Deutsche Bank

A comprehensive template is preferred. Providing a detailed breakdown by exposure class in EU CR5-B and EU CR6 would result in a disproportionate additional burden and little benefit to users.
It would be possible to breakdown the value adjustments and provisions, however, the usefulness of such disclosure is questionable. This is because most provisioning amounts are expected to be clustered around the lower end of the rating scale and defaulted exposures. Providing a breakdown in this manner would also make it harder to compare figures across institutions and would require additional qualitative information in order for the information to be of any use to the user.
We see limited use for information on the sources of counterparty credit risk (broken down by transaction type) for exposures measured under the Internal Model Method (IMM).
Currently, we disclose market risk own funds requirements by risk type for the standardised approach but not for the internal model approach. The revised BCBS Pillar 3 framework maintains this requirement only for the standardised approach, which makes sense. However, we provide the market risk own funds requirement broken down by the relevant internal model approach, such as Value at Risk (VaR) or Incremental Risk Charge (IRC).

While there would be no impediments to providing a break down as outlined by the Guidelines, it would be misleading to provide market risk own funds requirements by risk type for internal model approaches. This had been explained previously in our 2015 Pillar 3 Report.

For each business unit, we calculate a separate VaR for each risk type, for example, by interest rate risk, credit spread risk, equity risk, foreign exchange risk and commodity risk. Key risk factors include swap/government curves, index and issuer-specific credit curves, funding spreads, single equity and index prices, foreign exchange rates, commodity prices as well as their implied volatilities. Simply adding the VaR figures of the individual risk types to arrive at an aggregate VaR would imply that the losses in all risk types occur simultaneously and are driven by concurrent extreme adverse movements of underlying risk drivers. As proposed, such a disclosure would ignore diversification effects, which reflects the fact that the total VaR on a given day will be lower than the sum of the VaR relating to the individual risk types.
When reviewing the template design for market risk disclosures, the overall direction of prudential regulatory developments should be taken into account. As the VaR disclosures are likely to be made defunct by the implementation of Fundamental Review of the Trading Book (FRTB), it would make sense, especially from a resource perspective, to consider a template update compatible with the implementation of FRTB.
While the development of key risk metric template(s) that would apply to all institutions is a sensible objective, we believe the EU template(s) should be consulted on at a later date once the equivalent template is finalised by the BCBS. This would help ensure this requirement is implemented consistently across jurisdictions.
We currently disclose a financial data supplement on an annual and quarterly basis in an editable format. This disclosure is made publicly available in excel format to provide users with a detailed financial summary of the bank at the consolidated and segmental levels over a historical period.

However, while making quantitative disclosures available in an editable format is feasible, it would be difficult to do for each and every template. This is due to the sheer magnitude of additional templates required, the provided implementation timeframe, and the governance needed over disclosures in an editable format. It would be possible, but at a cost that would outweigh its usefuleness.

It is essential, moreover, for the user to be able to read and thoroughly understand clear definitions in order to understand the differences of the underlying data. For example, Template EU CR6: Internal Ratings-Based Approach (IRB) – Credit risk exposures by exposure class and PD range features Columns (a) and (b) that are based on accounting carrying values and columns (c) through (l) that are based on regulatory values - either determined by institutions or as specified in the Guidelines. Our concern is that without additional qualitative background, user groups could be misled if their reading assumes the figures are determined by the same definition. Furthermore, the added governance required would be in addition to the increase in resources needed to comply with the requirements proposed in the Guidelines.

Instead of making each quantitative disclosure available in editable format, we recommend only providing quantitative disclosure in an editable format for templates that are considered high usage and which users would find most useful.
Deutsche Bank