Response to consultation on draft ITS on Pillar disclosures on ESG risk
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In relation to Template 3, the units of measurement for energy and for CO2 emissions need to be specified. To do this we recommend that primary energy is used because it is both comprehensive, encompassing the scope 1 and 2 emissions of a building, and is already established as the unit of measurement for building energy requirements at European level. Moreover, for both primary energy and CO2 emissions the units should be normalised to m2 of floor area to ensure comparability. Lastly, we consider that instructions are needed as to how the performance of each individual asset should be weighted in order to derive the figures for reporting. We would recommend considering a weighting based on the value of outstanding loans against each property, sometimes referred to as a portfolio weighting approach.
While we consider that Template 4 represents an important step in seeking to assess transition risk, there are a number of weaknesses that require addressing in order to make it operational for financial institutions and for meaningful disclosure. Template 4 will require more detailed guidance to support financial institutions in preparing these alignment disclosures. This is required in order to ensure consistency, with guidance needed on the calculation and allocation methods, scope of sectors, eligible data sources and tools. We have provided more details of how we would see this working under our response to Question 6.
Draft Templates 2 and 4 provide a useful starting point for both disclosure of the time horizon for exposure and the misalignment of economic activities with sectoral decarbonisation pathways for climate change mitigation. These templates do not however fully fulfil the purpose of determining the possible extent of transition risk. This would have to be done by more comprehensively applying tools such as climate change scenario alignment and stress testing across the sectors disclosed. Please see our response to Question 6 for further information on Template 4.
Draft Template 3 is not currently fit for purpose because the primary energy use underpinning the EPC bands is not consistent in each Member State and it does not provide a direct route to obtain a weighted average energy performance. In fact in some Member States EPCs are not even used. We would therefore not recommend aggregating the data for reporting using such a proxy. Instead we would recommend establishing bands of primary energy consumption which, although national calculation methods also vary by Member State, would allow for disclosure on the basis of a unit of measurement rather than a proxy. Moreover, the unit of measurement of primary energy use has a more widespread, standardised basis in the EU, having been defined as the common metric under the Energy Performance of Buildings Directive and in particular for the performance of nearly zero energy (NZEB) buildings. This unit of measurement is required to accompany building permits and property transactions in all Member States, thereby providing a commonly available data point to obtain a weighted average from.
That said, the exposure to NACE sectors can only provide a limited introduction to transition risk, namely to see potential hot spots. However, what ultimately matters for transition risk is whether the companies you are financing in those sectors are transitioning. NACE exposures will not be able to help in that regard, as it does not show exposures at the technology level. This is also why Template 4 is so important.
Building on this point, guidance should be given as to how to treat companies where there is a split of business activities or revenue across several NACE codes. Banks may make assumptions about how to make this split using different methods, so the EBA should clarify whether this shall be allowed and if so it will be important to provide definitive guidance in order to ensure comparability. At the same time we recognise from our experience that it is hard to impossible to determine a separation of loans going to the different activities of a company. We would recommend, as a minimum, to map exposures for the fossil fuel sector, as with divestment and diversification these activities are likely to span different NACE codes, covering both high emitting and lower emitting technologies.
Template 1 first requests disclosure of the gross carrying amount for a list of ‘exposures towards sectors that highly contribute to climate’ (rows 1-49) and then a disclosure is requested in columns i-k for a subtotal of these exposures that are ‘towards other carbon-intensive sectors’. We consider that this is unnecessarily confusing and that it would be clearer to simply present one list of carbon-intensive sectors that are a priority for disclosure based on their emissions and in accordance with the footnote **. We also question the need to include at this stage exposures to other sectors.
Disclosure on an institution’s scope 3 emissions
We agree that the scope of the emissions disclosure should be on the scope 3 emissions of a financial institution. For the purpose of the overall disclosure our understanding is that scope 3 relates to the financed emissions of the institution as defined in ISO 14064-1/2 and the Greenhouse Gas Protocol i.e. the weighted or unweighted CO2 emissions attributed to a counterparty or equity/bond position holdings. To make this definition more precise reference to scope 3 category 15 investments could be made.
In terms of the transitional period proposed and given the urgency of addressing the potential impacts of climate change we consider that 2024 would represent too great a delay in introducing the overall disclosure requirement. As a minimum initial disclosure using Templates 1-4 should commence in the 2022 reporting cycle. For example, the transitional timeframe is not appropriate for oil, gas and coal extraction operations because of their strategic importance to addressing climate change.
Applicability of scope 3 to underlying companies
In order to avoid confusion we also consider that greater clarity is also needed on which of the company-level scopes (1, 2, 3) need to be included when calculated the Scope 3 of the bank.
1. How financed emissions should be interpreted for fossil fuel producing companies reported using template 1,
2. The extent to which the scope of financed emissions shall extend to cover scope 3 upstream or downstream company activities i.e. what is referred to in the instructions as the ‘carbon footprint’ of a company’s activities.
First, for loans to fossil fuel producing companies, the disclosure should include exposure to actual production volumes of the fossil fuels. This is because the majority of the emissions relate to downstream use of the processed fuels supplied i.e. scope 3 at the company/activity level. However, the scope 3 emissions from burning these fuels can only ever be estimated based on their apportionment to end-markets, which is very difficult to do (see next paragraph), so instead the overall volume of primary (fossil) energy production should be disclosed as a proxy – as we propose in Template 4.
Second, for many sectors reporting on scope 3 emissions is still in its infancy and relies on the implementation of life cycle assessment (LCA) methodologies as well as being subject to varying levels of data quality. These methodologies are still in the process of being more widely applied for the purpose of corporate reporting, having originated as an academic tool. At present rules are not consistently available for each sector. If company scope 3 is to be considered at company/activity level then it may therefore be prudent to identify those sectors where:
• scope 3 is a ‘hot spot’ for significant upstream and downstream emissions,
• where consistent guidance on the sector rules to use can be provided, and
• where there is evidence of high quality, asset level data being available from life cycle inventory data providers.
For example, for the construction of new buildings LCA evidence shows that the scope 3 upstream emissions from manufacturing of construction products can account for upwards of 20-30% of life cycle GHG emissions. Moreover, the building sector is a good example of a sector which already has a standardised and widely implemented calculation and reporting framework as laid down in EN 15978 and EN 15804.
While understanding potential medium to long term exposure horizons to companies with high emissions could also provide useful information, exposure transition risk can potentially be minimised in the short term by ensuring a focus on the correct initial alignment of transitional investments over a 5-10 year time horizon. Those counterparties that have debts that mature within a 5 year timeframe should be cross-referenced with the alignment results obtained as input data for template 4. This would allow banks to determine the extent to which the economic activities of a counterparty or position held in a company may expose the institution to transition risks (misalignment) in the short term.
A specific focus could also be made on fossil fuel activities that spill into the longer maturity buckets through to 2040 and 2050, when the full extent of any potential economic impacts from climate change will have started to become apparent. It is particularly important to understand medium to long term exposures to these activities. Note that if oil producers are always only captured within the relevant NACE code for their existing operations then their diversification into other activities such as renewable electricity and fuel production would not be captured.
We would like to re-iterate the previous point made under question 5 in relation to the use of NACE codes. Guidance should be provided as to how to account for a split of exposures across several NACE sectors.
As noted earlier, while exposures to sectors, related greenhouse gas emissions, and maturity buckets can provide an initial assessment of where potential hotspots of risk in the balance sheet may lie, ultimately, transition risk needs to be measured based on the alignment of a financial institution’s exposures to the most climate critical sectors activities. Template 4 is therefore a critical step towards a better understanding of transition risk.
To assess transition risk there is the need to assess the underlying companies and develop the metrics to track transition at asset level. This is where Template 4 can play a crucial role. While we welcome the inclusion of this template, we do believe the template needs to be significantly improved as well as the accompanying guidance. We have the following comments:
The need to include forward-looking results of the alignment metrics
In our view, alignment metrics need to include a forward-looking component. Thus, we recommend that the template not only asks for the alignment metrics and deviation from the IEA’s SDS on t=0 but also on t=5, based on a static balance sheet. This last point is important as it means the results will be driven by whether the companies in the sectors that are financed are transitioning. Meaning that if bank A’s alignment improves from t=0 to t=5 while that of Bank B declines in the same period, this is exclusively due to the fact that bank A is exposed to companies that are transitioning better and faster and thus have lower transition risk. Moreover, providing alignment projections creates reference points against which future assessments of the institution can be benchmarked.
Regarding the different alignment metrics
Regarding the different alignment metrics proposed, we would make two points – the first relates to the importance of including a technology/fuel mix metric where possible (Note: these are alternatively referred to as technology share, fuel share, or capital stock indicators in the literature. For ease of reading we will simply refer to them as technology/fuel mix, even if different terms are used to describe the concept). The second relates to how fossil fuels are addressed (upstream gas and oil and coal mining).
Technology/fuel mix
Firstly, we strongly welcome the inclusion of a technology/fuel mix metric, although we recommend that its definition be more clearly defined. Regarding the relevance of this metric, it’s important to realize that the IEA scenarios can roughly be divided into two types of scenarios: scenarios with technology pathways and scenarios without technology stock pathways. A technology pathway means that as part of the scenario, the IEA explains what needs to happen to the production levels of specific technologies or fuels e.g. the required growth of low carbon technologies and decline of high carbon technologies. These scenarios will calculate how fast the production of electric cars and solar and wind power needs to increase and how fast the production of coal power and ICE cars need to decline in order to meet the climate goals. At any point in time in the scenario you can calculate the “technology or fuel mix”, e.g. what is the share of electric cars, hybrid and ICE in total car production in a region (or global), or the share of coal power, wind power, solar power, etc., or the amount of coal, gas and oil production. For sectors that do not have a technology pathway, the scenarios simply provide for a carbon budget and accompanying levels of production, with the idea being that as production of e.g. steel and cement continues to increase in the coming decades (due to economic and population growth for example), the emissions in that sector need to go down.
For sectors without a technology pathway it makes most sense to calculate alignment based on emission intensities. For sectors with technology pathways specified, it makes sense to also calculate exposures and alignment directly to these technologies/fuels. There are five main reasons:
1. Closer alignment with the scenario: This approach stays closer to what is given in scenarios and you can see what drives the actual alignment results. The scenarios provide for production levels in certain technologies / fuels and you can measure your alignment to them directly. An emission intensity metric requires additional modelling and calculations (i.e. it requires emission factors) to be able to calculate associated emissions. You will need to make assumptions about how much a European coal power plant or steel power plant emits in terms of CO2 vs a non-European one, and this inventively leads to more estimates, assumptions, and therefore more risks of errors.
2. Ease of obtaining information: it is easier to obtain information on the production of companies per these technologies (electric cars, renewable power) than it is to obtain emission factors/emission intensities.
3. Greater comparability: As it requires less assumptions/modelling, it is more comparable.
4. Link to stress-test work: A reference to capital stock pathways links more intuitively to the class of stress-test models currently under development and thus ensures data collection systems will more easily plug into those models in the future. In addition, capital stock indicators link more closely to economic production and sales references.
5. Link to long-term scenario compliance: While emission intensities are easier to report, capital stock indicators allow for a reflection on the low-carbon technology deployment, crucial to avoiding a ‘glass floor’ in emissions reductions as energy efficiency measures are exhausted.
For these reasons above, it is important to complement the emission intensity metric where possible to references of technology/fuel mix. We should note that this is eminently feasible given current data availability. In terms of its definition, it needs to be expressed in a way that shows the share of each technology / fuel within the sector that the bank is exposed to (instead of just a sum of high or low carbon technologies), again given the link to the sector-specific scenario pathways.
Fossil fuels
Fossil fuels (i.e. upstream gas and oil and coal mining) are a specific case in point which require a distinct approach to be adopted. It is important to look directly at the specific production plans of the companies that are financed for each resource (oil, gas, coal). Are the companies that are financed planning to decrease oil, gas and coal production in line with the scenarios? For this an additional metric called ‘volume trajectory’ is helpful. This would show the normalized production trajectory of financed companies versus a required production trajectory.
Note however that from a risk perspective when these fossil fuel companies try to align, they are likely to switch to another business model to remain profitable into the future. It makes sense to therefore develop additional fossil fuel company metrics that try to capture these developments. Note also that this is why the revenue split for these activities in the exposure templates 1 and 3 is so important, as this can show whether fossil fuel companies are diversified or not.
We see a number of relevant additional indicators that may be worth exploring given the prominence of the fossil fuel sector in the decarbonization effort – all of which are measurable given current data availability. These could take the form of:
• Risk metrics around costs (e.g. breakeven price of oil plays, % of plays above climate aligned breakeven price) as developed by Carbon Tracker Initiative and as already required as disclosure for fossil fuel companies themselves;
• Indicators relating to the IEA scenarios which directly relate to the scenario constraints (e.g. % of future production related to new developments, oil barrels produced related to as of yet undeveloped fields); or
• Financing indicators (e.g. financing splits in primary energy production across fossil fuels and new diversified energy related activities)
Need to establish and communicate on allocation and calculation rules
An important element that is missing from the template are allocation and calculation rules. Particularly for banks disclosing for the first time, specific calculation guidance and rules are needed. Note that alignment results always first need to be calculated on the company-level and then allocated to the portfolio to calculate portfolio results. The guidance and rules will need to answer the following questions and alongside each we have proposed an approach:
• How should banks allocate company-level alignment results (emission intensity or technology mix) to a financial portfolio?
We recommend a portfolio weighted approach as this reflects the capital allocation decision of the bank. A portfolio-weighted approach means that the company that represents the biggest share of a financial institution’s loans in that sector also has the biggest influence on the overall score of exposures to that sector. This is helpful from a risk perspective as the company which is attributable to the largest financial exposure drives the results.
• How should scenario targets be calculated?
In order to determine deviation from the IEA scenario, for each company being financed a scenario target must be calculated at the company level. We recommend a market share approach for each technology/fuel mix metric and a convergence approach for emission intensities. Note that for the technology/fuel mix targets, a differentiation needs to be made between companies with a business model currently based on high carbon existing technologies and those based already on low carbon alternative technologies e.g. a power company that only has coal power capacity should be expected to build out renewable power, but a power company that only has renewable cannot be expected to retire coal power capacity.
• How should the deviation (distance to target) from the IEA scenario be calculated?
A percentage may be difficult to interpret as the comparison is not being made relative to an existing starting point. This could instead be calculated as a ratio that represents the distance to target. So, for example, if a target emissions intensity in 2050 is 50 kg CO2/tonne of production and the current emissions intensity is 75 kg CO2/tonne of production then the distance to target ratio would be 1.5. It could also be considered to present a direct comparison between the current position and the IEA results for the scenario.
Further additional comments:
• We consider that guidance is needed on data quality and data sources that banks may use to obtain to these results. Added to that, banks will likely use different tools and methodology providers to get these results. This is not in itself a bad thing, but the EBA could provide guidelines for what key elements/boundaries of such tools should be in order to be eligible or suitable as the basis for making this disclosure. This also extends to guidance on how to express uncertainties in the data and whether uncertainty bands should be used in providing the indicators.
• The EBA needs to consider the regionality aspect of alignment. Alignment should be measured per sector based on the most appropriate regionality. Most of the sectors mentioned in the template are global sectors and when banks finance companies in these sectors, the companies tend to have physical assets (oil fields, steel factories) globally as well. For those, global scenarios work well. But consider for example the power sector: if a bank finances only European power companies with only power plants based in Europe, it makes more sense to apply the Europe power region scenario.
• While it is important that banks report their alignment on the same scenario, so as to ensure comparability, it could also be interesting for the supervisor to see under how many different 2 degrees or net-zero scenarios for each individual sector or technology the bank would be aligned. This could an optional additional reporting column that provides a sensitivity on the main scenario results disclosure. We recommend that banks are required to explicitly identify a reference scenario that they use where their own scenario deviates from the IEA scenario.
• In terms of the scope of the sectors we recommend clarifying the inclusion of the extraction and production of the fossil fuels oil, natural gas and coal. The need for clarification arises because there appears to be a mistake in rows 1 and 2, as D.35 relates to power generation, whilst scenario alignment analysis would also tend to focus on mining for coal (B.5) and upstream oil and natural gas extraction (B.6). These two should be mentioned as separate sectors. Transportation should be disaggregated to present NACE codes for light duty and heavy duty vehicles (C.29.1) and passenger air travel (H.51.1). It is not clear why concrete products and metal ore mining are included. We recommend selecting the NACE codes to precisely reflect the manufacturing activity, with the boundary initially drawn around the primary iron or steel works and integrated cement works.
• In terms of the tracking of changes in exposure over time relative to the baseline year, it may be necessary to consider establishing rules for rebaselining. This would be to reflect the significant change that can occur over time in portfolio and banking book compositions, as well as possible future changes in the disclosure rules. Consider for example that the forward looking alignment targets of a bank’s portfolio do not come directly from the scenarios but depend on the specific companies it finances (bear in mind that scenario targets should be calculated on the company level using either a market share or convergence approach). If the composition of the balance sheet changes (i.e. different companies are being financed), then the target should/would also change. If so, the target should be re-calculated. The Greenhouse Gas protocol (Greenhouse Gas protocol, Corporate Value Chain (Scope 3) Accounting and Reporting Standard) currently provides a useful reference point for introducing rebaselining rules, albeit it at company level. The rebaselining rules would need to establish thresholds or criteria for triggering recalculations, in particular related to any significant change in the underlying assets, exposures, emissions scope boundaries, or any other relevant factors. This question is likely to also be relevant for other templates.
• While the template mentions gross carrying amount the instructions mention the use of ‘fair value’. We recommend against using ‘fair value’ as this will lead to significant changes in the alignment results caused only by changes in the market value of the underlying investment. As such, the gross carrying amount is the better value. Note however that currently, the gross carrying amount includes both loans, bonds and equities. This can complicate the alignment calculations, as it’s our understanding that bonds and equities would be on market value. It is important to not mix results for equities and bonds that are on market value and loans that are on book value. Thus the results should be shown separately for loans and for equities/bonds.
• high emitting sectors,
• the transition risk associated with specific assets, and
• the credit default risk based on specific future operating factors, such as the write down of reserves or a progressive loss of a companies’ revenue base.
The disclosure should be designed to distinguish cases where a high emitter is making credible, verified efforts to align with a decarbonisation pathway (e.g. by substituting its fossil fuel primary energy production with renewable primary energy production). This is also where the alignment metrics from Template 4 are helpful. Assessment of the exposure of banks to credit risk should be done on a case-by-case basis, with stress testing used to determine the extent of possible exposure to losses in the future under specific economic scenarios and within specific time frames.
While the breakdown by NACE classification offers some understanding of the distribution of physical risk, a breakdown by more subsectors would enable to better identify potential parts of a portfolio which carry high risk, as vulnerability towards different hazards differs across subsectors.
What is missing, however, is a differentiation of the exposure according to different time horizons and scenarios (RCPs, SSPs), if these have not been specified in advance. If the exposure is not reported along such parameters, the problem of inconsistencies of the measured exposure between banking books arises, resulting in limited comparability. This is exacerbated by the fact that the risks can be assessed in different ways and that there are many data sources and models. Compiling a standard framework for measuring physical risk would improve comparability and could serve as an orientation for banks.
Overall, we would like to emphasise that there is a great deal of uncertainty involved in measuring physical risks, so extrapolating down to a final exposure could be hugely misleading and has the potential to both over- and underestimate the actual exposure. The probability of the reported exposure is unclear and should be specified where possible. In this context, estimating an exposure range could address this problem.
As per our response to Q1, we consider that Template 4 will need to be complemented with more detailed guidance in order to support institutions in preparing alignment reporting. Linked to this guidance we also recommend, for the purpose of transparency and consistency, a separate disclosure on the tools used as well as some of the key methodological choices and assumptions made.
Question 1: Are the instructions, tables and templates clear to the respondents?
We consider that Templates 1-5 require further supporting instructions and guidance in order to define the terminology and data points that shall be reported on. In addition, for several templates - particularly Template 4 - the calculation method and allocation rules to be used are not apparent and would need to be provided. Where references are made to legislation, the requirements or exclusions referred to shall be reproduced in the instructions, to avoid respondents having to look them up.In relation to Template 3, the units of measurement for energy and for CO2 emissions need to be specified. To do this we recommend that primary energy is used because it is both comprehensive, encompassing the scope 1 and 2 emissions of a building, and is already established as the unit of measurement for building energy requirements at European level. Moreover, for both primary energy and CO2 emissions the units should be normalised to m2 of floor area to ensure comparability. Lastly, we consider that instructions are needed as to how the performance of each individual asset should be weighted in order to derive the figures for reporting. We would recommend considering a weighting based on the value of outstanding loans against each property, sometimes referred to as a portfolio weighting approach.
While we consider that Template 4 represents an important step in seeking to assess transition risk, there are a number of weaknesses that require addressing in order to make it operational for financial institutions and for meaningful disclosure. Template 4 will require more detailed guidance to support financial institutions in preparing these alignment disclosures. This is required in order to ensure consistency, with guidance needed on the calculation and allocation methods, scope of sectors, eligible data sources and tools. We have provided more details of how we would see this working under our response to Question 6.
Question 2: Do the respondents identify any discrepancies between these tables, templates and instructions and the disclosure requirements set out in the underlying regulation?
The requirement for disclosure set out in Article 449a of the amending Regulation (EU) 2019/876 makes a simple reference to physical climate risk and transition risk (as referred to in the report referred to in Article 98(8) of Directive 2013/36) so, as such, we do not see any major discrepancies.Question 3: Do the respondents agree that the new draft ITS fits the purpose of the underlying regulation?
Draft Templates 1-5 partly fulfil the purpose in that they provide an initial basis for understanding from a credit risk perspective in which sectors there is the potential for exposure.Draft Templates 2 and 4 provide a useful starting point for both disclosure of the time horizon for exposure and the misalignment of economic activities with sectoral decarbonisation pathways for climate change mitigation. These templates do not however fully fulfil the purpose of determining the possible extent of transition risk. This would have to be done by more comprehensively applying tools such as climate change scenario alignment and stress testing across the sectors disclosed. Please see our response to Question 6 for further information on Template 4.
Draft Template 3 is not currently fit for purpose because the primary energy use underpinning the EPC bands is not consistent in each Member State and it does not provide a direct route to obtain a weighted average energy performance. In fact in some Member States EPCs are not even used. We would therefore not recommend aggregating the data for reporting using such a proxy. Instead we would recommend establishing bands of primary energy consumption which, although national calculation methods also vary by Member State, would allow for disclosure on the basis of a unit of measurement rather than a proxy. Moreover, the unit of measurement of primary energy use has a more widespread, standardised basis in the EU, having been defined as the common metric under the Energy Performance of Buildings Directive and in particular for the performance of nearly zero energy (NZEB) buildings. This unit of measurement is required to accompany building permits and property transactions in all Member States, thereby providing a commonly available data point to obtain a weighted average from.
Question 4: Do the respondents agree that the tables with qualitative information proposed capture properly the information that institutions should provide?
NAQuestion 5: Regarding template 1 – ‘Banking book - Climate change transition risk: Quality of exposures by sector’, do the respondents agree with the proposals in terms of sector and subsector classification included in the rows of the template and the indentification of the most exposed sectors in columns f to k and p to u?
We support the use of a consistent economic activity classification system such as NACE. We would also suggest to provide sector crosswalks together with the guidance for financial institutions that use multiple sector classification systems to ease application where data systems may not be complete on NACE sectors.That said, the exposure to NACE sectors can only provide a limited introduction to transition risk, namely to see potential hot spots. However, what ultimately matters for transition risk is whether the companies you are financing in those sectors are transitioning. NACE exposures will not be able to help in that regard, as it does not show exposures at the technology level. This is also why Template 4 is so important.
Building on this point, guidance should be given as to how to treat companies where there is a split of business activities or revenue across several NACE codes. Banks may make assumptions about how to make this split using different methods, so the EBA should clarify whether this shall be allowed and if so it will be important to provide definitive guidance in order to ensure comparability. At the same time we recognise from our experience that it is hard to impossible to determine a separation of loans going to the different activities of a company. We would recommend, as a minimum, to map exposures for the fossil fuel sector, as with divestment and diversification these activities are likely to span different NACE codes, covering both high emitting and lower emitting technologies.
Template 1 first requests disclosure of the gross carrying amount for a list of ‘exposures towards sectors that highly contribute to climate’ (rows 1-49) and then a disclosure is requested in columns i-k for a subtotal of these exposures that are ‘towards other carbon-intensive sectors’. We consider that this is unnecessarily confusing and that it would be clearer to simply present one list of carbon-intensive sectors that are a priority for disclosure based on their emissions and in accordance with the footnote **. We also question the need to include at this stage exposures to other sectors.
Question 6: Do the respondents agree with the proposal included in templates 1 and 3 to disclose information on scope 3 emissions and with the transitional period proposed?
We have split our response to this question into two parts. The first part addresses the question of disclosure on the scope 3 emissions of financial institutions and the transitional period proposed. The second part addresses the need for additional clarity on the applicability of scope 3 to underlying assets i.e. at company and economic activity level.Disclosure on an institution’s scope 3 emissions
We agree that the scope of the emissions disclosure should be on the scope 3 emissions of a financial institution. For the purpose of the overall disclosure our understanding is that scope 3 relates to the financed emissions of the institution as defined in ISO 14064-1/2 and the Greenhouse Gas Protocol i.e. the weighted or unweighted CO2 emissions attributed to a counterparty or equity/bond position holdings. To make this definition more precise reference to scope 3 category 15 investments could be made.
In terms of the transitional period proposed and given the urgency of addressing the potential impacts of climate change we consider that 2024 would represent too great a delay in introducing the overall disclosure requirement. As a minimum initial disclosure using Templates 1-4 should commence in the 2022 reporting cycle. For example, the transitional timeframe is not appropriate for oil, gas and coal extraction operations because of their strategic importance to addressing climate change.
Applicability of scope 3 to underlying companies
In order to avoid confusion we also consider that greater clarity is also needed on which of the company-level scopes (1, 2, 3) need to be included when calculated the Scope 3 of the bank.
1. How financed emissions should be interpreted for fossil fuel producing companies reported using template 1,
2. The extent to which the scope of financed emissions shall extend to cover scope 3 upstream or downstream company activities i.e. what is referred to in the instructions as the ‘carbon footprint’ of a company’s activities.
First, for loans to fossil fuel producing companies, the disclosure should include exposure to actual production volumes of the fossil fuels. This is because the majority of the emissions relate to downstream use of the processed fuels supplied i.e. scope 3 at the company/activity level. However, the scope 3 emissions from burning these fuels can only ever be estimated based on their apportionment to end-markets, which is very difficult to do (see next paragraph), so instead the overall volume of primary (fossil) energy production should be disclosed as a proxy – as we propose in Template 4.
Second, for many sectors reporting on scope 3 emissions is still in its infancy and relies on the implementation of life cycle assessment (LCA) methodologies as well as being subject to varying levels of data quality. These methodologies are still in the process of being more widely applied for the purpose of corporate reporting, having originated as an academic tool. At present rules are not consistently available for each sector. If company scope 3 is to be considered at company/activity level then it may therefore be prudent to identify those sectors where:
• scope 3 is a ‘hot spot’ for significant upstream and downstream emissions,
• where consistent guidance on the sector rules to use can be provided, and
• where there is evidence of high quality, asset level data being available from life cycle inventory data providers.
For example, for the construction of new buildings LCA evidence shows that the scope 3 upstream emissions from manufacturing of construction products can account for upwards of 20-30% of life cycle GHG emissions. Moreover, the building sector is a good example of a sector which already has a standardised and widely implemented calculation and reporting framework as laid down in EN 15978 and EN 15804.
Question 7: Do respondents agree that information in terms of maturity buckets by sector proposed in template 2 is relevant to understand the time horizon of when the institution maybe more exposed to climate change transition risk?
We consider that the proposed disclosures by maturity bucket are relevant and provides a useful starting point to prompt financial institutions to look at the time horizons for potential exposure across the scope of sectors and economic activities. However, a missing element in seeking to understand exposure to transition risk is the extent to which the carrying amount in each bucket may be misaligned according to a selected decarbonisation trajectory and as used to disclose in template 4. This is particularly important for the continued financing beyond 2025-30 of production volumes associated with oil, gas and coal extraction. Ideally, while not yet easily feasible now, it would be great to show the different metric buckets linked to alignment results, and showing the maturity of aligned and misaligned exposures.While understanding potential medium to long term exposure horizons to companies with high emissions could also provide useful information, exposure transition risk can potentially be minimised in the short term by ensuring a focus on the correct initial alignment of transitional investments over a 5-10 year time horizon. Those counterparties that have debts that mature within a 5 year timeframe should be cross-referenced with the alignment results obtained as input data for template 4. This would allow banks to determine the extent to which the economic activities of a counterparty or position held in a company may expose the institution to transition risks (misalignment) in the short term.
A specific focus could also be made on fossil fuel activities that spill into the longer maturity buckets through to 2040 and 2050, when the full extent of any potential economic impacts from climate change will have started to become apparent. It is particularly important to understand medium to long term exposures to these activities. Note that if oil producers are always only captured within the relevant NACE code for their existing operations then their diversification into other activities such as renewable electricity and fuel production would not be captured.
We would like to re-iterate the previous point made under question 5 in relation to the use of NACE codes. Guidance should be provided as to how to account for a split of exposures across several NACE sectors.
Question 8: Do respondents agree that information in terms of alignment metrics and relative scope 3 emissions proposed in template 4 is relevant to understand and compare the transition risk phased by institutions? What are the respondents’ considerations with regard to the alignment metrics proposed and the sectors that should be covered by this disclosure? Do respondents agree with the transitional period proposed?
We strongly welcome the inclusion of an alignment metrics template and consider it an important tool to understand whether the underlying companies being financed are transitioning. Given the current activity in the sector around the use of scenario alignment tools we consider that disclosure using the template is readily achievable using existing tools and methods. For example, the PACTA scenario alignment tool developed by 2 Degrees Investing Initiative has now been used by over 60 banks as well as by supervisors and central banks to assess their regulated entities. However, in order to ensure consistency and comparability it is important to lay down more precise rules and guidelines for disclosure.As noted earlier, while exposures to sectors, related greenhouse gas emissions, and maturity buckets can provide an initial assessment of where potential hotspots of risk in the balance sheet may lie, ultimately, transition risk needs to be measured based on the alignment of a financial institution’s exposures to the most climate critical sectors activities. Template 4 is therefore a critical step towards a better understanding of transition risk.
To assess transition risk there is the need to assess the underlying companies and develop the metrics to track transition at asset level. This is where Template 4 can play a crucial role. While we welcome the inclusion of this template, we do believe the template needs to be significantly improved as well as the accompanying guidance. We have the following comments:
The need to include forward-looking results of the alignment metrics
In our view, alignment metrics need to include a forward-looking component. Thus, we recommend that the template not only asks for the alignment metrics and deviation from the IEA’s SDS on t=0 but also on t=5, based on a static balance sheet. This last point is important as it means the results will be driven by whether the companies in the sectors that are financed are transitioning. Meaning that if bank A’s alignment improves from t=0 to t=5 while that of Bank B declines in the same period, this is exclusively due to the fact that bank A is exposed to companies that are transitioning better and faster and thus have lower transition risk. Moreover, providing alignment projections creates reference points against which future assessments of the institution can be benchmarked.
Regarding the different alignment metrics
Regarding the different alignment metrics proposed, we would make two points – the first relates to the importance of including a technology/fuel mix metric where possible (Note: these are alternatively referred to as technology share, fuel share, or capital stock indicators in the literature. For ease of reading we will simply refer to them as technology/fuel mix, even if different terms are used to describe the concept). The second relates to how fossil fuels are addressed (upstream gas and oil and coal mining).
Technology/fuel mix
Firstly, we strongly welcome the inclusion of a technology/fuel mix metric, although we recommend that its definition be more clearly defined. Regarding the relevance of this metric, it’s important to realize that the IEA scenarios can roughly be divided into two types of scenarios: scenarios with technology pathways and scenarios without technology stock pathways. A technology pathway means that as part of the scenario, the IEA explains what needs to happen to the production levels of specific technologies or fuels e.g. the required growth of low carbon technologies and decline of high carbon technologies. These scenarios will calculate how fast the production of electric cars and solar and wind power needs to increase and how fast the production of coal power and ICE cars need to decline in order to meet the climate goals. At any point in time in the scenario you can calculate the “technology or fuel mix”, e.g. what is the share of electric cars, hybrid and ICE in total car production in a region (or global), or the share of coal power, wind power, solar power, etc., or the amount of coal, gas and oil production. For sectors that do not have a technology pathway, the scenarios simply provide for a carbon budget and accompanying levels of production, with the idea being that as production of e.g. steel and cement continues to increase in the coming decades (due to economic and population growth for example), the emissions in that sector need to go down.
For sectors without a technology pathway it makes most sense to calculate alignment based on emission intensities. For sectors with technology pathways specified, it makes sense to also calculate exposures and alignment directly to these technologies/fuels. There are five main reasons:
1. Closer alignment with the scenario: This approach stays closer to what is given in scenarios and you can see what drives the actual alignment results. The scenarios provide for production levels in certain technologies / fuels and you can measure your alignment to them directly. An emission intensity metric requires additional modelling and calculations (i.e. it requires emission factors) to be able to calculate associated emissions. You will need to make assumptions about how much a European coal power plant or steel power plant emits in terms of CO2 vs a non-European one, and this inventively leads to more estimates, assumptions, and therefore more risks of errors.
2. Ease of obtaining information: it is easier to obtain information on the production of companies per these technologies (electric cars, renewable power) than it is to obtain emission factors/emission intensities.
3. Greater comparability: As it requires less assumptions/modelling, it is more comparable.
4. Link to stress-test work: A reference to capital stock pathways links more intuitively to the class of stress-test models currently under development and thus ensures data collection systems will more easily plug into those models in the future. In addition, capital stock indicators link more closely to economic production and sales references.
5. Link to long-term scenario compliance: While emission intensities are easier to report, capital stock indicators allow for a reflection on the low-carbon technology deployment, crucial to avoiding a ‘glass floor’ in emissions reductions as energy efficiency measures are exhausted.
For these reasons above, it is important to complement the emission intensity metric where possible to references of technology/fuel mix. We should note that this is eminently feasible given current data availability. In terms of its definition, it needs to be expressed in a way that shows the share of each technology / fuel within the sector that the bank is exposed to (instead of just a sum of high or low carbon technologies), again given the link to the sector-specific scenario pathways.
Fossil fuels
Fossil fuels (i.e. upstream gas and oil and coal mining) are a specific case in point which require a distinct approach to be adopted. It is important to look directly at the specific production plans of the companies that are financed for each resource (oil, gas, coal). Are the companies that are financed planning to decrease oil, gas and coal production in line with the scenarios? For this an additional metric called ‘volume trajectory’ is helpful. This would show the normalized production trajectory of financed companies versus a required production trajectory.
Note however that from a risk perspective when these fossil fuel companies try to align, they are likely to switch to another business model to remain profitable into the future. It makes sense to therefore develop additional fossil fuel company metrics that try to capture these developments. Note also that this is why the revenue split for these activities in the exposure templates 1 and 3 is so important, as this can show whether fossil fuel companies are diversified or not.
We see a number of relevant additional indicators that may be worth exploring given the prominence of the fossil fuel sector in the decarbonization effort – all of which are measurable given current data availability. These could take the form of:
• Risk metrics around costs (e.g. breakeven price of oil plays, % of plays above climate aligned breakeven price) as developed by Carbon Tracker Initiative and as already required as disclosure for fossil fuel companies themselves;
• Indicators relating to the IEA scenarios which directly relate to the scenario constraints (e.g. % of future production related to new developments, oil barrels produced related to as of yet undeveloped fields); or
• Financing indicators (e.g. financing splits in primary energy production across fossil fuels and new diversified energy related activities)
Need to establish and communicate on allocation and calculation rules
An important element that is missing from the template are allocation and calculation rules. Particularly for banks disclosing for the first time, specific calculation guidance and rules are needed. Note that alignment results always first need to be calculated on the company-level and then allocated to the portfolio to calculate portfolio results. The guidance and rules will need to answer the following questions and alongside each we have proposed an approach:
• How should banks allocate company-level alignment results (emission intensity or technology mix) to a financial portfolio?
We recommend a portfolio weighted approach as this reflects the capital allocation decision of the bank. A portfolio-weighted approach means that the company that represents the biggest share of a financial institution’s loans in that sector also has the biggest influence on the overall score of exposures to that sector. This is helpful from a risk perspective as the company which is attributable to the largest financial exposure drives the results.
• How should scenario targets be calculated?
In order to determine deviation from the IEA scenario, for each company being financed a scenario target must be calculated at the company level. We recommend a market share approach for each technology/fuel mix metric and a convergence approach for emission intensities. Note that for the technology/fuel mix targets, a differentiation needs to be made between companies with a business model currently based on high carbon existing technologies and those based already on low carbon alternative technologies e.g. a power company that only has coal power capacity should be expected to build out renewable power, but a power company that only has renewable cannot be expected to retire coal power capacity.
• How should the deviation (distance to target) from the IEA scenario be calculated?
A percentage may be difficult to interpret as the comparison is not being made relative to an existing starting point. This could instead be calculated as a ratio that represents the distance to target. So, for example, if a target emissions intensity in 2050 is 50 kg CO2/tonne of production and the current emissions intensity is 75 kg CO2/tonne of production then the distance to target ratio would be 1.5. It could also be considered to present a direct comparison between the current position and the IEA results for the scenario.
Further additional comments:
• We consider that guidance is needed on data quality and data sources that banks may use to obtain to these results. Added to that, banks will likely use different tools and methodology providers to get these results. This is not in itself a bad thing, but the EBA could provide guidelines for what key elements/boundaries of such tools should be in order to be eligible or suitable as the basis for making this disclosure. This also extends to guidance on how to express uncertainties in the data and whether uncertainty bands should be used in providing the indicators.
• The EBA needs to consider the regionality aspect of alignment. Alignment should be measured per sector based on the most appropriate regionality. Most of the sectors mentioned in the template are global sectors and when banks finance companies in these sectors, the companies tend to have physical assets (oil fields, steel factories) globally as well. For those, global scenarios work well. But consider for example the power sector: if a bank finances only European power companies with only power plants based in Europe, it makes more sense to apply the Europe power region scenario.
• While it is important that banks report their alignment on the same scenario, so as to ensure comparability, it could also be interesting for the supervisor to see under how many different 2 degrees or net-zero scenarios for each individual sector or technology the bank would be aligned. This could an optional additional reporting column that provides a sensitivity on the main scenario results disclosure. We recommend that banks are required to explicitly identify a reference scenario that they use where their own scenario deviates from the IEA scenario.
• In terms of the scope of the sectors we recommend clarifying the inclusion of the extraction and production of the fossil fuels oil, natural gas and coal. The need for clarification arises because there appears to be a mistake in rows 1 and 2, as D.35 relates to power generation, whilst scenario alignment analysis would also tend to focus on mining for coal (B.5) and upstream oil and natural gas extraction (B.6). These two should be mentioned as separate sectors. Transportation should be disaggregated to present NACE codes for light duty and heavy duty vehicles (C.29.1) and passenger air travel (H.51.1). It is not clear why concrete products and metal ore mining are included. We recommend selecting the NACE codes to precisely reflect the manufacturing activity, with the boundary initially drawn around the primary iron or steel works and integrated cement works.
• In terms of the tracking of changes in exposure over time relative to the baseline year, it may be necessary to consider establishing rules for rebaselining. This would be to reflect the significant change that can occur over time in portfolio and banking book compositions, as well as possible future changes in the disclosure rules. Consider for example that the forward looking alignment targets of a bank’s portfolio do not come directly from the scenarios but depend on the specific companies it finances (bear in mind that scenario targets should be calculated on the company level using either a market share or convergence approach). If the composition of the balance sheet changes (i.e. different companies are being financed), then the target should/would also change. If so, the target should be re-calculated. The Greenhouse Gas protocol (Greenhouse Gas protocol, Corporate Value Chain (Scope 3) Accounting and Reporting Standard) currently provides a useful reference point for introducing rebaselining rules, albeit it at company level. The rebaselining rules would need to establish thresholds or criteria for triggering recalculations, in particular related to any significant change in the underlying assets, exposures, emissions scope boundaries, or any other relevant factors. This question is likely to also be relevant for other templates.
• While the template mentions gross carrying amount the instructions mention the use of ‘fair value’. We recommend against using ‘fair value’ as this will lead to significant changes in the alignment results caused only by changes in the market value of the underlying investment. As such, the gross carrying amount is the better value. Note however that currently, the gross carrying amount includes both loans, bonds and equities. This can complicate the alignment calculations, as it’s our understanding that bonds and equities would be on market value. It is important to not mix results for equities and bonds that are on market value and loans that are on book value. Thus the results should be shown separately for loans and for equities/bonds.
Question 9: Regarding the same template 4, what are the respondents’ considerations with respect to the choice of the 2 degrees reference scenario, would respondents opt for a different scenario?
If consistent and comparable reporting is the objective, then it is important that the scenario and subsequent revision versions are clearly defined and fixed for all institutions. Our observation is that respondents are tending towards a choice of beyond 2degrees (B2DS) or ‘net zero’ scenarios. In general, however, we would propose requesting disclosure on results for both 2 degree and 1.5 degree decarbonisation pathways. The IEA’s Sustainable Development (SDS) and Below 2 Degrees (B2DS) scenarios provided as part of the World Energy Outlook and Energy Technology Perspectives 2020 can be useful here, but so can the 1.5 degree and 2 degree scenarios from the Joint Research Centre’s Global Energy Outlook 2020, which has the benefit of being created by the EU and where EU legislation can create a requirement to develop updated scenarios annually.Question 10: Do respondents agree that information proposed in template 5 is relevant to understand the level of climate change transition risk and that information on exposures towards the most polluting companies is a good complement to the sectorial information included in other templates? Specific feedback is sought on possible alternative formats for the presentation of the information required in template 5. In particular, the EBA seeks feedback on whether aggregate information on exposures towards th
The aim of this template should be more carefully considered as it could have the effect of incentivising divestment instead of disclosing on transition. We consider that the definition of the most polluting companies should be more tightly defined in relation to:• high emitting sectors,
• the transition risk associated with specific assets, and
• the credit default risk based on specific future operating factors, such as the write down of reserves or a progressive loss of a companies’ revenue base.
The disclosure should be designed to distinguish cases where a high emitter is making credible, verified efforts to align with a decarbonisation pathway (e.g. by substituting its fossil fuel primary energy production with renewable primary energy production). This is also where the alignment metrics from Template 4 are helpful. Assessment of the exposure of banks to credit risk should be done on a case-by-case basis, with stress testing used to determine the extent of possible exposure to losses in the future under specific economic scenarios and within specific time frames.
Question 11: What are respondents view on the way template 6 reflects how the trading book of institutions may be impacted by climate change transition risk? Do respondents agree that the threshold proposed to determine which institutions have to disclose this template is the appropriate threshold? Feedback on whether there are alternative ways to present information on the trading book that may allow for a better understanding of how climate change transition risk may impact the trading portfolio.
NAQuestion 12: Do respondents agree that the information included in template 7 is appropriate to understand how and to what extent the institution may be exposed to climate change physical risk and that the differentiation between a simplified and an extended template is necessary in the short/medium term?
The simplified version is a starting point to understand exposure to physical risk. However, the simplified version should always be a summary of the extended version, as physical risks can only really be reported as a whole if one sees it as the sum of the individual hazards, both for chronic and acute risks. The differentiation between simplified and extended is therefore necessary, as the results in the simplified template should be based on the extended template.While the breakdown by NACE classification offers some understanding of the distribution of physical risk, a breakdown by more subsectors would enable to better identify potential parts of a portfolio which carry high risk, as vulnerability towards different hazards differs across subsectors.
What is missing, however, is a differentiation of the exposure according to different time horizons and scenarios (RCPs, SSPs), if these have not been specified in advance. If the exposure is not reported along such parameters, the problem of inconsistencies of the measured exposure between banking books arises, resulting in limited comparability. This is exacerbated by the fact that the risks can be assessed in different ways and that there are many data sources and models. Compiling a standard framework for measuring physical risk would improve comparability and could serve as an orientation for banks.
Overall, we would like to emphasise that there is a great deal of uncertainty involved in measuring physical risks, so extrapolating down to a final exposure could be hugely misleading and has the potential to both over- and underestimate the actual exposure. The probability of the reported exposure is unclear and should be specified where possible. In this context, estimating an exposure range could address this problem.
Question 13: Regarding template 7, specific feedback is asked regarding the methodologies and data sources that institutions may use to identify the relevant geographies. Feedback is also required on the content and disclosures proposed in the extended version of the template and on the transitional period proposed.
EBA could greatly benefit from requiring banks to disclose more granular information on the PDs by sector in the proposed template, without adding any complexity to the document. More specifically, banks should be required to disclose the average weighted PD (in %) not only on the sectoral level of performing loans but further on: i) the subset of exposure-prone to impact from chronic climate change events; and ii) the subset of exposures prone to impact from acute climate change events. This way, EBA has more granular information that gives more flexibility in future analysis. As banks have to identify the subset of firms that are at risk of such physical risk and calculate the share to the overall sectorial exposure anyway, banks should have no difficulty in also providing the average weighted PDs of the two subsets of exposures that are prone to acute and chronic physical risk. Based on such information, EBA could compare average PDs across the exposure subsets and identify whether there is, on average, a higher PD average for firms in sectors that are exposed to physical risk. This could give some indication of whether banks are currently incorporating any climate considerations into their internal credit risk framework.Question 14: Regarding templates 8 and 9, do respondents consider that this template should be enriched including information not only on assets aligned with the taxonomy but also in the interest income generated by those assets? Do respondents agree with the timeline proposed and transitional period proposed for the disclosure of these templates?
NAQuestion 15: Specific feedback is required from respondents on the way template 10 is defined, and on whether there is additional information that should be added. Feedback is sought on alternative disclosure formats that may contribute to a more standardised and comparable disclosure.
NAQuestion 16: Finally, respondents feedback on whether the draft ITS should include a specific template on forward looking information and scenario analysis, beyond the qualitative information currently captured in the tables and templates under consultation and the information required in template 4.
We consider forward looking information and scenario analysis an essential and currently underspecified component of the draft ITS. They play an important role in providing a more complete picture of potential exposure to transition risk. In this respect we propose expanding Template 4 to include additional timeframes looking forward a minimum of 5 years, based on analysis by the institution (see also our response to the questions on Template 4), and potentially also disclosing exposure to clients that have established and validated targets to 2030 and beyond.As per our response to Q1, we consider that Template 4 will need to be complemented with more detailed guidance in order to support institutions in preparing alignment reporting. Linked to this guidance we also recommend, for the purpose of transparency and consistency, a separate disclosure on the tools used as well as some of the key methodological choices and assumptions made.