The importance of an effective green transition is now universally acknowledged, likewise the need of engaging the banking system to help funding the transition itself.
In recent years, numerous banking regulators and central banks produced reports to discuss how to align prudential regulation, the key structure of modern supervision, to the goals of the transition, especially the Paris Agreement. Moreover, notably in Europe, the struggle against climate change is producing a wide regulatory framework, with the EU taxonomy at the forefront of the trend.
We have published a series of articles to propose a way to incorporate environmental externalities into banking regulation, published in 2019, 2021 and 2022. Notwithstanding the growing interest in these topics, the discussion has not reached yet an operational stage. For sure, changing the intricate structure of banking regulation is not an easy task, but the lack of progress on this front is a serious obstacle to the transition.
Here we try to sum up what should be the logic of an environment-based banking regulation.
Principles for effective environmental risk-weighted assessments
The starting point, as far as the banking regulation is concerned, is the role of the risk-weighted assets (RWA). Although criticised for a number of reasons, they are still the key of microprudential supervision.
They work as follows: every asset a bank has in its books yields a risk and hence produces a minimum amount of capital against that risk. Environment-related risks (both physical and transitional) are overlooked by the ordinary RWA structure, making it imperative that those risks are introduced into RWAs themselves to help the transition.
As a result of our work, we have identified 10 characteristics that environment-based RWAs (or ERWAs) should possess to be effective. We think they are the most important and easy to assess in order to help the creation of any green prudential rule. For a discussion of these issues from a regulatory standpoint, see papers published by the Basel Committee on Banking Standards, the Financial Stability Board and the European Banking Authority.
- Already available data: banks already report a massive amount of credit data to their regulators. Ideally, ERWAs should work with data already available or easy to produce for the regulated entities.
- Easy to enforce: banking regulation is very complicated (Basel III goes on for hundreds of pages even without taking into account technical appendixes). An effective ERWA should mimic the existing RWA, allowing for a different weight that includes also environmental externalities.
- Less (assumptions) is more: banking regulation is frequently criticised because it is allegedly based on a thin theoretical rationale. The fewer assumptions a regulatory tool has behind it, the less it is matter of opinion and open to manipulation.
- Microprudential: ERWAs should work as a microprudential tool, as it is already the case with RWAs.
- Based on appropriate environmental approaches reflecting a life-cycle logic: risks related to environmental externalities are distributed in the productive process of a commodity or a service. Therefore, ERWAs should be able to consider the carbon footprint – or even better, the whole range of environmental costs footprint – of an investment to capture the whole risk behind it.
- Symmetric and all encompassing: the logic of RWAs is to compare the risks inside the whole of a bank’s assets, hence ERWAs should work for every asset. Although credit risk makes more than 80% of RWA composition for the average EU bank, it should also be easy to apply to bonds and other assets.
- Feasible for finance industry: if a tool would require, say, doubling the own funds of banks in a couple of years, it would be impossible to enforce without affecting bank operations and the economy as a whole. Feasibility also entails a gradualist approach, as is always the case with banking regulation.
- Empirically testable: calculation of ERWAs should be based on well-rooted indicators and recognised methods to aggregate risks related to environmental externalities, so that ERWAs remain easy to measure and fast to be put in practice for empirical tests, allowing for rapid deployment.
- Mapping into the existing environment-related rules: many policymakers are intensifying their efforts to produce environment-related taxonomies to drive future investments. This is especially true for the EU, in particular with the taxonomy. It is important that the tool is able to connect and is consistent with those rules.
- Giving the right incentive to the banks: the tool should incentivise banks and other financial operators to gradually change their business model to favor the transition. This is already the logic behind RWAs that incentivises behaviours considered to be more prudent, like funding mortgages with low loan-to-value ratios or having a more granular banking book.
With these aspects in mind, we can appraise the different options proposed so far. Ideally, a tool should embed all the features we discussed.
The best-known approach is the green supporting factor. It could work to encourage green loans but, being asymmetrical (it only provides a premium, not a sanction as well), it could not mimic how RWAs work. It also leaves brown investment untouched, slowing down the transition.
A second example is the use of climate stress tests or scenario analyses. These exercises are useful to assess the banking industry situation, but they have a systemic logic and they are macroprudential tools. As such, they cannot incentivise individual banks to decarbonize their assets.
In our aforementioned papers, we explain in detail how to build a feasible bridge between RWAs and environmental externalities, and we explain how our proposal satisfies the characteristics outlined above. At any rate, broadly speaking it is important that regulators, policymakers and scholars deliver the practical sides of a greener finance, rather than restricting their efforts to research and data collection.
Otherwise, discussions on the transition will remain just words while we need to speed up implementation.
This page was last updated June 29, 2022
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