Revisiting the Early Years of Risk-Based Supervision ( 1980-2000)
Dr. Sunando Roy
Advisor @ Central Bank of Bahrain | Risk Leader, PRMIA ।Audit Leader Network Member , Institute of Internal Auditors (IIA), । Fellow , International Compliance Association(FICA) । Fellow, UC Irvine I Published Author
Concepts
The global banking landscape has undergone unprecedented transformation over the last few decades. Financial deregulation, globalization, and technological advancements have led to a more complex and risk-prone financial system. With increasing competition and innovation, banks have adopted new business models, developed complex financial instruments, and engaged in cross-border transactions, exposing them to greater financial, operational, and systemic risks.
Banking supervision has had to evolve in response. Traditional supervisory mechanisms, which relied heavily on periodic on-site inspections, were increasingly seen as inadequate in identifying risks in real-time. The need for more dynamic and proactive monitoring methods became clear. This led to the development of supervisory risk assessment and early warning systems, which integrate financial indicators, statistical models, and qualitative management assessments to assess risk comprehensively and predict potential bank failures or financial distress.
The fundamental principle behind these systems is risk-based supervision—a regulatory approach that prioritizes banks with higher risk profiles, ensuring that supervisory resources are allocated efficiently. These methods have since become global best practices, forming the foundation of modern prudential supervision frameworks.
Evolution of Risk-Based Supervision
The roots of risk-based supervision can be traced back to the early 1980s, when bank failures in the United States highlighted the limitations of traditional supervision methods. This led to the introduction of the CAMEL rating system, which provided a structured framework for evaluating banks based on capital adequacy, asset quality, management quality, earnings, and liquidity.
By the 1990s, financial crises in different parts of the world—including the Savings and Loan crisis in the U.S. and banking crises in Latin America and Asia—accelerated efforts to refine supervisory practices. Supervisors began incorporating off-site analytical techniques, allowing them to identify early warning signals of financial distress before problems escalated.
BIS WP4 (2000) represents a major milestone in this evolution. The paper was one of the first comprehensive studies of supervisory risk assessment and early warning systems across G10 countries, documenting their methodologies, effectiveness, and future potential. This led to a global paradigm shift towards formalized, risk-focused, and data-driven supervision, which has only continued to evolve in the 21st century.
Country Experience and Innovations
Different countries adapted risk-based supervision based on their unique financial structures, regulatory environments, and available resources. The U.S., France, Germany, Italy, the Netherlands, and the U.K. all developed distinct supervisory tools, but with a common goal: to improve early risk detection and supervisory efficiency.
The U.S. led the way with SEER, SCOR, and Growth Monitoring System (GMS), which utilized statistical models and financial data analysis. The French Banking Commission implemented ORAP, integrating peer group comparisons and stress testing. Germany's BAKIS, Italy's PATROL, and the Netherlands' RAST each developed quantitative and qualitative risk assessment methodologies. Meanwhile, the UK's RATE model focused on consolidated risk analysis and structured regulatory reviews. These innovations provided valuable insights into banking resilience and risk mitigation strategies.
Contrasts and Commonalities in Advanced Economies
Although risk-based supervision became a widely accepted principle among advanced economies, each country’s approach reflected unique priorities and regulatory philosophies.
Some jurisdictions placed a greater emphasis on statistical modeling and quantitative analysis, such as the U.S. and Germany, while others like France and Italy incorporated more qualitative assessments, including management oversight and compliance culture. The UK and Netherlands developed hybrid models, integrating both quantitative analytics and regulatory oversight mechanisms. Despite these contrasts, common features included:
• The use of financial ratios and peer group analysis for risk evaluation.
• A focus on early warning indicators to flag potential vulnerabilities.
• The integration of qualitative supervisory insights alongside quantitative modeling.
• A risk-based resource allocation strategy, prioritizing oversight of high-risk banks.
Supervisory Models of Risk-Based Supervision
This appendix provides an overview of key supervisory models used across various regulatory frameworks.
1. CAMELS (United States) – A rating system evaluating Capital adequacy, Asset quality, Management, Earnings, Liquidity, and Sensitivity to market risks.
2. SEER (United States, Federal Reserve) – A statistical model for estimating supervisory risk ratings based on historical data.
3. SCOR (United States, FDIC) – A regression-based tool designed to predict bank failures by analyzing financial indicators.
4. ORAP (France, Banking Commission) – A multi-factor approach incorporating internal and external risk assessments.
5. BAKIS (Germany, Federal Supervisory Office) – A peer group comparison system for evaluating financial stability.
6. PATROL (Italy, Bank of Italy) – An off-site rating system that focuses on capital adequacy, earnings, and liquidity.
7. RATE (United Kingdom, Financial Services Authority) – A comprehensive risk assessment framework evaluating business risks and financial health.
8. RAST (Netherlands, Netherlands Bank) – A model that integrates qualitative and quantitative risk indicators for supervisory assessment.
These models represent a structured approach to risk-based supervision, ensuring that banks operate within sound financial parameters while enabling regulators to anticipate potential vulnerabilities.
Early Warning Indicators: Key Metrics for Predicting Financial Distress
Early warning indicators (EWIs) serve as critical tools for identifying potential vulnerabilities within a banking institution. These indicators are derived from financial ratios, macroeconomic trends, and qualitative supervisory assessments. The primary objective of EWIs is to provide regulators with advance notice of financial distress, enabling them to take preemptive action before problems escalate.
Key Early Warning Indicators
1. Capital Adequacy Indicators
o Risk-weighted capital ratios (Basel standards compliance).
o Leverage ratios measuring total assets to equity.
2. Asset Quality Indicators
o Non-performing loans (NPLs) as a percentage of total loans.
o Loan loss provisions relative to total assets.
3. Liquidity Indicators
o Loan-to-deposit ratio, measuring liquidity reliance.
o High-frequency liquidity stress tests.
4. Earnings Performance Metrics
o Return on Assets (ROA) and Return on Equity (ROE).
o Net interest margin (NIM).
5. Market Risk Indicators
o Sensitivity to interest rate fluctuations.
o Foreign exchange and derivatives exposure.
6. Macroeconomic & Systemic Indicators
o Credit-to-GDP ratio and deviation from trend.
o Inflation, GDP growth, and unemployment levels.
These indicators are integrated into supervisory models to determine a bank’s financial health and assign risk ratings. In the context of supervising increasingly complex financial sector, BIS WP4 (2000) was a seminal study that evaluates the risk-based supervisory models in use across G10 countries. It provided:
• A taxonomy of supervisory approaches, classifying them into four broad categories: supervisory bank rating systems, financial ratio and peer group analysis, comprehensive bank risk assessment models, and statistical models.
• A detailed comparison of how different countries have structured their risk assessment frameworks.
• An assessment of the effectiveness of early warning systems in predicting banking crises.
• Policy recommendations for further refinement and global adoption of risk-based supervision.
The G10 initiative, as outlined in BIS WP4, aimed to harmonize risk-based supervision across major economies. The key recommendations included:
• Enhancing predictive accuracy of supervisory models.
• Integrating qualitative assessments with quantitative analytics.
• Developing international data-sharing mechanisms for cross-border bank supervision.
Conclusion
The recommendations in BIS(2000) continue to influence modern supervisory policies, ensuring that financial institutions are monitored effectively and that systemic risks are minimized.Risk-based supervision has transformed bank regulation from a reactive process to a proactive, data-driven approach. BIS WP4 laid the foundation for future innovations, shaping the way banks are monitored today. The continued evolution of supervisory models and early warning systems remains crucial to maintaining financial stability in an increasingly interconnected world. Given the Importance of the study for subsequent developments in RBS and EWI, the study deserves, in my view, a revisit.
As the Keynote speech by Erik Thedéen, (Chair of the Basel Committee on Banking Supervision and Governor of Sveriges Riksbank) , at the Institute of International Finance Annual Membership Meeting, Washington DC, 23 October 2024 underscores : “ we cannot afford to ignore, or forget, the lessons of history. This time is not different. There have been no fewer than 150 systemic banking crises since 1970.9 Just last year, we saw the most significant system-wide banking stress since the GFC, including the distress of five banks with total assets exceeding one trillion US dollars. While each banking crisis may have had its unique characteristics, the common thread throughout history is that we simply cannot predict when or from where the next crisis will emerge. We therefore need to ensure robust and durable resilience for the global banking system to withstand a range of potential shocks.”
Reference
Bank for International Settlements. Supervisory Risk Assessment and Early Warning Systems. Working Paper No. 4. Basel: Bank for International Settlements, 2000.