New ECB climate-related data must be assessed with care; several limitations remain
The ECB has recently disclosed data on climate-related indicators. From a first glance, we see that investment funds seem to have the largest financed emissions and also the largest weighted average carbon intensity, but banks have the largest carbon footprint. The data also still has several limitations and must therefore be treated with care.
The ECB has recently disclosed data on climate-related indicators
From a first glance, we see that investment funds seem to have the largest financed emissions and also the largest weighted average carbon intensity…
…However, banks have the largest carbon footprint
It is therefore hard to draw conclusions in terms of financial institution’s exposure to transition risks
The ECB data also still has several limitations and must therefore be treated with care
The ECB has recently disclosed data on climate-related indicators at the euro area level (see ). These indicators will help policy makers to assess climate risks, and to better understand challenges and opportunities around the climate transition. However, the data still involves several limitations, which mean that, at this stage, the data is published as experimental statistics and should be used/interpreted with caution.
The recently disclosed data includes indicators across three different areas: (i) sustainable finance; (ii) carbon emissions financed by financial institutions; and (iii) physical risks. Below, we focus on the indicators for carbon emissions and intensity of the securities and loan portfolios of financial institutions, which also includes information on the financial sector’s exposure to counterparties with carbon-intensive business models. These indicators are mainly related to risks stemming from the climate transition.
How are indicators calculated
Before digging into preliminary conclusions that can be drawn from the ECB’s data, we focus first on how the main indicators are calculated. This will help to understand why different indicators may also yield different conclusions (more on this below).
From the indicators above, we can already assess that FE is mostly an indicator of absolute emissions (how much of the company’s total emissions can be attributed to the financed institution financing it). On the other hand, CI and WACI are mostly intensity indicators, which means that these refer to not absolute emissions, but rather how these emissions compare to the company’s revenues. Specifically looking at CI, this indicator represents a financial institution’s share of emissions (that is, proportional to the investment into the company), relative to its share of a company’s revenues. On the other hand, WACI focuses on how much weight a company’s emission intensity has in the financial institution’s portfolio. Hence, while CI takes into account only the share of emission intensity, WACI puts that into perspective by weighting that share across the financial institution’s portfolio value. The same is true for CFP, which is also takes into account the portfolio value. However, contrary to WACI, CFP uses as numerator the company’s absolute emissions.
All in all, FE and CI are indicators of how much a financial institution’s contributes to a company’s emissions, representing therefore indicators of how the financial sector contributes to the financing of high emitting economic activities. On the other hand, WACI and CFP are better indicators of a financial institution’s exposure to transition risks, as they take into account the financial institution’s portfolio value.
Below we have summarized a few of the key conclusions we can draw from the ECB’s data.
Investment funds have the largest financed emissions…
We start with the FE indicator. As shown in the chart below (left), clearly, investment funds have the largest absolute carbon footprint (that is, they account for the largest financed emissions) in comparison to other financial institutions (both in terms of scope 1 and scope 2 emissions). This does make sense, as investment funds also have the largest portfolios. This seems to be consistent across different asset classes, as both on the debt but also equity side, investment funds have the largest FE compared to other financial institutions (see chart below on the right side). It is therefore fair to assume that investment funds, due to their large portfolios, have been the largest contributors to the financing of high carbon emission activities.
…And finance the most carbon intensive companies, according to the WACI indicator
We take the analysis further by then evaluating the WACI. As we previously stated, WACI is a better indicator for exposure to transition risks, as it takes into account the size of a financial institution’s portfolio. As depicted in the chart below (left), the WACI is also higher for investment funds. Furthermore, banks’ loan portfolios have the smallest WACI (and therefore the smallest exposure to transition risk), in comparison to other financial institutions.
Moreover, as shown in the chart on the previous page (right side), the WACI for investment funds has decreased significantly over the years despite its still relatively high number. In absolute terms, the WACI from investment funds went from 273 tons of CO2 per EUR mn in 2018, to 232 in 2020. From a relatively perspective, however, the largest decrease came from insurance and pension funds, where WACI has decreased by a whopping 28% between 2018 to 2020. That makes sense, as insurance firms are significantly exposed to not only physical but also transition risks (which can cause losses in asset values) and have, therefore, an intrinsic motivation to reduce this exposure.
However, banks have the largest CFP
We move our analysis to the CFP indicator and from this perspective, we get to different conclusions. While deposit taking institutions (that is, banks), have the second highest WACI (behind investment funds), they have the highest CFP (see chart below). Hence, from a carbon footprint perspective, the banking sector seems to have the highest exposure to transition risks. This is however, not the case when looking exclusively at the banks’ loan portfolios. These still have (as is the case when measured by WACI) the smallest carbon footprint. These results are a bit puzzling, as this would imply that the biggest (transition) risk for banks stems from their investment portfolio, rather than their loan portfolio. While the majority of the banks’ investments may be directed towards ‘safer’ assets such as government / SSA bonds, this would imply that the small share that invests into corporates is overweight into carbon intensive companies.
The difference in conclusions drawn when taking into account CFP or WACI mainly relies on the fact that the former takes into account total assets of the company being financed, while this is not the case with WACI. Hence, a situation where a company’s assets decreases, while revenues and emissions remain equal (for example, due to a decrease in cash to pay down debt), would result in an increase of CFP, but not of WACI. It is therefore hard to draw meaningful conclusions around exposure to transition risks (more on this below).
Some countries have a consistently high WACI, regardless of the type of Financial Institution
The data of the ECB is also published on a country level. We compare country differences by first zooming into the WACI indicator. From the chart on the next page (right side), we see that banks’ located in Estonia, Slovakia and Austria have the largest WACI when looking exclusively at their securities portfolios (that is, excluding loans). On the other hand, as shown in the chart on the left, loan portfolio of banks located in Portugal, Slovakia and Greece show the largest WACI. The lack of consistency of WACIs from different types of portfolios across European countries indicates that there does not seem to be a strong correlation between the countries’ emissions/location, and their corresponding WACI. For example, Germany is a country that has high absolute emissions, low/average emissions per capita, but a very high loan portfolio WACI, while at the same time having one of the lowest WACIs for their securities portfolios. It is therefore likely that WACIs are more correlated with the financial institution’s individual (green) ambitions, rather than its location.
Nevertheless, when looking at the WACI from financial institutions’ portfolio of securities, there seems to be a consistency across financial institutions. With exception of a few countries (such as Lithuania, Latvia and Estonia), a WACI is high or low regardless of the type of financial institution. For example, Belgium, Germany and the Netherlands all have the lowest WACI across all different type of financial institutions.
Different conclusions to be drawn dependent on the indicator…
Overall, it seems that different ECB indicators yield different conclusions. As we previously stated, both WACI and CFP are used as indicators for financial institution’s exposure to transition risks. However, WACI and CFP are not always consistent, which means that sometimes a certain financial institution may have a high WACI, but a low CFP (or vice versa). It is therefore hard to see how WACI and CFP correlate with each other, which ultimately makes it hard to actually access exposure to transition risk. It would have therefore been easier to assess and process the ECB data if also individual data sets would have been made available. For example, company’s revenues, assets, emissions, as well as financial institutions’ portfolio values (all on an aggregate basis). This would have allowed for a better assessment in terms of to what extent are WACI and CFP inconsistent due to for example it being driven by the company’s assets.
…And data sets must be assessed taking into account limitations
Finally, the aforementioned information must be treated with care, given the limitations of the dataset. Firstly, the ECB discloses that the average coverage of total outstanding nominal amount with balance sheet and emission information represents only around 47% for the euro area across the years (2018, 2019 and 2020). Secondly, emissions also need to be read taken into account that they do not fully represent the entire universe. Owing to a lack of source data, emissions for firms outside of the EU ETS are imputed using the number of employees at sector level when available. Overall, the average share of imputed emissions for the euro area is 49%.
Finally, there might be an overlap between scope 1 and 2 emissions. For example, a firm’s scope 2 emissions might represent another firm’s scope 2. This would result in double counting. With that in mind, we have also hereby presented the emissions data separately (we have not accounted scope 1 and 2 together). However, the use of indicators involving scope 1 and 2 data separately might also yield different conclusions. It is therefore hard to draw conclusions and properly assess the new climate-related data by the ECB. The central bank is however aware of these limitations, and it aims to get into discussions with relevant stakeholders about how to improve the quality of the data. As such, the disclosure of climate-related data by the ECB is a clear sign of how committed it is to improve data availability on climate, and to ultimately use if efficiently in order to address issues such as climate change.