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EBA Methodological Guide: Risk Indicators and Detailed Risk Analysis Tools (V1.1) Summary

Core Content

The European Banking Authority (EBA) has developed a Methodological Guide that outlines risk indicators (RIs) and detailed risk analysis tools (DRATs) to support micro-prudential analysis and risk monitoring in the EU banking sector. This guide aims to enhance transparency and consistency in the computation and interpretation of these indicators, which are used in EBA publications such as the EBA Risk Dashboard and Risk Assessment Report.

The guide is structured into two parts:

• Part I: Covers risk indicators by type of risk, including liquidity, funding, asset quality, profitability, concentration, solvency, operational, and market risk, as well as SME-specific indicators.
• Part II: Addresses methodological issues that may arise when compiling or using the risk indicators and DRATs.

Main Risk Indicator Categories

1. Liquidity Risk

• Definition: The risk of a firm being unable to meet its financial obligations without incurring unacceptable costs or losses.
• Key Indicators:
  • LIQ 1: Core funding ratio (% of total liabilities) – 'Turner ratio'
  • LIQ 17: Liquidity coverage ratio (%)
• DRATs:
  • DRAT 27: Liquid assets to items requiring stable funding ratio by currency
• Key Points:
  • Liquidity risk is a systemic risk, especially in the banking sector due to maturity transformation.
  • Indicators are based on COREP and FINREP templates.
  • Some indicators focus on currency-specific liquidity (e.g., LIQ 10), reflecting the non-fungibility of liquidity across currencies.

2. Funding Risk

• Definition: The risk of a firm not having access to sufficient funds to meet its obligations when they fall due.
• Key Indicators:
  • FND 1: Asset encumbrance to total assets
  • FND 17: Loan-to-deposit ratio
  • FND 18: Customer deposits to total liabilities
• DRATs:
  • DRAT 28: Term funding per currency
• Key Points:
  • Funding risk is closely linked to creditworthiness and funding profile.
  • Asset encumbrance plays a crucial role in assessing funding stress and transition to secured funding.
  • Indicators include geographical funding concentration, secured vs. unsecured funding, and evolution of balance sheet items.
  • Additional data like CDS spreads, repo rates, and capital market credit spreads can enrich the understanding of funding risk.

3. Asset Quality

• Definition: The risk related to the quality of a bank's assets, particularly in terms of non-performing exposures.
• Key Indicators:
  • AQT_1: Non-performing loans and debt securities net of impairments to prudential own funds
  • AQT_3.2: Non-performing loans and advances to total gross loans and advances (NPL ratio)
  • AQT_3.3: Non-performing debt securities to total gross debt securities (NPDS)
• DRATs:
  • DRATs are used to provide detailed analysis of asset quality, such as the coverage ratio for performing and non-performing assets.
• Key Points:
  • Asset quality is measured through non-performing exposures (NPEs), non-performing loans (NPLs), and non-performing debt securities (NPDS).
  • Indicators are segmented by counterparty sector and country of residency.
  • Asset quality is interlinked with liquidity risk, but they are distinct concepts.

Main Views and Key Information

• Purpose of the Guide: To provide guidance on the concepts, data sources, and computation techniques for the EBA's risk indicators and DRATs, ensuring consistency and transparency.
• Data Sources: The indicators are based on COREP and FINREP reporting frameworks, which are harmonised across the EU.
• Methodological Tools:
  • DRATs go beyond traditional ratios by using data presentation and visualisation techniques to enhance analytical depth.
  • XBRL taxonomies are used to facilitate data exchange.
• Scope:
  • The guide covers 53 KRLs (Key Risk Indicators) and 34 FNDs (Funding Risk Indicators), along with various DRATs.
  • It supports comparative analysis across banks, jurisdictions, and the EU as a whole.
• Methodological Considerations:
  • Negative values in ratios need special handling.
  • Statistical measures like averages, percentiles, and standard deviations are used to interpret data.
  • Currency reporting is important due to the non-fungibility of liquidity and funding across currencies.
  • Flow data is used to track changes in financial positions over time.
  • The 'follow-the-money' approach and peer group analysis are alternative methods for calculating and comparing indicators.

Additional Methodological Issues

• Data Scope and Quality:
  • The EBA collects data from 55 banks in 20 EEA countries.
  • Data is collected through best-efforts methods, either directly from institutions or by mapping national formats to COREP/FINREP.
• Reporting Frequency and Timeliness:
  • The ITS (Implementing Technical Standards) on supervisory reporting serve as the backbone for data collection and harmonisation.
  • They define reporting frequency, reference dates, and remittance dates.
• Compliance and Flexibility:
  • While the guide supports consistent indicator computation, it is not mandatory and is intended to assist rather than bind competent authorities.
  • It is a living document, subject to periodic updates based on new experiences, user needs, and changes in EU reporting standards.

Conclusion

This guide offers a comprehensive framework for the analysis and monitoring of banking risks, supporting both internal EBA users and external competent authorities. It enhances data comparability, transparency, and analytical depth by introducing DRATs and addressing methodological challenges in the computation of risk indicators. The guide is essential for risk management, supervision, and public reporting in the EU banking sector.