Response to discussion on the review of the NPL transaction data templates
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We have reviewed the proposed data structure and the relationship between the templates, and it seems comprehensible to us. We have no comments.
We are of the opinion that a separate data category (for swap) is not necessarily required. It would be quite rare for us to come across swap agreements. However, the difference needs to be incorporated in the data dictionary.
If we are pricing separate segments in a portfolio, we need to know what these segments are. For us to be able to identify them, the identifier needs to be included somewhere.
Not all relevant information has been captured. In general, counterparty information, quality and integrity are very important for the buy-side. Poor data quality on counterparty information will significantly reduce the economic value of claims, given that claims will be more difficult to recover.
A key stage of valuation and financial due diligence is to validate the availability, the quality, and the integrity of counterparty data. The inability to validate data will require risk mitigation through amongst others pricing reductions and through relevant representations and warranties from a seller.
It is also important for the buy-side to know whether an institution is selling all their claims against an individual, or only specific liabilities. For secured portfolios, it is critical to receive information related to any cross-collateralization, as this would limit the scope for recovery if such were to exist.
i. Name of Counterparty: Critical in some countries, since it is used to properly identify the counterparty when this cannot be done through a Personal Identity Number.
ii. Number of Joint Counterparties: It is useful to know whether there is more than one counterparty, as this impacts our ability to recover the claim.
iii. Date of Birth: This information is critical to understand where in the lifecycle the debtor is, and to evaluate the long-term possibility for economic recovery and debt settlement.
iv. Personal Identity Number: With an ID number we can check our own database whether we know the debtor, debt exposure with us, and whether the debtor is paying or not, all of which reduce the uncertainty on the part of the purchaser. The preferred form of ID would be the relevant Social Security Number within the specific jurisdiction.
v. Nationality of Counterparty: This is needed to identify if the debtor is a domestic citizen. This has an economic impact on the value of the claim.
vi. Address of Residence: This is an important data field to establish if the address of residence is known. In some jurisdictions, it is challenging to obtain contact information through national registries, and this will give us an indication of the quality of debtor data in the portfolio.
vii. City of Residence: Required to properly identify the Address of Residence.
viii. Geographic Region of Residence: Useful to properly identify the City of Residence.
ix. Registration number: We need to identify the debtor. In most jurisdictions, this information will enable us to obtain additional information on the corporate borrower.
x. Date of Last Contact: useful to establish timing since recoveries. This has an economic impact on the value of the claim.
xi. Counterparty deceased: This is very important since it has a major impact on the value of a claim. In some jurisdictions, the value of claims from deceased individuals is normally zero (0), whereas in other jurisdictions where heirs inherit assets as well as the deceased debts, the vendor may sell these claims as a separate portfolio/subsegment as part of a transaction.
This field could be replaced with the Date of Deceased as it offers a more relevant picture for valuation purposes.
xii. Number of Current Judgements: This is useful as it indicates any indebtedness level of the counterparty, and it impacts the economic value of the claim. This field could be replaced with the Value of the Current Judgements as it offers a more accurate picture on the level of indebtedness.
xiii. Counterparty Status and Date into Specific Status: Internal classification of counterparty at data cut-off (such as for example: Bankrupt, Forbearance, Overseas, Deceased, Fraud, Prison, etc.) and the date the debtor moved into that specific status.
Vendors use this counterparty status as a basis for segmenting and selling assets (not all, but some do). This would give the buyer the most up to date counterparty status and the timing element on the customer within that specific status.
The “Deposit”-related fields (lines 51 to 53) appear unnecessary to us in the context of an NPL portfolio.
As a rule, deposits are already taken into consideration by the vendor prior to default or termination.
Even though the latest financial statements of corporate debtors may not be entirely up-to-date or less reliant considering the circumstances, they are nevertheless relevant in terms of sketching a broader picture. This data is important for the valuation context in that it gives us an idea of the wider context, size of the business, (historical) performance, number of employees, and general prior situation of the business pre-default.
As already touched upon in Question 6 above, much of this information is presumably only a snapshot of the corporate’s entities’ situation and therefore not always as pertinent in a post-default scenario. In that aspect, this information is unlikely to give us substantial comfort to rely upon. However, this data is nevertheless very relevant from a valuation perspective and to establish a more thorough understanding of the business.
We believe not all the relevant information was captured in the list of data fields on financial instrument needed for NPL valuation and financial due diligence such as:
i. Country of Origination: it is important to know where the product is originated, in particular if it is not the home country.
ii. Product Type: This is a critical field for valuation purposes, particularly for unsecured portfolios where we observe different recovery behavior patterns based on product type.
Product type therefore has a significant impact on the economic value of a portfolio and our ability to select and fit appropriate benchmarks. Furthermore, different regulations apply to different product types, in particular calculation of interest and fees. These parameters will need to be considered as part of the valuation process.
We also note that there is no data consideration for ‘Overdrafts’ or other types of unsecured products lending institutions may offer, other than ‘Credit Cards’ or ‘Consumer loans’.
iii. Original Maturity Date: product history gives an indication on the likelihood of recovery.
iv. Origination amount: idem as point iii.
v. Accrued Interest Balance (On book): Critical.
Legally, different rules often apply for interest and fees.
vi. Other Balances: Critical. Idem as point v.
vii. Original Interest Rate: Critical.
This is required for legal proceedings in some jurisdictions.
viii. Original Interest Rate Type: in some jurisdictions it is a legal requirement to know the interest rate type.
ix. Original Interest Base Rate: in some jurisdictions this is a legal requirement.
x. Original Interest Margin: in some jurisdictions this is a legal requirement.
xi. Past-Due Principal Amount: Critical.
xii. Past-Due Interest Amount: Critical.
xiii. Other Past-Due Amounts: Critical
xiv. Capitalised Past-Due Amount: Critical
xv. Date of Statue of Limitation: does not figure on the original data templates nor the revised template and should be added since this is critical in order to ascertain the residual time left to pursue legal recoveries.
This information significantly impacts the economic value of a portfolio. Furthermore, debt collectors would be breaching local laws and regulations if they are pursuing debtors beyond the ‘legal expiration date’.
xvi. Balance at Default and Charge-Off date: these fields should be re-classified as critical since these are critical parameters for valuation purposes.
Particularly in the unsecured class of assets we rely on these data fields and this information to run statistical models to determine the value of portfolios.
We think the following fields are not likely to be relevant/needed, particularly for unsecured assets:
3.47 – Syndicated Loan
3.48 – Syndicated Portion
3.49 – Securitised
3.57 – Subsidy
3.58 – Subsidy Provider
3.59 – Subsidy Amount
As a rule, the less information provided, the lower the price offered. Since risks and uncertainties require to be mitigated, and pricing is one of the main mitigating tools.
As such, it is critical that we receive as much information on existing collaterals as possible, including for example registration numbers, original year of registration, size (m2), use of collaterals (particularly property related), original valuations including dates and subsequent valuations, a history with dates and outcomes from previous/planned future Auctions, and the current running costs (Opex and Overheads) since all of this provides background information and puts context to the potential economic value of such collaterals.
Therefore, any fields pertaining to property collaterals original and current valuation should not be deleted or reclassified as non-critical, since they are critical to valuations, both in terms of the upside- as well as the down-side risks.
As a rule, non-property collateral is something we tend to not take into account. (Except perhaps in exceptional individual cases, but in such instances data fields or requirements relating to any non-property collateral would be negotiated in a tailor-made approach).
Our position is that, in general, all information regarding enforcement should be provided if such information is available.
However, fields relating to Date of Default, Default balance and Charge-Off Date need further clarification as those descriptions as they currently stand are open to interpretation.
Default Balance: specifically references to Art. 178 of CRR, yet neither Default Date nor Charge-off Date make similar references to article. Default Date or Charge-off Date (sometimes used interchangeably) normally reference to the date or event where the normal existing relationship terminates and all contractual monies becomes due and payable (‘overdue and future’, re: Art.178 of CRR) by the debtor.
Default/Charge-off dates: (including Original Defaulted balance) are key to classifying NPL portfolios and therefore critical to both valuation as well as our ability to legally collect.
These are furthermore normally static fields (except where corrections may be made), rather than dynamic fields. A counterparty may have multiple defaulted dates of individual payments, which he may recover from and therefore in this sense it is a dynamic field. However, when the existing relationship is terminated, the debtor is issued with a default/termination notice and balance, subsequently defaulted/terminated and formally reported to national banks or external credit reference agencies (depending on the materiality of the defaulted balance).
The process of termination of an account is a significant event in the credit lifecycle and requires institutions to follow and evidence the correct terminating process, and therefore cannot be anything else but critical for valuation purposes of NPLs.
However, it is also recognized that post-default/termination a debtor can make payments towards their debt, which would reduce the amount owed under the default terms. In this respect the defaulted balance and still outstanding amount becomes dynamic, but the actual default/termination date and balance remains static. So, we may need both sets of information: both at the termination point (formal default – remains static) and subsequent data points when there are changes on the debtor circumstances (dynamic).
Except for those points and comments already highlighted above.
However, all transactions, and therefore subsequently all the data pertaining to that transaction that is shared between seller and buyer, are per standard and market practice always subject to non-disclosure agreements (NDA) and data processing agreements (DPA), which are enforced internally by B2Holding. The practice of signing NDAs and DPAs reduces the need to withhold critical information.
Since transactions and subsequent data exchange are always subject to enforced confidentiality and personal data obligations, this furthermore means that regardless of any possible confidentiality aspects of certain data fields these two issues are per large addressed. Regardless of the confidentiality aspect of a data field, it is our opinion that the market will continue to use these instruments (NDA/DPA).
Except for those already highlighted in the section above.
Most if not all transactions (unless the portfolio is deemed insignificant to the buyer) require, according to us, a full set of data.
For the buyer, the size of the institution of the portfolio does not come into play when it comes to the data/information the buyer needs. In this respect, parties could, depending on the size of the portfolio or the significance from their point of view, agree to or waive certain data fields – upon agreement.
However, most if not all transactions (unless the portfolio is deemed insignificant to the buyer) require, according to us, a full set of data.
Any threshold in applying the proportionality principle will in practice also depend on the size or experience level of the buyer or the seller.
Taking this into account we think it would not be possible nor practical to have a threshold in a “size that fits all”.
Applying a threshold would furthermore impact the negotiation position of a party (most probably the buyer) who in case of a portfolio below the threshold would face difficulties negotiating full data fields or better data quality.
i. Current Accounts (Overdrafts): information related to whether there are/were overdrafts, which limits apply, whether there was delinquency on the current accounts, interest rates and fees applicable and whether the current accounts in question are primary accounts or secondary accounts.
ii. Credit cards: information related to what the original limits were, current limits, date last credit limit was changed, minimum payment terms, etc.
iii. Unsecured tails outstanding from original secured products.
iv. Any potential other products that are offered by banks or that are traded within the industry.
The structure and coverage of the templates may provide some guidance in this regard, but the final data requirements and sharing are tailor made in such instances.
For transactions where a portfolio is traded, we feel the structure and the coverage of the templates are a good start and basis and are certainly needed for the industry. However, they need further consideration (and some tweaks in terms of structure transparency and user-friendliness) and additional consultation, in particular from the side of debt purchasers.
However, the structure and coverage of data templates and the quality of transferred data has a significantly higher impact (i.e., valuation or expected performance of recovery) on buyers than on sellers. Along with some of our competitors, B2Holding supports the initiative to create a commonly recognized standard. Not only in the interest of all the market actors by ensuring a more efficient and harmonized process, but also to ensure a certain balance between the different market participants. As a debt purchaser, we find ourselves more than often in a situation where we are faced with sellers who are considerably larger in terms of organization and negotiation weight. This not only goes for B2Holding, but also for most of our competitors. Most banks are significantly larger than even the largest debt collectors. We therefore find ourselves often in a position whereby we as buyer, and thus the party requiring/benefiting the most of a detailed as complete as possible set of data are dramatically outweighed by the selling party, who has a set interest in keeping the dataset as limited as possible. A balanced and agreed upon uniform practice/standard would surely benefit the market.
Additionally, we believe that a more balanced debt sale market not only benefits the parties on the sell-side and the buy-side of the market, but at the end of the day also the debtors themselves. The availability of more data or more standardised NPL transaction data practices lead to a more transparent market, which in turn ultimately supports better collection practices and ultimately leads to better consumer protection.
2. We also note that there is a much wider product range on the market being traded in the industry beyond what is purely banking or usually in scope of the banking field. (e.g., consumer debt in telco, utilities, or general retail, closely related or in essence qualifiable as credit/lending)
3. We have furthermore noticed, along with some of our competitors, that quite a few of the data fields that have been suggested to be deleted are critical to portfolio valuations. Examples such as: deceased status, age of debtor, financial instrument information and collateral valuations. Given that the data templates support NPL transactions and the equilibrium in negotiation power, the fields pertaining to default or terminating of accounts should be nothing else but critical fields populated across all asset classes. The same goes for the statute barring date, which represents the expiry of legal ability to collect, and which should be included as critical. It has furthermore not featured anywhere on previous or current data templates. Including the above promotes good collection practices amongst the industry.
There is a potential fall back to negotiated covenants when it comes to these critical data fields that have not been incorporated in the templates, nevertheless we strongly urge EBA to reconsider the inclusion of these data fields. The data templates, as a common standard, should comprise of all required information and not rely on the notion that the information would be covered elsewhere.
1. Do you agree with the proposed data structure and the relationship between templates? If not, please provide explanation.
Yes.We have reviewed the proposed data structure and the relationship between the templates, and it seems comprehensible to us. We have no comments.
2. Do you agree with the deletion of data categories ‘NPL portfolio’ and ‘Swap’? If not, please provide explanation.
Yes.We are of the opinion that a separate data category (for swap) is not necessarily required. It would be quite rare for us to come across swap agreements. However, the difference needs to be incorporated in the data dictionary.
If we are pricing separate segments in a portfolio, we need to know what these segments are. For us to be able to identify them, the identifier needs to be included somewhere.
3. Do you think the suggested list of data fields capture all the relevant information on the counterparty needed for NPL valuation and financial due diligence? If not, please indicate which other data fields should be included and provide explanation for this.
No.Not all relevant information has been captured. In general, counterparty information, quality and integrity are very important for the buy-side. Poor data quality on counterparty information will significantly reduce the economic value of claims, given that claims will be more difficult to recover.
A key stage of valuation and financial due diligence is to validate the availability, the quality, and the integrity of counterparty data. The inability to validate data will require risk mitigation through amongst others pricing reductions and through relevant representations and warranties from a seller.
It is also important for the buy-side to know whether an institution is selling all their claims against an individual, or only specific liabilities. For secured portfolios, it is critical to receive information related to any cross-collateralization, as this would limit the scope for recovery if such were to exist.
i. Name of Counterparty: Critical in some countries, since it is used to properly identify the counterparty when this cannot be done through a Personal Identity Number.
ii. Number of Joint Counterparties: It is useful to know whether there is more than one counterparty, as this impacts our ability to recover the claim.
iii. Date of Birth: This information is critical to understand where in the lifecycle the debtor is, and to evaluate the long-term possibility for economic recovery and debt settlement.
iv. Personal Identity Number: With an ID number we can check our own database whether we know the debtor, debt exposure with us, and whether the debtor is paying or not, all of which reduce the uncertainty on the part of the purchaser. The preferred form of ID would be the relevant Social Security Number within the specific jurisdiction.
v. Nationality of Counterparty: This is needed to identify if the debtor is a domestic citizen. This has an economic impact on the value of the claim.
vi. Address of Residence: This is an important data field to establish if the address of residence is known. In some jurisdictions, it is challenging to obtain contact information through national registries, and this will give us an indication of the quality of debtor data in the portfolio.
vii. City of Residence: Required to properly identify the Address of Residence.
viii. Geographic Region of Residence: Useful to properly identify the City of Residence.
ix. Registration number: We need to identify the debtor. In most jurisdictions, this information will enable us to obtain additional information on the corporate borrower.
x. Date of Last Contact: useful to establish timing since recoveries. This has an economic impact on the value of the claim.
xi. Counterparty deceased: This is very important since it has a major impact on the value of a claim. In some jurisdictions, the value of claims from deceased individuals is normally zero (0), whereas in other jurisdictions where heirs inherit assets as well as the deceased debts, the vendor may sell these claims as a separate portfolio/subsegment as part of a transaction.
This field could be replaced with the Date of Deceased as it offers a more relevant picture for valuation purposes.
xii. Number of Current Judgements: This is useful as it indicates any indebtedness level of the counterparty, and it impacts the economic value of the claim. This field could be replaced with the Value of the Current Judgements as it offers a more accurate picture on the level of indebtedness.
xiii. Counterparty Status and Date into Specific Status: Internal classification of counterparty at data cut-off (such as for example: Bankrupt, Forbearance, Overseas, Deceased, Fraud, Prison, etc.) and the date the debtor moved into that specific status.
Vendors use this counterparty status as a basis for segmenting and selling assets (not all, but some do). This would give the buyer the most up to date counterparty status and the timing element on the customer within that specific status.
4. Do you think any specific data fields should be excluded from the template? If yes, please specify the data fields and give explanation to your answer.
Yes.The “Deposit”-related fields (lines 51 to 53) appear unnecessary to us in the context of an NPL portfolio.
As a rule, deposits are already taken into consideration by the vendor prior to default or termination.
5. Do you agree that data fields on current external and internal credit scores and current external and internal credit scores at origination should be included in the template (for both private individual and corporate counterparties)?
Yes6. Do you agree that data fields on corporate’s latest available financial statement amounts should be included in the template?
Yes.Even though the latest financial statements of corporate debtors may not be entirely up-to-date or less reliant considering the circumstances, they are nevertheless relevant in terms of sketching a broader picture. This data is important for the valuation context in that it gives us an idea of the wider context, size of the business, (historical) performance, number of employees, and general prior situation of the business pre-default.
7. Do you agree that data fields related to corporate counterparties’ assets and liabilities, market capitalisation should be included in the template?
Yes.As already touched upon in Question 6 above, much of this information is presumably only a snapshot of the corporate’s entities’ situation and therefore not always as pertinent in a post-default scenario. In that aspect, this information is unlikely to give us substantial comfort to rely upon. However, this data is nevertheless very relevant from a valuation perspective and to establish a more thorough understanding of the business.
8. Do you agree with the proposed Template 2 of Annex I? If not, please provide explanation to your answer.
Yes.9. Do you agree with the inclusion of the data fields related to interest rates and other information as per contractual agreement for the valuation and financial due diligence of NPLs, especially when they are not more than 90 days past due? Please provide data field-specific explanation to your answer.
Yes.10. Do you agree with the inclusion of the data fields related to forbearance measures for the valuation and financial due diligence of NPLs?
Yes.11. Do you think the suggested list of data fields capture all relevant information on financial instrument needed for NPL valuation and financial due diligence? If not, please indicate which other data fields should be included and provide explanation for this.
No.We believe not all the relevant information was captured in the list of data fields on financial instrument needed for NPL valuation and financial due diligence such as:
i. Country of Origination: it is important to know where the product is originated, in particular if it is not the home country.
ii. Product Type: This is a critical field for valuation purposes, particularly for unsecured portfolios where we observe different recovery behavior patterns based on product type.
Product type therefore has a significant impact on the economic value of a portfolio and our ability to select and fit appropriate benchmarks. Furthermore, different regulations apply to different product types, in particular calculation of interest and fees. These parameters will need to be considered as part of the valuation process.
We also note that there is no data consideration for ‘Overdrafts’ or other types of unsecured products lending institutions may offer, other than ‘Credit Cards’ or ‘Consumer loans’.
iii. Original Maturity Date: product history gives an indication on the likelihood of recovery.
iv. Origination amount: idem as point iii.
v. Accrued Interest Balance (On book): Critical.
Legally, different rules often apply for interest and fees.
vi. Other Balances: Critical. Idem as point v.
vii. Original Interest Rate: Critical.
This is required for legal proceedings in some jurisdictions.
viii. Original Interest Rate Type: in some jurisdictions it is a legal requirement to know the interest rate type.
ix. Original Interest Base Rate: in some jurisdictions this is a legal requirement.
x. Original Interest Margin: in some jurisdictions this is a legal requirement.
xi. Past-Due Principal Amount: Critical.
xii. Past-Due Interest Amount: Critical.
xiii. Other Past-Due Amounts: Critical
xiv. Capitalised Past-Due Amount: Critical
xv. Date of Statue of Limitation: does not figure on the original data templates nor the revised template and should be added since this is critical in order to ascertain the residual time left to pursue legal recoveries.
This information significantly impacts the economic value of a portfolio. Furthermore, debt collectors would be breaching local laws and regulations if they are pursuing debtors beyond the ‘legal expiration date’.
xvi. Balance at Default and Charge-Off date: these fields should be re-classified as critical since these are critical parameters for valuation purposes.
Particularly in the unsecured class of assets we rely on these data fields and this information to run statistical models to determine the value of portfolios.
12. Do you think any specific data fields should be excluded from the template? If yes, please specify the data fields and give explanation to your answer.
Yes.We think the following fields are not likely to be relevant/needed, particularly for unsecured assets:
3.47 – Syndicated Loan
3.48 – Syndicated Portion
3.49 – Securitised
3.57 – Subsidy
3.58 – Subsidy Provider
3.59 – Subsidy Amount
13. Do you agree with the data fields related to lease? Please provide data field-specific explanation to your answer.
We have no specific objections or comments to the data fields related to lease. In general, we very rarely come across leasing-related portfolios.14. Do you think the suggested list of data fields capture all relevant information on collateral needed for NPL valuation and financial due diligence? If not, please indicate which other data fields should be included and provide explanation for this.
Secured NPL transactions normally require longer time frames for valuation and financial due diligence, together with larger amounts of investment in terms of Capex to be expected. Both in terms of transaction value offered to vendors, as well as internal and external resource costs involved to actively participate on such processes.As a rule, the less information provided, the lower the price offered. Since risks and uncertainties require to be mitigated, and pricing is one of the main mitigating tools.
As such, it is critical that we receive as much information on existing collaterals as possible, including for example registration numbers, original year of registration, size (m2), use of collaterals (particularly property related), original valuations including dates and subsequent valuations, a history with dates and outcomes from previous/planned future Auctions, and the current running costs (Opex and Overheads) since all of this provides background information and puts context to the potential economic value of such collaterals.
Therefore, any fields pertaining to property collaterals original and current valuation should not be deleted or reclassified as non-critical, since they are critical to valuations, both in terms of the upside- as well as the down-side risks.
15. Do you think any specific data fields should be excluded from the template? If yes, please specify the data fields and give explanation to your answer.
No further specific comments on data field exclusions other than those already highlighted and commented in Question 14 above.16. Do you agree with the data fields on the characteristics of non-property collateral? Please provide data field-specific explanation to your answer.
No specific comments on the data fields on the characteristics of non-property collateral.As a rule, non-property collateral is something we tend to not take into account. (Except perhaps in exceptional individual cases, but in such instances data fields or requirements relating to any non-property collateral would be negotiated in a tailor-made approach).
17. Do you agree with the data fields related to the enforcement of collateral? Please provide data field-specific explanation to your answer.
Yes.Our position is that, in general, all information regarding enforcement should be provided if such information is available.
18. Do you agree with the proposed Template 5 of Annex I for NPL valuation and financial due diligence? Please provide data field-specific explanation to your answer.
Yes.19. Do you agree with description of data fields presented in data dictionary?
In general, yes.However, fields relating to Date of Default, Default balance and Charge-Off Date need further clarification as those descriptions as they currently stand are open to interpretation.
Default Balance: specifically references to Art. 178 of CRR, yet neither Default Date nor Charge-off Date make similar references to article. Default Date or Charge-off Date (sometimes used interchangeably) normally reference to the date or event where the normal existing relationship terminates and all contractual monies becomes due and payable (‘overdue and future’, re: Art.178 of CRR) by the debtor.
Default/Charge-off dates: (including Original Defaulted balance) are key to classifying NPL portfolios and therefore critical to both valuation as well as our ability to legally collect.
These are furthermore normally static fields (except where corrections may be made), rather than dynamic fields. A counterparty may have multiple defaulted dates of individual payments, which he may recover from and therefore in this sense it is a dynamic field. However, when the existing relationship is terminated, the debtor is issued with a default/termination notice and balance, subsequently defaulted/terminated and formally reported to national banks or external credit reference agencies (depending on the materiality of the defaulted balance).
The process of termination of an account is a significant event in the credit lifecycle and requires institutions to follow and evidence the correct terminating process, and therefore cannot be anything else but critical for valuation purposes of NPLs.
However, it is also recognized that post-default/termination a debtor can make payments towards their debt, which would reduce the amount owed under the default terms. In this respect the defaulted balance and still outstanding amount becomes dynamic, but the actual default/termination date and balance remains static. So, we may need both sets of information: both at the termination point (formal default – remains static) and subsequent data points when there are changes on the debtor circumstances (dynamic).
20. Do you agree with criticality (and non-criticality) of data fields presented in data dictionary? If not, please provide suggestions and explanations related to specific data fields.
In general, yes.Except for those points and comments already highlighted above.
21. Do you agree with confidentiality aspects of data fields? If not, please provide explanation.
Yes.However, all transactions, and therefore subsequently all the data pertaining to that transaction that is shared between seller and buyer, are per standard and market practice always subject to non-disclosure agreements (NDA) and data processing agreements (DPA), which are enforced internally by B2Holding. The practice of signing NDAs and DPAs reduces the need to withhold critical information.
Since transactions and subsequent data exchange are always subject to enforced confidentiality and personal data obligations, this furthermore means that regardless of any possible confidentiality aspects of certain data fields these two issues are per large addressed. Regardless of the confidentiality aspect of a data field, it is our opinion that the market will continue to use these instruments (NDA/DPA).
22. Do you agree with excluding no data options for data fields? If not, please provide suggestions and explanations related to specific data fields.
In general, yes.Except for those already highlighted in the section above.
23. Please provide your views on how proportionality considerations regarding the size of the exposures or portfolios being sold should be incorporated in the implementation of NPL data templates.
In our opinion the size of the portfolio should not or only minimally impact the need for information in respect of the portfolio.Most if not all transactions (unless the portfolio is deemed insignificant to the buyer) require, according to us, a full set of data.
For the buyer, the size of the institution of the portfolio does not come into play when it comes to the data/information the buyer needs. In this respect, parties could, depending on the size of the portfolio or the significance from their point of view, agree to or waive certain data fields – upon agreement.
However, most if not all transactions (unless the portfolio is deemed insignificant to the buyer) require, according to us, a full set of data.
24. Should there be a threshold (e.g. in monetary terms) for the application of the proportionality principle? If yes, then how should this be defined?
Given that we disagree with the relevance of proportionality and the idea that it should impact the data quality or amount of data, we also disagree with the notion of having a threshold.Any threshold in applying the proportionality principle will in practice also depend on the size or experience level of the buyer or the seller.
Taking this into account we think it would not be possible nor practical to have a threshold in a “size that fits all”.
Applying a threshold would furthermore impact the negotiation position of a party (most probably the buyer) who in case of a portfolio below the threshold would face difficulties negotiating full data fields or better data quality.
25. Do you agree that the proposed approach takes into account, in an adequate way, the proportionality principle? If not, which additional elements should be considered?
As a rule, we don’t particularly agree with the principle of proportionality, subject to the rationale in Question 23 and 24.26. Please provide your views on the asset classes covered and whether any specific data fields, other than already foreseen, should be included in the templates for ensure full coverage of certain asset classes.
We believe the Asset classes are correct, but that there are certain product types addressed which are incomplete. Some of the information regarding the product types that is lacking for instance:i. Current Accounts (Overdrafts): information related to whether there are/were overdrafts, which limits apply, whether there was delinquency on the current accounts, interest rates and fees applicable and whether the current accounts in question are primary accounts or secondary accounts.
ii. Credit cards: information related to what the original limits were, current limits, date last credit limit was changed, minimum payment terms, etc.
iii. Unsecured tails outstanding from original secured products.
iv. Any potential other products that are offered by banks or that are traded within the industry.
27. In your view, is the structure and coverage of the templates adequate for both portfolio transactions and transactions where an individual exposure is traded? Please explain your answer.
In our experience, transactions where an individual exposure is traded are usually subject to bespoke data requirements that are agreed upon between the relevant seller and buyer.The structure and coverage of the templates may provide some guidance in this regard, but the final data requirements and sharing are tailor made in such instances.
For transactions where a portfolio is traded, we feel the structure and the coverage of the templates are a good start and basis and are certainly needed for the industry. However, they need further consideration (and some tweaks in terms of structure transparency and user-friendliness) and additional consultation, in particular from the side of debt purchasers.
28. Please add any additional comments, remarks or observations you may wish to include in your feedback to the discussion paper.
1. We note that there is less input from the debt buy-side industry than there is from financial institutions and banks (essentially sell-side).However, the structure and coverage of data templates and the quality of transferred data has a significantly higher impact (i.e., valuation or expected performance of recovery) on buyers than on sellers. Along with some of our competitors, B2Holding supports the initiative to create a commonly recognized standard. Not only in the interest of all the market actors by ensuring a more efficient and harmonized process, but also to ensure a certain balance between the different market participants. As a debt purchaser, we find ourselves more than often in a situation where we are faced with sellers who are considerably larger in terms of organization and negotiation weight. This not only goes for B2Holding, but also for most of our competitors. Most banks are significantly larger than even the largest debt collectors. We therefore find ourselves often in a position whereby we as buyer, and thus the party requiring/benefiting the most of a detailed as complete as possible set of data are dramatically outweighed by the selling party, who has a set interest in keeping the dataset as limited as possible. A balanced and agreed upon uniform practice/standard would surely benefit the market.
Additionally, we believe that a more balanced debt sale market not only benefits the parties on the sell-side and the buy-side of the market, but at the end of the day also the debtors themselves. The availability of more data or more standardised NPL transaction data practices lead to a more transparent market, which in turn ultimately supports better collection practices and ultimately leads to better consumer protection.
2. We also note that there is a much wider product range on the market being traded in the industry beyond what is purely banking or usually in scope of the banking field. (e.g., consumer debt in telco, utilities, or general retail, closely related or in essence qualifiable as credit/lending)
3. We have furthermore noticed, along with some of our competitors, that quite a few of the data fields that have been suggested to be deleted are critical to portfolio valuations. Examples such as: deceased status, age of debtor, financial instrument information and collateral valuations. Given that the data templates support NPL transactions and the equilibrium in negotiation power, the fields pertaining to default or terminating of accounts should be nothing else but critical fields populated across all asset classes. The same goes for the statute barring date, which represents the expiry of legal ability to collect, and which should be included as critical. It has furthermore not featured anywhere on previous or current data templates. Including the above promotes good collection practices amongst the industry.
There is a potential fall back to negotiated covenants when it comes to these critical data fields that have not been incorporated in the templates, nevertheless we strongly urge EBA to reconsider the inclusion of these data fields. The data templates, as a common standard, should comprise of all required information and not rely on the notion that the information would be covered elsewhere.