Transition risk assessment practices pertaining to corporate exposures within banks require more granular data, better profiling, and stronger identification of future pockets of risk. To reach this conclusion, the ECB performed case study interviews and surveys of client files for counterparties expected to be associated with high levels of transition risk. The general finding highlighted in the report is that banks did not sufficiently collect greenhouse gas (GHG) emissions data and forward-looking trajectory information from their counterparties—leading to a failure to effectively measure risk and determine mitigating actions.
The report notes that collecting granular data at the level of the counterparty is unavoidable. Proxies had been recommended in the past, for lack of a better option. Yet, this time the focus was on the weaknesses associated with such methods for determining transition risk at the corporate exposure level. The average level of CO2 emissions for a given sector provides an indication of the sector’s carbon intensity but could lead to unwanted consequences. The overestimation of an individual counterparty’s exposure to transition risk or the failure to recognise ongoing transition enabling investments, could lead to over-provisioning or de-investment strategies. The former would limit a bank’s lending capacity, the later would limit a borrower’s access to funding, and both would be detrimental to steering each sector of the economy towards a sustainable future. Similarly, underestimating the emissions associated with a given counterparty could lead to a build-up of non-identified pockets of risk, which could materialise under, say, a policy change. Hence, accurate data on a counterparty level, and even on asset level, is a key goal for banks to allow for accurate and effective risk management.
The target is for banks to improve the soundness and comprehensiveness of their approaches without leading to unrealistic resource expenditure. Institutions could perform preliminary assessments of each economic sector’s role in the overall economy and establish how granular and elaborate their estimation of climate risks should be for each category. In effect, the 2022 climate stress test report published last July indicated that, on the 31st of December 2021, a non-negligible average of 21% of the total interest income earned by participating institutions was associated with highly emitting sectors such as mining and quarrying, the manufacture of coke and refined petroleum products, electricity, and so on.  It is important to note that those industries are generally the largest emitters in an economy but also the providers of essential inputs to sectors active in the secondary and tertiary industries. Under a disorderly transition scenario, the ill-performance of those sectors could cause major disruptions in the overall performance of our economies and lead to significant losses. Hence, it is paramount for banks that are exposed to those sectors to adapt their data collection and obtain granular data at the asset level. The goal is to build a realistic picture of what is required for such sectors to align to their emissions targets, to allocate exposures and set appropriate prices to finance their transition.
It is necessary for banks to keep funding corporates whilst creating the framework to maintain ensuing risks within the range of their current risk appetite. The aim is to do so with sound measurement that would allow for dynamic portfolio steering and correct pricing, at the individual counterparty level. Taking the example of the steel industry, iron ore reduction using hydrogen has the advantage of releasing water instead of CO2 in the treatment of iron oxides. Such changes in the production process are known methods that could drastically reduce emissions associated with the sector. On the other hand, such methods require a steady stream of sustainably produced hydrogen, which in turn will require a steady stream of green energy to sustainably extract hydrogen from water.  The banking sector will, in its role and capacity as a lender, need to turn those initiatives into practice at the global level. Consequently, granular asset level data and sound inclusion of transition pathways on a counterparty level are essential for banks to choose where to allocate their funds.
Models need to be designed to integrate such dynamic forward-looking perspectives. Metrics such as the probability of default are to be measured as a function of the borrower’s or the project’s distance from its net-zero emissions target. It should also factor in the assets and disruptive technologies in which the counterparty invests in to reach that target. The same applies to collaterals where energy performance or GHG emissions have an impact on valuation. Of course, such an exercise cannot be performed at the same level of granularity across all portions of a bank’s portfolio. The present recommendation is for banks to perform in depth data collection and develop forward-looking approaches proportional to the carbon intensity and the share of total exposures associated with a given sector.