Response to consultation on Draft Guidelines on the methodology to estimate and apply credit conversion factors under the Capital Requirements Regulation

1. Question 1: How material are the cases for your institution where you would have to assign an SA-CCF to exposures arising from undrawn revolving commitments and thus restrict the use of own estimates of LGDs within the scope of application for IRB-CCF in the CRR3? For which cases would you not have enough data to estimate CCFs but have enough data to es-timate own estimates of LGDs?

 These cases are estimated to be immaterial. 

However, the consultation paper introduces the concept of a “Fixed CCF” for exposures that fall within the scope of the IRB-CCF framework, but for which institutions are unable to assign an IRB-compliant CCF due to not meeting the minimum estimation requirements. This may occur, for example, when LGDs are robustly estimated, but CCFs are not. In such cases, institutions are required to apply a Fixed CCF, which incorporates a MoC quantified by the institution. The minimum level of final CCF including MoC must be no less than 100%. First of all, the introduction of the Fixed CCF does not appear to be fully aligned with the provisions of CRR III - Article 166(8b), which explicitly permits the use of SA-CCF for exposures where the minimum requirements for estimating IRB-CCF, as outlined in Section 6, are not met (e.g., due to data scarcity). Notably, this article makes no reference to the LGD estimation approach, which in our view supports the applicability of the IRB-LGD combined with SA-CCF approach.

In addition, while the introduction of a Fixed CCF for portfolios affected by data scarcity may offer a pragmatic solution, the imposition of a minimum CCF of 100% appears overly conservative. This threshold may disproportionately disadvantage institutions using IRB-CCF compared to those applying the SA-CCF, particularly in the case of unconditionally cancellable commitments, where the gap between Fixed CCF and the corresponding SA-CCF can be significant for the same type of product.

2. Question 2: Do you have any comments related to guidance on the identification of a relat-ed set of contracts which are connected such that they constitute a facility?

Restructuring, both pre-default and post-default is most relevant in the context of connected facilities. During such restructurings, a revolving facility may be used to settle a non-revolving facility (e.g., a term loan) via interfacility balance transfers. In these cases, no additional funds are disbursed by the bank to the obligor. However, the drawing on the revolving facility increases, which affects the estimation of both pre-default and post-default drawings for revolving facilities. Given that no new funds are provided to the obligor, it is proposed that the EBA specifies that changes in drawings on revolving facilities resulting from interfacility transfers should not impact the realised CCF or LGD. This approach significantly simplifies dealing with related facilities and reduces divergent interpretations of the impacts on the realised CCF and LGD of migrations between related facilities due to interfacility transfers.

To further simplify the identification of related facilities, we propose that where the same collateral agreement is shared between different revolving commitment facilities that are linked to obligors in the same controlling structure, the option be available to group these facilities together.

3. Question 3: Do these GL cover all relevant aspects related to the definition of revolving commitments that you consider relevant for the scope of the IRB-CCF? Have you identified any product that should be in the scope of the IRB-CCF that is currently excluded in the GL? In terms of off-balance sheet exposures, how material are the exposures that fall within the defined scope of the IRB-CCF for your institution?

We have not identified products that are incorrectly excluded from the scope of IRB-CCF. 

However, we do not agree with including into the scope products offered but not yet accepted, as specified in par. 20(a) page 60 of the CP. This scope increase is also in conflict with the par. 313(b) of EGIM 2025 which specifically refers to “arrangements … accepted by that client”.  We therefore request clarity on this conflicting scope requirement.

4. Question 4: Are there products that have an advised limit of zero but a nonzero unadvised limit that should be included in the scope of the IRB-CCF GL? How material are these cases for your institution?

We do require clarity on the treatment of facilities that have a seasonal revolving-credit feature.  Specifically, these facilities have an agreed limit schedule where in some months the limit is zero (including unadvised limit) and in other months the limit is non-zero. Therefore, the same facility exists over time, but the revolving feature is not always available to the client. Furthermore, when the client requests to end the revolving facility, there may still be an outstanding balance that the client will repay over time. However, during this repayment period the facility will not have a revolving feature. It is not clear from the CP how these facilities should be treated in model estimation as well as model application, especially for the periods where the facility has no revolving feature, i.e. the limit is zero.

5. Question 5: Do you think that dynamic limits (e.g. limits the extent of which is dependent on the market value of financial collateral pledged by the obligor in relation to the revolving loan) warrant a specific treatment in the IRB-CCF GL? How material are these cases for your institution?

These cases are not material for our bank. 

We do not think a separate treatment should be specified. The reasons are that when these cases are material:

• These cases can be treated as a separate calibration segment, if needed.
• The existing requirement to consider, among others, bank-management practices as risk drivers is already sufficient to capture unique behaviour of these product types, when modelled as part of a larger product portfolio.

6. Question 6: Have you identified any unwarranted consequences of including fully drawn revolving commitments in the scope of the IRB-CCF. How material are these cases for your institution?

These facilities are approximately 15% of the historical defaults for the Corporate and 17% for the Retail SME exposure classes. We include in these samples also overdrawn facilities. Likely challenges envisaged are that these facilities are dominated by relatively small exposures, yet contribute materially to the LRA CCF due to the required number-weighting averaging scheme, and limited options for outlier treatment during risk quantification. 

We also note that the inclusion of fully drawn commitments in the scope of CCF estimation as being in conflict with the definition of credit conversion in CRR Article 182(1), which only considers credit conversion where there is an undrawn portion available (i.e. not fully drawn), and request that EBA clarifies this conflict.

8. Question 8: Are there cases for your institution where the calibration samples should be shorter than the sample used to calculate the long run average (LRA) CCF

No. Conceptually, the main reason that a shorter calibration sample compared to the LRA sample would be considered is to make the calibration sample more representative of current portfolio and market conditions. However, there are already other sufficient mechanisms to deal with non-representativeness. 

Related to the LRA calculation, we welcome the direction and clarity provided by EBA that the LRA be calculated as the sample average rather than the average of annual averages as specified in par. 322(d) of the 2025 ECB guide to internal models.

Furthermore, it is proposed that EBA clarifies that the analysis of good vs. bad years with in the LRA period specified in par. 322(e) of the 2025 ECB guide is no longer relevant given that the LRA is now specified as a sample average (and not annual averages) and that existing mechanisms specified under the representativeness section are sufficient to address concerns related to having a non-representative LRA period.

9. Question 9: Do you have any concerns with the requirements introduced to analyse and mitigate a lack of representativeness for CCF? Do the requirements on the different data samples when observing a lack of representativeness impede your ability to model CCF portfolios?

We do not have specific concerns, and welcome the simplification. However, from a cross-risk-parameter alignment perspective, it is not clear why a simpler analysis for CCF estimation is warranted over PD and LGD (as described in EBA/GL/2017/16), and request that EBA clarifies this position.

10. Question 10: Do you have any concerns with linking the fixed CCF to the lack of historical data available to the institution in relation to the coverage by the RDS of material subseg-ments of the application portfolio? How is your institution currently treating these cases?

We request EBA to clarity if the proposed Fixed CCF is still treated as an IRB-CCF, or as a SA-CCF and to clarify if for these exposures IRB-LGDs are still applicable (see also Question 1).

Should the proposed Fixed CCF not be the same as the SA-CCF, it is counterintuitive to first estimate IRB-CCF on segments where data limitations are already known to significantly hamper the estimation and then quantify a MoC to potentially bring the IRB-CCF above 100%. In addition, the imposition of a minimum CCF of 100% appears overly conservative compared SA-CCFs.  It could be considered to instead apply SA-CCF directly, removing the need for IRB-CCF estimation for these segments.

11. Question 11: Are there any concerns with requiring consistency in the analysis of changes in the product mix with the institution’s definition of facility? Are institutions able to identify and link contracts (partially) replacing other contracts where the closing or repayment of one contract is related to the origination of a new contract? Are institutions able to link new contracts that are originated after the reference date to related contracts existing at refer-ence date? In particular, is it possible in the case contracts that are revolving commitments are replaced by contracts that are non-revolving commitments (e.g. by a term loan)?

Although these requirements are in principle reasonable, in practice, it is difficult to uniquely link contracts over time. 

Also refer to our response under question 2 to exclude interfacility transfers that will simplify dealing with connected facilities.

12. Question 12: Do institutions consider it proportionate to the risks of underestimation of CCF to perform the identification analysis and allocation procedure? If it is deemed not propor-tional, what would be an alternative approach that is still compliant with Article 182(1b) CRR?

The same points that we raised in question 11 apply. 

13. Question 13: Do you have any concerns on the proposed approach for the treatment of so-called ‘fast defaults’? In case you already apply a 12-month fixed-horizon approach, do you apply a different treatment for ‘fast defaults’ in practice, (and if so, which one)? Is the ‘fast default’ phenomenon material according to your experience? If yes, for which exposures, exposure classes or types of facilities?

We do have concerns with the inclusion of “fast default” in the scope due to the likely bias these defaults add to the estimation. Any such bias cannot be objectively determined and corrected. We therefore propose to exclude fast defaults from the scope provided that the number of fast defaults is below a threshold, for example 10% of the commitment default observations. Only where the number of fast defaults exceed this threshold, should it be included in the scope since the larger proportion of fast default are then likely to be structural phenomena in the portfolio under consideration.

14. Question 14: Do you have any concerns on the multiple default treatment? To what extent are your current models impacted by the application of a multiple default treatment?

We welcome the clarity on the required treatment of multiple defaults.  The impact on CCF of applying the MDT is immaterial in our portfolios.

15. Question 15: Do you agree with the three principles for the calculation for realised CCF in the context of consumer product mix, and their implications for the cases mentioned as ex-amples? In case of disagreement, what is the materiality of the cases with unwarranted re-sults, in particular in relation with the definition of facility applied in your institution? In case of material unwarranted results, can you describe your alternative practice to this CP?

We agree in principle. Our concerns are that the linking of facilities is difficult in practice as already listed in our responses to questions 11 and 12. We require clarification on the following cases:

• In light of paragraph 63(b)(ii), in the cases where no contract information is available, but a non-revolving commitment is present at reference date, how should we treat new non-revolving commitments that originated between reference date and default date?
• Based on paragraph 79(b), do we understand correctly that if a facility consists of a single term loan which is transformed into a revolving loan between the reference date and default date, then this facility is not in scope of the CCF estimation?

16. Question 16: Are there any concerns related to the allocation mechanism described in these GL?

We list no concerns.

17. Question 17: Where credit lines are kept open even if the facility is in default, the alterna-tive option described in this consultation box could lead to high realised CCF values. Is this a relevant element for your institution and if yes, why and how material are these cases with-in the scope of IRB-CCF models?

The management credit lines after default is typically not the same as before default. Specifically, additional drawings are approved and are linked to forbearance measures to limit losses for the bank, making in-default drawings more controlled and linked to specific expenditures agreed with the obligor compared to performing drawings where the obligor has less restrictions to draw and use drawings. Therefore, the consideration of the limit amount after default is less relevant. However, the CP proposes to calculate the realised CCF for defaulted facilities different for utilisation<100% and utilisation>=100%. However, due to the drawings being more controlled after default, we believe that the limit amount is less relevant (as outlined above), and therefore a distinction between utilisation <100% and >= 100% is not beneficial.  We therefore propose that the in-default realised CCF should not use the limit amount, but only be calculated as follows, (which aligns with the CP’s proposal for utilisation>=100%, but is proposed to be used irrespective of the limit amount and utilisation):

CCF_at_reference = (Outstanding_at_reference + Additional_drawings_after_reference) / Committed_amount_at_reference

Here of committed amount is defined as the maximum of limit amount and actual drawn amount (also see our response to Q32).

An additional benefit of this simplification is that less modelling segments are needed for the in-default model, which reduces model complexity and avoid splitting already sparse data into more modelling segments (especially since non-retail portfolios, for which the in-default CCF is required, typically have much less observations than retail portfolios, for which the in-default CCF is not a requirement).

With respect to the calculation of the additional drawn amount, we propose to clarify in the GL that in cases where institutions infer post-default cashflows from changes in, say, monthly account balances, a monthly granularity for calculating the additional drawn amount is acceptable.

18. Question 18: In case of multiple defaults, the CCF might also be driven by drawings while the obligor was in its default probation period or in the dependence period between the merged defaults. Do you expect this to be material for your CCF models?

Not material for our portfolio.

19. Question 19: Do you see any unwarranted consequences of the proposed approach for in-corporating additional drawings after default? In particular, in order to maintain consistency between the realised CCF calculation and the calculation of the denominator of the realised LGD as described in paragraph 140 of the GL PD and LGD, would this require a redevelop-ment of your LGD models?

Some challenges are noted, namely:

1. Different drawing behaviour before and after default: Conceptually, the drawing behaviour is fundamentally different before default (for performing facilities) and after default (for defaulted facilities). This is because the drawings from performing facilities are mainly driven by obligor decisions and needs, compared to in-default drawings that are more controlled via bank forbearance measures and less so by obligor decisions. This CP proposes that the realised CCF combine performing and in-default drawings. This hybrid definition forces the same risk drivers to be considered for both the performing and in-default behaviour. Separating the performing and in-default realised CCFs (rather than having one hybrid realised CCF) would allow more optimal and parsimonious model components to separate performing and in-default behaviour. We propose that the option be available to separate the performing and in-default component should the hybrid definition cause demonstrable non-intuitive results.
2. Simpler in-default realised CCF calculation: The CP proposed to calculate the realised CCF for defaulted facilities different for utilisation<100% and utilisation>=100%. However, due to the drawings being more controlled after default, we belief that the limit amount is less relevant, and therefore a distinction between utilisation<100% and utilisation>=100% is not beneficial.  We therefore propose that the in-default realised CCF should not use the limit amount, and therefore also not utilisation, but only be calculated as follows (which aligns with the CP’s proposal for utilisation>=100%, but is here proposed to be used irrespective of the limit and utilisation): 

           CCF_at_reference = (Outstanding_at_reference + Additional_drawings_after_reference) / Committed_amount_at_reference

Regarding the sub-question on the impact on LGD model redevelopment, this change may trigger a redevelopment of the LGD model because the target variable would be affected. Therefore, we propose that:

1. Different approaches should be considered admissible provided consistency between CCF and LGD is ensured, and
2. In case of changes relevant for the LGD model, guidelines should be given on how to apply these guidelines for the first time.

20. Question 20: Do you think that the relative threshold is an appropriate approach to restrict the use of the alternative CCF approach for those facilities in the region of instability? Do you think it is appropriate to define a single relative threshold per rating system or are there circumstances where multiple relative thresholds would be warranted? Do you see a need to use an absolute threshold in addition to the relative thresholds?

We understand that “threshold” here refers to a threshold that identifies the ROI, e.g. a specific utilisation threshold above which level the ROI is defined. We welcome that a regulatory value is not prescribed. Multiple relative thresholds within a rating system are preferred to capture the idiosyncratic features of the modelling segments under consideration.

With respect to the realised CCFs observed in the ROI, we propose that the EBA clarifies that fundamental statistical techniques – such as the treatment of outliers using percentile or absolute caps – are permissible to enhance the robustness of model estimation. This proposal considers paragraph 322(c) of the 2025 EGIM, which is typically interpreted by assessment teams of the Supervisory Authority as prohibiting statistical outlier treatment for risk quantification. Such an interpretation conflicts with the overarching objective of achieving robust and reliable risk-quantification levels that are unbiased by extreme outliers.

21. Question 21: Do you consider the guidance sufficiently clear in relation to the requirement for institutions to set up a policy to define a threshold value?

Yes.

22. Question 22: Do you consider it appropriate to set a prescribed level or range for the de-fined threshold, and if so, what would be an appropriate level for the threshold? In case an absolute threshold is warranted, what would be an appropriate prescribed level for an abso-lute threshold?

No. every institution and portfolios within institutions would likely display different behaviour making a prescribed threshold less suitable. It should be up to the institution to define their own threshold based on the guidance provided in the guidelines. Also for the absolute threshold, the value should be set by the institution.

23. Question 23: Do you think that, for the facilities in the region of instability, and/or for fully drawn revolving commitments, a single approach should be prescribed (e.g. one of the ap-proaches above defined in the Basel III framework), or that more flexibility is necessary for institutions to use different approaches they deem most appropriate for these facilities?

Flexibility is always preferred to better reflect the unique and idiosyncratic behaviour in credit conversion in different portfolios and portfolio segments, that cannot always be captured with a “one size fits all” approach. 

With respect to the ROI, we prefer the BIS CRE 36.95 approach in par 98.a, i.e. the limit at reference in the denominator, and for fully drawn observations, the approach in 98.b. i.e. the drawn amount in the denominator.

24. Question 24: If such flexibility is indeed warranted, what is the technical argumentation why prescribing a single alternative approach for these facilities is not suitable? Which cases or which types of revolving commitments could not be modelled under the approaches pre-scribed? Are there types of revolving commitments that could not be modelled by any of the approaches described in the Basel III framework?

Currently the approach of using a limit factor is suggested. However, in the case of low limits, this could also create other, unwanted instability. Furthermore, in the case of overdrawn facilities, it may make more sense to use a balance factor rather than a limit factor as this is the committed amount at reference date. Allowing institutions some flexibility in their approach would result more appropriate CCF modelling, i.e. a single overarching approach might not provide the most appropriate solution for different portfolio and product characteristics.

25. Question 25: Which of the three approaches described in the Basel III framework is pre-ferred in case a single approach would be prescribed?

We prefer 98.b., i.e. the drawn amount at default date as a percentage of the drawn amount at reference date.

26. Question 26: For the purpose of the long run average calculation, are there any situations where such intermediate exposure weighted averaging at obligor level would lead to a dif-ferent outcome (that is unbiased) with regard to the CCF estimation? How material is this for your portfolio?

We do expect a different outcome for our non-retail portfolios. Regarding the averaging method for the LRA calculation, we note the CP specifies sample averaging, which is a conflicting requirement compared to the ECB EGIM (July 2025, par. 322(d)) which requires yearly averaging. 

27. Question 27: Do you have any comments on the condition set to use the simple approach to estimate additional drawings after default. Do you consider that the simple approach is also relevant for retail portfolios?

The conditions specified for the simple approach resembles the modelling approach, Therefore, it appears that the simple approach is an outcome of the modelling approach and should therefore not be specified as a separate approach, i.e. the modelling approach must be used anyway to check if the imputation from unresolved to resolved status of all unresolved cases do not impact the LRA CCF, in order to justify the use of the simple approach.

28. Question 28: It was considered that requiring institutions to exclude unresolved cases from the long run average CCF, if their realised CCF is lower than the LRA of the corresponding fa-cility grade, could be seen as too conservative. Do you have any comments on this treat-ment introduced in the simple approach? Do you have specific examples when this treat-ment would not be appropriate?

For non-retail portfolios that have longer workout periods, the exclusions of unresolved cases do create challenges in determining the appropriate calibration level for the recent years, due to the reduced number of resolved cases in the recent years. Furthermore, back-testing results for the recent period are typically inconclusive due to the use of a reduced sample size.

29. Question 29: Do you have any comments on the modelling approach to estimate additional drawings after default for unresolved cases?

We do prefer Option A (alignment of the maximum drawings period with the maximum recovery period used for LGD).

30. Question 30: Do you have any concerns with the requirement to use as a maximum drawing period the maximum recovery period set for LGD?

No concerns are noted. We welcome the simplification and improved alignment due to using a maximum drawing period consistent with the maximum recovery period.

31. Question 31: For CCF estimation, do you use estimation methods that incorporate portfolio-level-calibration of the estimates? What are the main reasons to use a calibration at a level that is higher than the grade-level calibration?

Generally, calibration at levels lower than the portfolio level is preferred to better capture the varying risk levels within the portfolio. The following reasons may require calibration at levels higher than the grade level: 

1. Limited observations per grade level, e.g. especially for non-retail portfolios.
2. Additional model complexity caused by too granular segmentation (if calibration segments are defined at a grade-level) because of the requirement to estimate downturn, appropriate adjustments and margins of conservatism at the calibration-segment level.
3. A too granular calibration segmentation causes the estimation error per segment to increase since this error scales proportional to the number of observations per segment which then artificially increases the IRB CCF estimate after application of margin of conservatism, and therefore may overstate EAD and therefore RWAs.

Note that calibration to the grade levels defined within a larger calibration segment is possible, for example using techniques such as a calibration function within the calibration segment that considers the individual grade levels, e.g. utilisation ranges. However, when this technique is used, it may be interpreted as having separate calibration segments for every grade level. Therefore, it is proposed to clarify that when a calibration function is used within a calibration segment to calibrate to the individual grade levels (e.g. utilisation buckets) in that calibration segment, that these individual grade levels are then not considered as separate calibration segments for the purposes of downturn, appropriate adjustment and margin-of-conservatism assessments. 

For non-retail portfolios we use a continuous scale, and not a grade-level scale. It is proposed that the GL specify how the references to “grade-level” must be interpreted when continuous scale models are used.

Also refer to our proposal at Q20 to clarify that classical statistical techniques such as outlier treatments using percentile or absolute caps are permissible to ensure that calibration levels are not biased by extreme outliers in the calibration segment under consideration.

With respect to the impact of calibration on rank-ordering, par. 99 of the EBA/GL/2017/16 specifies that the calibration may not influence the rank-ordering. Although in the PD section, this requirement is typically interpreted by institutions and assessment teams as applying to all IRB risk parameters. Since CCFs are floored at zero for calibration purposes, but the option is provided to still have a rank-ordering model that does not zero-floor CCFs, the scenario unfolds were the rank-ordering after calibration changes. We therefore request clarity on whether the requirement in par. 99 of EBA/GL/2017/16 applies to CCF.

32. Question 32: Do you have any comments on the guidance for the CCF estimation of default-ed exposures?

The guidance specifies that the denominator of the in-default CCF is the “committed amount”.  The committed amount is defined as the maximum of the advised and unadvised limits. For overdrawn facilities, this definition of “committed amount” has the limitation that the committed amount is less than the actual drawn amount. We propose that the definition of committed amount be clarified for overdrawn facilities as the maximum of limit and actual drawn amount.

33. Question 33: Do you have any comments on the determination of the low share of ob-served additional drawings after default in the historical observation period relative to the observed undrawn amount at default date? Do you consider it appropriate to set a pre-scribed threshold to determine what constitutes this low share? If so, what would be an ap-propriate value for such a materiality threshold?

A guidance threshold rather than a prescribed threshold for what constitutes material drawings after default is preferred due to the unique drawing behaviours in non-retail portfolios.

34. Question 34: Are there examples where the haircut approach should be considered the most appropriate approach for estimating the downturn CCF?

No, we do not consider the haircut approach the most appropriate. We support the guidance in the CP that for Type 2 estimation approaches only the extrapolation approach using macroeconomic variables be used.

It is proposed that the CDR on downturn periods and the GL DT LGD be updated with the variations considered here for the GL CCF to avoid having to “stitch” together different guidance documents to get obtain the final applicable guidance.

35. Question 35: Do you think the add-on of 15 percentage points is adequately calibrated when the downturn impact cannot be observed nor estimated? Could you provide clear examples or reasons why this add-on should be higher or lower than 15 percentage points?

The 15pp add-on, in the context of CCF seems arbitrary, and cannot be verified internally by a bank. It can potentially only be tested using industry-wide realized CCF time-series data to determine an industry-average CCF increase over typical downturn periods.

We also expect that such an add-on should vary with the available headroom, and that a fixed percentage is therefore too simplistic.

36. Question 36: Have you observed, or do you expect a (statistically significant) correlation be-tween economic indicators and realised CCFs? If so, do you expect higher or lower levels of CCFs observed in the downturn periods compared to the rest of the cycle? Do you have pol-icies in place that restrict or, on the other hand, relax the drawing possibilities in the down-turn periods?

 We typically find it challenging to obtain statistically significant correlation between CCFs and macroeconomic variables in our portfolios. It is not clear if the observed CCF must also be floored at zero for alignment with the LRA CCF for: 

1. testing the relationship between CCF and macroeconomic variables and/or
2. for quantification of the downturn impact. 

Specifically, we propose that the EBA clarify that observed CCFs should not be floored for the purposes of testing the relationship between CCFs and macroeconomic factors. Furthermore, we recommend that the relevant downturn impact be assessed by comparing unfloored downturn CCFs with LRA CCFs (which are floored). The rationale for using unfloored downturn CCFs is that applying a floor penalizes banks for implementing risk management practices aimed at reducing or limiting spending on revolving credit—particularly during economic downturns, when such practices are most critical. Effective credit risk management can influence customer behaviour, potentially leading to reduced utilization of available credit limits. This may result in lower exposure levels and, in some cases, negative CCFs. The alternate option of applying a floor to downturn CCFs would inadvertently penalize banks for demonstrating the effectiveness of their risk management capabilities. This issue has been a point of contention in recent internal model inspections, and we therefore request clarification from the EBA on this matter.

We propose that it be confirmed that the annual-average observed CCFs calculated for the purpose of the reference value specified in par. 162 of the CP, be calculated without applying zero-flooring (so that the actual observed CCFs are considered) since the CP is silent on this detail.

37. Question 37: The possibility to have no downturn effect on CCF estimates is restricted to the case where observations are available during a downturn period. Which alternative meth-odologies could be used to prove the non-existence of a downturn effect on CCF estimates, in the case where no observation is available during a downturn period?

The non-existence of a downturn effect on CCFs can be substantiated with a statistical analysis of relevant macro-economic variables and the observed CCFs (during a sufficiently long period for which CCF observations are available) for the segment under consideration. This analysis can be used as follows:

1. Where a statistically significant relationship cannot be found, this implies that the CCFs (for the segment under consideration) are not linked to the macro-economic cycle, and therefore a downturn effect is not relevant. This conclusion (which is determined over a sufficiently long period where CCF observations are available and is therefore representative of an economic cycle) then also applies to earlier periods where no CCF observations are available.
2. Where a statistically significant relationship is found, the CCFs can be inferred for the period where no observations are available (using extrapolation based on the relationship between observed CCFs and macroeconomic variables MEVs). If the inferred CCFs are lower than the CCF LRA, it confirms that there is no downturn effect in the period where no CCF observations are available.

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