility and open access to the data as well as the underlying algorithms.

Related Links

• FSI Paper on Macro-Prudential Policies for Climate Risks
• FSI Paper on Macroprudential Policies for Climate Risks (PDF)
• Press Release on Project Gaia