EBA欧洲银行-End-2016-G-SIB-assessment-instructions-2017-01-16_58页_832kb

Basel Committee on Banking Supervision: End-2016 G-SIB Assessment Exercise Summary

Core Content

The Basel Committee on Banking Supervision (BCBS) initiated a data collection exercise to assess the systemic importance of global systemically important banks (G-SIBs). This exercise serves as input into the methodology for identifying G-SIBs, which was outlined in the July 2013 document "Global systemically important banks: updated assessment methodology and the higher loss absorbency requirement." The methodology is under the supervision of the Financial Stability Board and aims to provide a comprehensive and robust assessment of systemic importance using both quantitative and qualitative indicators.

The data collection is mandatory for banks with a leverage ratio exposure measure exceeding 200 billion euros, and for those below the threshold but classified as G-SIBs in the previous year. The data must be publicly disclosed within four months of the financial year-end or by July of the relevant calendar year if it is the first year of inclusion.

Main Points

• Data Collection Purpose: To assess the systemic importance of banks globally using a combination of quantitative and qualitative indicators.
• Participation: While participation is voluntary in some jurisdictions, the BCBS expects a high level of participation to ensure the robustness of the results.
• Disclosure Requirement: Banks exceeding the 200 billion euro threshold must publicly disclose 12 indicators. Newly added G-SIBs must also comply with this requirement.
• Confidentiality: Raw data is treated as confidential and shared only with a small working group of the Macroprudential Supervision Group. Publicly disclosed data may be shared more widely.
• Reporting Format: The data must be submitted using an official Excel template, with specific rules on data entry, validation, and formatting.

Key Information

Reporting Rules and Standards

• Consolidation: All offices within the consolidated reporting group must be reported on a consolidated basis, with line-by-line consolidation unless otherwise specified.
• Data Quality: Banks are expected to ensure the highest quality of data for all indicators, with internal validation processes. Memorandum items may be reported on a best-efforts basis.
• Currency and Units: The reporting currency is determined by the relevant supervisory authority and should remain consistent across exercises. The unit (1, 1,000, or 1,000,000) must be the same for all data entries.
• Data Entry Guidelines:
  • Yellow cells are mandatory.
  • Green cells are for best-efforts or optional comments.
  • Red cells are completed by supervisory authorities.
  • No text (e.g., "n/a") should be entered into data cells; explanations should go into the comments column.
  • Zero values must be confirmed in the remarks column, otherwise the checks column will flag the entry.
  • Negative values are only allowed for specific items such as regulatory adjustments, net revenue, and certain liability-related items.

Changes from the End-2015 Exercise

• Updated Items:
  • Intra-Financial System Assets (Section 3) and Intra-Financial System Liabilities (Section 4) have been updated to reflect the revised definition of Securities Financing Transactions (SFTs).
• Added Items:
  • Size Items (Section 16): Investment value and guarantee value for unit-linked products.
  • Interconnectedness Items (Section 17): Holdings of securities issued by other financial institutions.
  • Substitutability/Financial Infrastructure Items (Section 18): Trading volumes of various securities and intragroup transactions.
  • Complexity Items (Section 19): Trading and available-for-sale securities, Level 1 and 2 assets, and Level 3 assets.
  • Cross-Jurisdictional Activity Items (Section 20): Cross-jurisdictional claims and liabilities, including derivatives.
  • Ancillary Items (Section 22): Net revenue and number of jurisdictions considering the Euro Area and European Union as single jurisdictions.
• Removed Items:
  • Section 17 (Interconnectedness) has had several items removed, including book value of equities with no market price, mutual bank certificates, minority interest, and standby letters of credit.

Data Worksheet Structure

• General Bank Data: Includes general information such as reporting unit, accounting standard, date of public disclosure, language of disclosure, and web address.
• Size Indicator: Measures total exposures, including derivatives, SFTs, and other assets, based on the Basel III leverage ratio definition.
• Interconnectedness Indicators: Focus on the exposure of banks to other financial institutions, including SFTs and securities holdings.
• Substitutability/Financial Infrastructure Indicators: Cover trading activity, intragroup transactions, and the role of banks in financial infrastructure.
• Complexity Indicators: Include notional amounts of OTC derivatives, trading volumes, and asset classifications based on risk levels.
• Cross-Jurisdictional Activity Indicators: Measure claims and liabilities across different jurisdictions, with specific emphasis on the Euro Area and European Union.
• Ancillary Indicators: Provide additional data on revenue and jurisdictional scope.
• Memorandum Items: These are not used in the calculation of systemic importance but are included for reference and may be reported on a best-efforts basis.
• Automated Checks: The template includes built-in checks to validate data consistency, ensuring accuracy and reliability. These checks highlight issues such as negative values, text entries, missing data, and logical inconsistencies.

Conclusion

The end-2016 G-SIB assessment exercise is a critical part of the global banking supervisory framework, aimed at identifying and monitoring banks that are systemically important. The exercise requires precise and consistent data reporting, with strict guidelines on data entry, validation, and disclosure. The changes from the previous year reflect an ongoing effort to refine the assessment methodology and ensure it remains relevant and effective in capturing the complexity and interconnectedness of global banking systems.