Central bankers announced a groundbreaking advancement on Tuesday, revealing their utilization of artificial intelligence (AI) to gather data aimed at evaluating climate-related financial risks. This development comes at a crucial juncture as the influx of disclosures from banks and corporations is poised to escalate.
Collaborating entities including the Bank for International Settlements (BIS), the Bank of Spain, Germany’s Bundesbank, and the European Central Bank disclosed the deployment of their experimental Gaia AI project. Gaia was tasked with analyzing company disclosures pertaining to carbon emissions, green bond issuance, and voluntary net-zero commitments.
Regulatory bodies overseeing banks, insurers, and asset managers necessitate top-tier data to gauge the ramifications of climate change on financial institutions. However, the absence of a standardized reporting format subjects them to a fragmented landscape of public information dispersed across textual content, tables, and footnotes within annual reports.
In a joint statement, the central banks emphasized Gaia’s capacity to transcend disparities in definitions and disclosure frameworks across jurisdictions, thereby providing essential transparency. Gaia’s approach facilitates the comparison of indicators related to climate-related financial risks, despite variations in how data is reported by different companies.
Unlike conventional methodologies which require painstaking data retrieval efforts for each additional key performance indicator (KPI) or institution, Gaia streamlines the process. Its focus lies on the definition of each indicator rather than the labeling of data, enabling swift integration of new KPIs or institutions.
With impending mandatory climate-related disclosures mandated by global, US, and European Union regulations, Gaia’s analysis of 20 key indicators across 187 financial institutions over five years underscores the evolving landscape. While the results indicate a rising trend in commitments to net-zero targets and green bond issuance, disparities persist across geographical regions.
The adaptable design of Gaia presents a potential template for AI-enabled applications across a spectrum of use cases within central banks and the financial sector at large.
Looking ahead, the central banks contemplate the possibility of making Gaia publicly accessible as an open web-based service for analysts, signaling a commitment to advancing transparency and efficacy in climate risk analysis.
