As the world moves towards a more sustainable future, banks have come under increasing scrutiny for their environmental, social and governance (ESG) practices. Pillar III ESG is one of the regulatory efforts to address this issue, and banks have now reported their first Pillar III ESG reports. The first reporting rounds seemed to be difficult, and the lack of comparability between the banks is an issue.
Pillar III is a global regulatory framework for financial institutions, designed to promote transparency and market discipline in the financial sector. Pillar III ESG is an addition to this framework, which requires large banks to disclose ten quantitative templates of their climate-related risks and how they are to mitigate them. The first set of disclosures covered five templates while the remaining templates are to be disclosed at a later date.
The ten quantitative templates can be divided into three categories: transition risk, physical risk and mitigation actions. In transition risk, banks disclose how much of their exposures face more risk from the inevitable move towards a more carbon neutral environment. Physical risk addresses the extent to which the bank’s exposures face risk from actual climate change related events, such as the increase of floods or the scarcity of water. Finally, mitigation actions disclose how much of the bank's exposures can be interpreted as green, as defined by the EU Taxonomy.
In the first template, banks disclose their exposures against the most polluting industries. One of the most difficult measures in this template was the Paris aligned benchmark exclusions, where banks reported all their exposures that are excluded from Paris Aligned Benchmarks based on Benchmark Regulation (2020/1818). What made this data point particularly difficult was the fact that banks needed certain information regarding their customers, which they most likely did not have beforehand, nor did their customers need to report this previously. For instance, banks needed to know how large share of their customers’ revenue was based on oil fuels or hard coal and lignite. When it comes to small customers, this kind of information is nearly impossible to get.
Banks used various methodologies to tackle the issue, making comparisons of the results difficult. The disclosed methodologies revealed that the PAB analysis was mostly done through internal analysis, or by buying the required data from third-party vendors, such as Moody's. Using third-party vendors for this column is an option for acquiring the information about large corporate customers, but the data vendors lack the information about SME customers, which make up a large share of the customer portfolio in Nordic banks. Internal analysis is also very time consuming and difficult, since most of the small customers do not publish the relevant information themselves.
The exposures against the PAB excluded companies compared to the total exposures against the most polluting industries varied from 0% to almost 7%. Differences in methodologies explain most of the variance in reported figures. For example, OP and Deutsche Bank had the highest share of PAB excluded companies in the peer group with internal analysis, while Nordea and Handelsbanken used data from Moody’s and reported a lower ratio of PAB excluded companies.
In Template 2, banks disclose the energy efficiency of their real estate collaterals. Reported energy efficiencies are either based on the bank’s internal models or on official EPC labels. OP had the highest weighted average energy requirement in their real estate collaterals (228 kWh/m²), followed by Santander (189 kWh/m²) and Nordea (168 kWh/m²). Meanwhile, SEB had the best energy efficiency (115 kWh/m²), but also the highest amount of energy efficiency information missing from their collaterals, with over 50% of their collaterals without information. Swedbank, Handelsbanken and Nordea had done the best job within their energy efficiency modelling, as they were able to model or acquire energy efficiency information for almost all their real estate collaterals.
This template had the least methodological differences, and the reporting instructions were easiest to interpret. Even so, the reported figures had surprisingly large deviations between the Nordic banks. This could imply that the efficiency models developed by the banks still have differences within the input data and methodologies.
In template 5, banks disclosed information on how much of their exposures face physical risk caused by climate change events, such as floods or droughts. All the banks in the examined peer group used external data sources together with internal analysis to report exposures facing physical risk. External data was used to gather information on where, geographically, physical risk was present, and after that, to map exposures’ locations against this information. Some of the external data sources used were Moody’s Climate Risk Assessment, Maplecroft’s Index and various flood maps from different countries’ environmental institutes. However, this template requires banks to have location-specific information on their exposures, which most of the peer group did not have, causing differences in the reported figures. For instance, based on the disclosed methodologies, Deutsche Bank was the only one that reported physical risks based on actual location-specific information of its exposures.
Scope limitations were often used to reduce the number of exposures to be analysed. While the template requires to analyse various sectors, loans collateralized by immovable property were the most focused area in physical risks. Some banks, such as Nordea, Swedbank and SEB, even focused their analysis only on real estate collaterals. Finally, most of the banks did not use the actual customer location data according to the published methodologies, which also causes variations on the figures reported.
In the graph below, we looked at the ratio of exposures under physical risk to total assets. From the peer group, Deutsche Bank stood out with a ratio of over 30% under physical risk, whereas the rest of the peer group had a ratio of 5% to 15%. Overall, we can see variations between the Nordic and European banks. Nordic banks had a heavy focus on the loans collateralized by immovable property, while Deutsche Bank and Santander analysed other sectors and regions outside of Europe. The difference between Deutsche Bank and its peer group could be possibly stem from its large geographical reach outside of Europe, and the use of better location-specific information from S&P.
The scope of the pillar III ESG reporting will extend in the near future. At the end of 2023, banks will report three additional templates related to the EU taxonomy, followed by BTAR templates in 2024. BTAR ratio will be extremely challenging for the banks, as the scope from the EU taxonomy will widen towards the smaller customers that are not required to report required figures themselves. Also, as seen in the EBA Roadmap on Sustainable Finance, the scope could also widen towards the other four taxonomy objectives in the future.
BearingPoint has helped Nordic banks to implement ESG regulatory requirements and data capabilities. Based on the study findings and numerous discussions with the banks, by focusing on automatization, ESG data and governance, institutions can better tackle the numerous challenges and opportunities ESG regulation is bringing.
This analysis was just a glimpse of the full ESG reporting analysis done by BearingPoint. If you want to understand your institution’s situation compared to other European banks, please reach out to Lasse Kantonen or Matti Rajala.
Business Consultant, BearingPoint Finland
Manager, BearingPoint Finland
Business Analyst, BearingPoint Finland