Response to consultation on ITS amending Commission Implementing Regulation EU 2016-2070 on Benchmarking
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Creating a simplified rating split model on template C105 as proposed would not result in losing explanatory information on the variability of benchmarking parameters. Where model calibration and risk parameters are significantly different across countries, then country specific models would be used and with inclusion of the internal model ID and model name fields in the template the relevant splits providing explanatory power would be maintained.
We would find it helpful if the exposure class field was included in template C105.4 even if the model name field already indicates the exposure class.
We do not expect that any data points on C105.04 would involve materially incremental IT costs or other burden.
We would welcome clarification whether templates C200 and C300 need to be calculated and populated for rating/country splits for which there is not any exposure in the current year but where there has been within the previous 5 years.
We also agree that the combination of sector and type split of the exposures are sensible components to explain the variability of risk parameters.
Of the options presented in the consultation paper, we would prefer Option 1, the current approach in the CP, which would not require a rating split for specialised lending under the slotting approach. We are not sure whether the additional split proposed in Option 2 would enhance the additional explanatory power of the exercise.
We assume this to be the case for most other institutions. It is likely that the additional split of data would bring about further validation and data issues increasing the reporting burden.
We do not consider the current split using only NACE code F to be sufficient. The current (construction only) breakdown does not represent a significant part of the exposure class. In last year’s exercise, construction firms formed only a small part of the total exposures for non-SME corporates.
We agree that choosing a subset list at the sector level as proposed will reduce the burden of data collection.
As the low (<50%) LTV bands have relatively low RWAs, combining them and adding more granularity for higher LTVs that have a higher proportion of the RWAs may provide additional explanation for RWA variability.
The EBA may want to consider aligning the LTV buckets to the one proposed in the new Basel III framework.
Do you agree that the combined split of rating and country in template C103 can generally be replaced by a simpler rating split per model (i.e., rating distribution) in template 105, which will cover all models in the scope of the benchmarking exercise (HDP and LDP) without losing explanatory information on the variability of benchmarking parameters? Is there any data point collected in the new template 105.04 that involve significant IT costs or burden and should be dropped?
We agree that the current requirement that institutions provide a rating split per country in template C103 and C102 increases the number of portfolios leading to excessive granularity. This has made the completion of the template unnecessarily onerous without adding analytical insight as there are many countries that will share the same model for similar exposures.Creating a simplified rating split model on template C105 as proposed would not result in losing explanatory information on the variability of benchmarking parameters. Where model calibration and risk parameters are significantly different across countries, then country specific models would be used and with inclusion of the internal model ID and model name fields in the template the relevant splits providing explanatory power would be maintained.
We would find it helpful if the exposure class field was included in template C105.4 even if the model name field already indicates the exposure class.
We do not expect that any data points on C105.04 would involve materially incremental IT costs or other burden.
We would welcome clarification whether templates C200 and C300 need to be calculated and populated for rating/country splits for which there is not any exposure in the current year but where there has been within the previous 5 years.
Do you agree that SLE portfolios should be reported in a separate exposure class? Do you agree that the proposed level-2 breakdown on (a) the proposed sectors of counterparties and (b) the proposed types of exposures (i.e. categories of specialized lending) might be relevant components to explain the variability of risk parameters? Which option do you prefer with respect to the rating split under the slotting approach?
We agree that Specialised Lending should be reported as a separate exposure class rather than be reported as subportfolios of the Large Corporates benchmarking portfolios as in the 2019 benchmarking exercise.We also agree that the combination of sector and type split of the exposures are sensible components to explain the variability of risk parameters.
Of the options presented in the consultation paper, we would prefer Option 1, the current approach in the CP, which would not require a rating split for specialised lending under the slotting approach. We are not sure whether the additional split proposed in Option 2 would enhance the additional explanatory power of the exercise.
Do you expect that the LDP sub-portfolio characterized by eligible covered bods will cover a material share of exposure? Do you expect that the separation of these exposures can contribute to explain RWA variability?
We do not believe that the proposed separation would contribute to the explanation of RWA variability as, for Standard Chartered Bank, the LDP sub-portfolio characterized by eligible covered bonds would not cover a material share of exposure. As of Q3 2018, our covered bonds represented only 4% of our IRB institution’s exposure.Do you think the alternative portfolio split would provide for a higher explanatory power as regards RWA variability induced by differences in CRM usage?
We do not think that the proposed alternative portfolio split, a subdivision of a considered portfolio into homogenous portfolios in terms of collateralisation, would be very useful. Adding this split to C103 would only provide additional explanatory power for Corporate SMEs as this asset class contains a variety of collateral types. For the other asset classes, the overwhelming majority of the collateral is in a single type e.g. retail secured by real estate, and real estate collateral.We assume this to be the case for most other institutions. It is likely that the additional split of data would bring about further validation and data issues increasing the reporting burden.
Do you expect that the proposed NACE Code breakdown for HDP sub-portfolios will provide more explanation for RWA variability for a material share of exposure? Do you expect that the separation of these exposures can contribute to explain RWA variability in the according HDP portfolios or do you consider the current split using only NACE code F sufficient? Does the selection of a subset of NACE codes significantly reduce the burden of the data collection (compared to a comprehensive collection of all NACE codes)?
We think that the proposed more granular NACE Code breakdown may provide more explanations of RWA variability.We do not consider the current split using only NACE code F to be sufficient. The current (construction only) breakdown does not represent a significant part of the exposure class. In last year’s exercise, construction firms formed only a small part of the total exposures for non-SME corporates.
We agree that choosing a subset list at the sector level as proposed will reduce the burden of data collection.
Do you expect that the proposed ILTV buckets for HDP sub-portfolios secured by immovable property will provide more explanation for RWA variability for a material share of exposure? Do you expect that the separation of these exposures can contribute to explain RWA variability in the according HDP portfolios?
Yes, we believe that the additional granularity at higher LTV values will provide better insights into where the RWA has more potential to vary between institutions.As the low (<50%) LTV bands have relatively low RWAs, combining them and adding more granularity for higher LTVs that have a higher proportion of the RWAs may provide additional explanation for RWA variability.
The EBA may want to consider aligning the LTV buckets to the one proposed in the new Basel III framework.