Cover Letter: Discussion Paper: Future of the IRB Approach
Barclays welcomes the opportunity to comment on the EBA’s key discussion paper on the future of the IRB approach and valued the opportunity to attend the hearing at EBA’s offices on 8 April 2015. Our main points are summarised below and the attached Appendix contains answers to the specific discussion paper questions:
1. Retaining Flexibility: Barclays supports the EBA’s intention to improve the comparability and consistency of the IRB Approach and considers that greater harmonisation of the components of the IRB Approach will affirm and support the IRB Approach as an effective method for measuring risk. However Barclays considers that it is essential to maintain a degree of flexibility within the framework to maintain a risk sensitive approach.
2. Implementation Approach: There should be caution in implementing changes to the different elements in phases as there may be a challenge when the market is looking for a result as a whole. This could potentially lead to perverse outcomes when compared to introducing all changes simultaneously.
3. Use of Historical Data: Adjusting retrospective data to fit a materiality threshold is complex and it may be difficult to create wholly reliable time-series of default data without a high margin of error. Barclays would therefore recommend that banks should be permitted to build up data on a go forward basis. Alternatively a trade off between the length of the historical period required and the reliability of the data would need to be reached.
4. Timescales: Barclays considers that the timescales proposed may be rather ambitious if the presumption is that all regulatory models will need to be built from first principles and there would be a stretch of both Regulator and banks resources. If greater flexibility is provided on the extent of the implementation, then the timescales proposed may be possible to meet.
5. Alignment with other Regulatory Changes: Barclays considers that it is essential that the reforms and timescales should be fully aligned with other related regulatory initiatives relevant to risk management. To this extent we consider that there is an opportunity to reform the IRB Approach in conjunction with the Basel Committee’s work on RWA consistency and in addition there is also an opportunity to align the timelines with the implementation of IFRS9 Impairment which will also involve substantive changes to models. This will enable banks and Regulators to address the changes simultaneously thereby optimising resources and minimising associated implementation costs.
If you have any queries, or would like to discuss any points made in this letter, please do not hesitate to contact me.
Q1. It is difficult to confirm that the proposed prioritisation and groupings are appropriate without knowing the full extent of the changes which will be involved for each element. However on the face of it, the proposed groupings appear to be logical. We would however suggest that timelines are aligned closely with Basel and the upcoming other initiatives including for example the accounting changes being introduced under IFRS9 Impairment.
The challenge is making what might be perceived as piecemeal changes when the market is looking at the result as a whole. In such cases this could lead to potentially perverse outcomes compared with introducing all proposed changes simultaneously.
We consider that it is essential that the prioritisation of changes should be closely aligned to the Basel changes to avoid uneven global implementation.
We agree that the three pronged approach set out in the discussion paper will help improve the transparency of IRB models and their outcomes via developing technical standards and guidelines on key aspects of the IRB approach, monitoring of supervisory practices which in particular will include the use of benchmarking exercises and measures to enhance transparency around IRB models (with areas of priorities including the definition of default, LGD and conversion factor estimation, PD estimation, treatment of defaulted assets and Credit Risk Mitigation).
However as has been acknowledged by the EBA, although some of the non-risk based differences will be addressed by the above measures, legitimate reasons exist as to why the estimates of the drivers of risk for each exposure (PD, LGD, EAD and M) can be different across financial institutions including the inherent risk in the different asset classes, expert judgement, firms own historical loss experience, approach to managing and mitigating risk.
In isolation the timelines are extremely challenging if the presumption is that all regulatory models will need to be rebuilt from first principles. However if the rules were flexible to allow for the use of high level post model adjustments to capture the essence of the change this would be achievable. However the challenge will be if the regulatory interpretation is such that a full and complete rebuild is required for which skilled resources are likely to be in extremely short supply.
If it were possible to introduce the changes as part of a structured approach aligned to the annual validation and model rebuild timetable that firms maintain this would help mitigate the risk of untimely implementation.
Other than for CRM, where the possible changes appear to be relatively modest, the implementation timelines appear to be inadequate. For example if the default definition is changed, default histories would need to be re-stated to ensure that model calibrations are appropriate and in those cases a two year implementation window is unlikely to be sufficient.
If the definition of default, definition of an economic downturn and treatment of defaulted assets are modified, default or data histories would need to be refreshed, model parameters varied and/or calibrations updated across the model suite. In some cases, it might not be possible to re-state data.
With regard to PD estimation, the proposed requirements for calculating long-run default rates as basis for TTC PDs are defined by rating bucket/grade, hence would only be applicable to institutions that empirically calibrate their master scales to observed defaults. Where a bank’s modelling philosophy is fundamentally different, as allowed for under the CRR, and based on direct estimation of PDs without any bucketing. If enforced, such a change would call for revision and redevelopment of all PD models across the bank, hence the proposed timelines would be insufficient.
In respect to the treatment of defaulted assets, a harmonised definition of default would be challenging to apply to models based on external data for example. This could delay implementation considerably for those portfolios.
Where the definition of default is based upon the unlikeliness to pay indicators contained within CRR Art. 178.3 these will require a subjective assessment as they are prior to actual default. In these cases it will be difficult to achieve perfect harmonisation in the absence of overly prescriptive rules which are unlikely to ever be sufficient to cover all eventualities.
The following are examples of occasions where we have adjusted historical data:
• The most substantive adjustment took place for the preparation of the first IRB applications during the implementation of Basel II in order to meet the inputs required. This was especially the case for the estimation of LGD which required a level of data that banks had not been previously been required to collate and thus was not generally available.
• Historical data (EDF time series) have been adjusted for some regions during a local downturn period to align the PD estimates with the observed default rates.
• External historical data (e.g. S&P CIQ) are periodically backward-adjusted by the data vendor affecting mainly PD models which have been calibrated to reflect the external data.
• Historical ratings data and list of defaulted counterparties are adjusted by Moody’s and S&P periodically, affecting models that incorporate such data.
Adjusting retrospective data to fit a materiality threshold is complex and it may be difficult to create wholly reliable time-series of default data without a high margin of error. Incorporating unreliable data into models may lead to significant bias and will not improve RWA comparability. There would also be practical problems as business processes are aligned to the definition of default which were in force at the time. Assessing past performance on a definition that was not used at the time is unlikely to be a reliable indicator of future performances. We would therefore recommend that banks should be permitted to build up data on a go forward basis. Alternatively a trade off between the length of the historical period required and the reliability of the data would need to be reached.
The expected materiality of the changes to IRB models is difficult to assess, pending fuller information about the proposals. This includes, among others, details on the nature, severity and duration of an economic downturn, details on PD computation (including guidance on how to combine different data sources and calibrate margins of conservatism), the identification of stressed years and how to cope with the absence of the time series of adequate stress conditions to capture a downturn, downturn adjustment of LGD and conversion factor estimates (including the treatment of incomplete workouts, treatment of collateral and guarantees, discounting factor, margin of conservatism and costs etc) and the treatment of multiple defaults.
We consider that differences in long-run default rates for similar groups of obligors are likely to converge across institutions based on the proposed changes. However, individual obligor PDs will depend less on the proposed changes and more on which factors are (or are not) used in the calibration of the model – e.g. use of different financial ratios or different calculation of financial inputs can produce large differences between institutions’ PD estimates.
The consultation paper refers to defaulted exposures that cure to non-default status and then return to defaulted status in a short period of time being treated as a constant default event from the first occasion. It would be helpful if clarity could be provided as to the meaning of a short period of time (does this mean one year, six months, 90 days, etc?). There is a potential risk of performing names being marked as defaults. Estimation of transition matrices also requires default to be a terminal state.
With regard to downturn adjustments of LGD and conversion factors, a downturn period could vary by industry sector or by region/geography. Any move towards consistency should recognise that a common downturn period might not be desirable. How the duration is defined is also of relevance (e.g. market indices from peak to trough).
Rules related to use of external data for PD and LGD/EAD calibration. In particular, the definition of default when an exact definition cannot be applied because it is not known how an obligor that was classified as a defaulted case by the data vendor actually defaulted, i.e. cases with unknown materiality threshold.
Inclusion of qualitative factors or indicators in models is often questioned so guidance on the use of such factors would be welcome, along with the preferred approach for embedding qualitative factors.
For some portfolios where there is sufficient data to construct bespoke LGD models for defaulted assets, these have been applied. These are typically for Retail where sufficient default history exists. However in the majority of cases there is insufficient default data to develop statistical models and so “expert judgement” based methods are used to supplement the calculation of ELBE and LGD in default estimate.
Yes. Our initial assessment suggests that the proposed changes will go a long way to eliminating firm specific differences in the treatment of defaulted assets.
Guidance on the LGD approach for forbearance cases would be welcome.
A balance needs to be struck between the roll-out period given to banks and any quantitative RWA / exposure thresholds imposed. The time horizon to achieve roll-out should not be too short such that banks are unable to meet minimum risk management standards by ensuring appropriate quality of data, methodology and output. Additionally, it needs to be recognised that banks can only meet their time defined roll-out plans if the regulator is able to review models and provide feedback at a corresponding pace.
We do not anticipate any direct organizational structural change would be required due to these proposals.
The proposed grouping and prioritisation of regulatory products is logical, however it should be recognized that any changes to the CRM framework also need to flow into LGD estimations. The omission of such guidance in the beginning of the process could lead to undesirable multiple changes to IT systems and LGD models to address LGD calibration and further revisions to LGD at a later date due to changes in CRM rules.
The main initiative that has the potential to diverge is the IFRS9 accounting rule changes that introduce the concept of significant deterioration, which is an earlier state to default as required under the regulatory rules. In addition, where exposures, either on an individual or collective basis, meet the significant deterioration criteria and assessment of lifetime ECL is required.
Fundamentally we think that disclosure is a key topic and that adequate disclosure will enhance transparency and reinforce internal models credibility. However, we disagree with the publication of benchmarking exercise results on the EBA website. Currently, the final version of the BCBS disclosures already include numerous disclosure templates for external stakeholders which would benefit from a greater harmonisation. Disclosure over and above the current requirements as this may present customer and firm confidentiality issues.
Our experience of benchmarking is that whilst well intentioned, requires an extremely detailed and granular set of assumptions such that external disclosure without the full set of assumptions would be misleading and likely to have market impacts.
In general we support more harmonised disclosures as outlined. We believe that the prioritisation is best developed through the Enhanced Disclosure Task Force (EDTF).
As above, such modification should be developed through the EDTF.
There continues to be the potential for differing levels of capital held between banks, depending on how the book is segmented, what constitutes a low default portfolio, and if a particular sector might be deemed to be a low default portfolio in one bank but not in another (either due to segmentation or data volumes). It would be helpful if a defined approach could be specified for those sectors or types of entity which might reasonably be expected to constitute low default portfolios or where data volumes are limited even if 20 data points exist. This could include adoption of the Foundation IRB approach, although the proposals in PRA CP 12/14 were not taken forward. Greater consistency in terms of how data points should be identified might also be worthy of consideration.
Fundamentally we do not subscribe to the notion that firms intentionally set out to mis-report their risk positions. It may be appropriate to develop a different style of disclosure which provides confidence to the accuracy of models used to support IRB estimates. This would be most relevant for material businesses and portfolios and the models used in those areas.
Yes. Data capture and reconciliation would be incrementally more difficult unless these are aligned.
It should be recognised that the regulatory measure of PD is appropriate for some, but not all elements of risk management. For example, when pricing at origination a more PIT approach may be more relevant. In addition, for stress test and planning purposes it is appropriate to consider future economic conditions which may deviate from a pure TTC approach.
Whilst in principle this is appealing substantial differences arise from the different historical observation periods that firms have applied. Therefore if the objective is to minimise potentially inappropriate RWA differences harmonisation on the observation periods is a step in the right direction. However this is not without challenge, for example, where a bank moves into a new market or changes direction the data availability could be constrained rendering comparisons difficult.
We consider that the prime drivers of risk and capital estimates are captured for Pillar 1 purposes. However we believe there is scope for inconsistent interpretation and application within Pillar 2 for RWA risks contained within Pillar 1.