This paper explores the intersection of climate change policies with banking supervisory law. Statutory mandates define banking supervisory agencies’ objectives, functions and powers. Policies that aim to address climate change risks appear fully germane to banking supervisors’ main objective of safety and soundness. As such, banking supervisory agencies have a duty to address climate risks in light of their mandate. A mandate that is not anchored on safety and soundness in light of best practice would blur the accountability of banking supervisory agencies and undermine their legitimacy also with respect to climate. While legal changes can help provide greater legal certaintly, particularly given the long-term perspective of climate change, bank supervisory agencies can take action without fundamental reforms of their legal framework. Accordingly, they have set expectations or requirements for banks to incorporate climate into their strategy and business model, risk management, and governance. A combination of legal instruments—based on soft law and hard law—helps to achieve this objective. Notwithstanding implementation challenges, taxonomies and disclosures remain important tools, and banking supervisors should assess their role in the development of such tools in light of their mandate. The key responsibility to address climate risks rests on banks, and corporate governance frameworks could assist.
Torsten Ehlers, Ulrike Elsenhuber, Kumar Jegarasasingam, and Eric Jondeau
Environmental, Social, and Governance (ESG) scores are a key tool for asset managers in designing and implementing ESG investment strategies. They, however, amalgamate a broad range of fundamentally different factors, creating ambiguity for investors as to the underlying drivers of higher or lower ESG scores. We explore the feasibility and performance of more targeted investment strategies based on specific ESG categories, by deconstructing ESG scores into their granular components. First, we investigate the characteristics of the various categories underlying ESG scores. Not all types of ESG categories lend themselves to more focused strategies, which is related to both limits to ESG data disclosure and the fundamental challenge of translating qualitative characteristics into quantitative measures. Second, we consider an investment scheme based on the exclusion of firms with the lowest scores in a given category of interest. In most cases, this strategy allows investors to substantially improve the ESG category score, with a marginal impact on financial performance relative to a broad stock market benchmark. The exclusion results in regional and sectoral biases relative to the benchmark, which may be undesirable for some investors.We then implement a “best-in-class” strategy by excluding firms with the lowest category scores and reinvesting the proceeds in firms with the highest scores, maintaining the same regional and sectoral composition. This approach reduces the tracking error of the portfolio and slightly improves its risk-adjusted performance, while still yielding a large gain in the targeted ESG category score.