2015年-ECB欧洲央行_Survey_of_national_practices_regarding_MFI_balance_sheet_statistics_286页_1mb

Summary of the Survey on National Practices Regarding MFI Balance Sheet Statistics

Core Content

This document presents a survey of national practices regarding the compilation of balance sheet items (BSI) statistics for monetary financial institutions (MFIs) in the euro area, conducted in November 2015. It provides an overview of how different countries collect, validate, and disseminate monetary data, as well as their accounting practices and methodological approaches.

Main Objectives

• Enhance transparency of BSI statistics
• Measure harmonisation across countries
• Develop a benchmark for assessing national practices in line with improved harmonisation

Key Findings

1. Legal and Institutional Framework

• The survey was based on Regulation ECB/2013/33 (BSI Regulation) and the ECB's Manual on MFI BSI Statistics (BSI Manual).
• Only one country (NL) reported that the BSI Regulation is the sole legal instrument for BSI reporting.
• Most countries use domestic legislation, typically a central bank law, to support data collection from MFIs.
• Some countries (AT, SI) use the BSI Regulation as the primary legal instrument and domestic legislation as supplementary.
• Specific legislation exists for Money Market Funds (MMFs) in some countries.

2. Data Collection and Dissemination

• Ten NCBs grant derogations to small MFIs under Article 9.1 of the BSI Regulation, reducing reporting requirements.
• These derogations mainly benefit credit unions and small commercial banks, and cover 18.3% of all MFIs in the euro area, but only 1.25% of total assets.
• Eight NCBs apply derogations to MFIs whose contribution to the national balance sheet is less than 5% in terms of stocks.
• Data collection is part of a broader set of data, with some countries collecting more detailed data than required by the BSI Regulation.

3. Accounting Practices

• The accounting framework is largely aligned with international standards, though still national in practice.
• Valuation and recording of financial instruments are central to the survey:
  • Loans and deposits are generally recorded at face value or amortised cost.
  • Debt securities are typically recorded at fair value or historical cost.
  • Shares and equities are reported at their nominal value.
  • Financial derivatives are subject to specific valuation rules, often based on fair value.
  • Foreign currency instruments are translated into euros using exchange rates.

4. Translation of Accounting Data into MFI Balance Sheet Data

• The timing of recording is a critical point of divergence, especially for loans.
• Repurchase agreements are reported either as deposits/loans or under remaining assets and liabilities, creating discrepancies.
• Securities are translated using specific methods, and financial derivatives require careful treatment to ensure consistency with BSI statistics.

5. Transactions, Revaluations, and Other Adjustments

• Securities revaluations and transactions are reported with varying methodologies.
• Loan write-offs/write-downs are handled differently across countries.
• Exchange rate adjustments are an important aspect of translating financial instruments into euros.

6. Compilation Approach for Securities

• A detailed approach is used for compiling securities data, including specific classifications and treatment of embedded derivatives.
• Some countries integrate securities data with supervisory data, increasing the level of detail.

7. Securitisation and Derecognition of Loans

• Securitisation is a key area of focus, with varying approaches to derecognition of loans.
• The treatment of securitised assets affects the classification of loans in the balance sheet.

8. Selected Issues on Financial Instruments

• Securities with embedded derivatives, convertible bonds, preference shares, and impaired securities are reported with varying degrees of detail.
• Deposits with embedded derivatives and special terms (e.g., freeze options) are also reported differently.
• Capital and reserves are reported with specific methodologies, depending on national practices.
• Remaining assets and liabilities are treated with different approaches, and transactions with central counterparties are reported in a variety of ways.

9. Linkages to Other Macroeconomic Datasets

• BSI statistics are integrated with other datasets, including economic research, interest rate statistics, balance of payments, and locational banking statistics.
• This integration helps improve the comprehensiveness and utility of the data for policy and analysis.

Structure of the MFI Sector

At the end of 2014, the euro area MFI sector (excluding NCBs) consisted of 6,416 institutions with total assets of €31,900 billion:

• 5,492 were credit institutions (CIs), of which 1,349 were commercial banks.
• 750 were money market funds (MMFs).
• 174 were other MFIs, including 25 electronic money institutions (EMIs).

Asset Distribution

• Credit institutions accounted for 96.7% of total assets, with €30,800 billion.
• MMFs contributed €930 billion, and other MFIs added €120 billion.
• Commercial banks represented 74.7% of total CI assets, with €22,734 billion.

Geographical Control

• 80.0% of MFIs and 81.5% of total assets were domestically controlled.
• 20.0% were domestically incorporated, foreign-controlled.
• Commercial banks had a more balanced control (48.6% domestic, 51.4% foreign), while savings banks, credit unions, and mortgage banks were mostly domestic.

Group Reporting

• Only two countries (CY and FR) indicated group reporting for credit unions.
• The combined number of groups was 3, with total assets of €947 billion.

Conclusion

The survey highlights the diversity in national practices and the need for further harmonisation in the euro area. While the BSI Regulation and BSI Manual provide a robust framework, differences in accounting standards, data collection, and reporting methodologies persist. These differences affect the comparability and transparency of BSI statistics, which is crucial for monetary policy and research. The results aim to improve data quality, reporting consistency, and understanding among stakeholders.