EBA欧洲银行-EBA-NPL-Transaction-Template-Instructions_final_175页_2mb

EBA NPL Transaction Templates Summary

Core Content

The European Banking Authority (EBA) has developed the EBA NPL Transaction Templates to support the financial due diligence (FDD) and valuation of Non-Performing Loans (NPLs) in the context of NPL transactions. These templates provide the most granular and extensive data fields compared to the EBA NPL Portfolio Screening Templates, which are used for initial market sounding exercises.

The templates aim to reduce information asymmetry between buyers and sellers of NPLs, helping to develop a functioning secondary market in the EU. They are based on existing regulations and standards such as the Capital Requirements Regulation (CRR), the Financial Reporting (FINREP), AnaCredit, and NACE and NUTS3 classifications.

Main Views

1. Purpose and Scope

• The EBA NPL templates are designed to provide standardized, comparable data for NPL transactions.
• They are intended for use by institutions and their counterparties in NPL transactions.
• The templates are not guaranteed to be complete, accurate, or timely, and users are responsible for legal, accounting, and tax obligations.

2. Template Components

• Instructions: Explain how to use the templates.
• Data Dictionary: Lists all data fields, including their category, description, and importance.
• Data Tape: The actual file to be filled in by the institution with relevant data.
• Validation Rules: Guide on how data points can be validated against each other.

3. Data Classification

• Data fields are classified based on criticality for FDD and valuation:
  • Critical: Essential for pricing models and binding offers.
  • Important: Likely to have a material impact on the transaction price.
  • Moderate: Adds value but not expected to significantly affect pricing.
• Data fields are also marked as static or dynamic based on whether they change with different Cut-Off Dates.
• Confidentiality indicators are provided, using color codes and numbers to identify fields subject to data protection or confidentiality rules.

4. Asset Class Breakdown

The templates categorize NPLs into the following asset classes:

• Residential Real Estate loans
• Commercial Real Estate loans
• SME / Corporate loans
• Unsecured Retail loans
• Leasing / Asset Backed Finance (ABF) loans
• Auto loans
• Specialised Loans

Each asset class has specific characteristics and definitions.

5. Country Specificity

• The templates include country-specific data fields for the 28 EU member states.
• These fields are marked in the Data Dictionary and are based on national restructuring and insolvency procedures.
• Country-specific data should not replace legal due diligence and must be confirmed by legal counsel.

Key Information

1. Data Fields and Their Types

• Data fields are grouped into categories such as Portfolio, Counterparty Group, Counterparty, Loan, Collateral, etc.
• Field types include:
  • Boolean (Yes/No)
  • Choice (from predefined lists)
  • Date (dd/mm/yyyy)
  • Number (with two decimal places)
  • Percentage (with two decimal places)
  • Text (free text)

2. Confidentiality and Data Protection

• Data fields are marked with confidentiality indicators:
  • Red '1': Confidential for all countries.
  • Orange '2': Confidential for some countries.
  • Blank: Not confidential.
• Users must ensure compliance with data protection laws, including the GDPR (Regulation (EU) 2016/679).

3. Special Notes

• The data tape is used only for Active Loans as of the Cut-Off Date.
• Users are encouraged to provide a full and complete data tape to optimize accuracy in FDD and valuation.
• Users must implement appropriate Non-Disclosure Agreements (NDAs) or Confidentiality Agreements (CAs) as needed.

4. Handling of Missing Data

• The following codes may be used for missing data:
  • ND1: Not collected as not required.
  • ND2: Collected but not loaded into the reporting system.
  • ND3: Collected but stored in a separate system.
  • ND4-YYYY-MM-DD: Collected but available from a specific date.
  • ND5: Not relevant.

5. Definitions and Standards

• The templates align with:
  • CRR and FINREP
  • AnaCredit
  • NACE and NUTS3 classifications
  • ISO codes (including ISO 3166 ALPHA-2 and ISO 20022)
• They also incorporate definitions from the World Health Organisation (WHO) and the International Standard Classification of Occupation (ISCO-08).

Structure and Flow

The data structure is outlined in Figure 1: DATA STRUCTURE, which illustrates the flow of data fields across different categories and levels of granularity.

The templates are intended to be used in conjunction with legal and regulatory frameworks and should be complemented by appropriate contractual arrangements to ensure data confidentiality and compliance.