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IMF Country Report No. 22/279

WEST AFRICAN ECONOMIC AND MONETARY UNION

FINANCIAL SECTOR ASSESSMENT PROGRAM

TECHNICAL NOTE ON STRESS TESTS, CREDIT CONCENTRATION, AND INTEREST RATE RISKS

August 2022

This technical note on Bank Stress Test for Climate Change Risks was prepared by a staff team of the International Monetary Fund and World Bank in the context of a joint IMF-World Bank Financial Sector Assessment Program (FSAP). It is based on the information available at the time it was completed in July 2022.

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Title page

WEST AFRICAN ECONOMIC AND MONETARY UNION

FINANCIAL SECTOR ASSESSMENT PROGRAM

July 22, 2022

TECHNICAL NOTE

STRESS TESTS: CREDIT, CONCENTRATION, AND INTEREST RATE RISKS

Prepared by

Monetary and Capital Markets Department

This technical note was prepared by IMF staff in the context of a Financial Sector Assessment Program (FSAP) mission to the West African Economic and Monetary Union. The note contains technical analysis and detailed information underpinning the FSAP assessment's findings and recommendations. Further information on the FSAP can be found at http://www.imf.org/external/np/fsap/fssa.aspx.

Contents

  • Glossary

  • EXECUTIVE SUMMARY

  • INTRODUCTION

  • MACROFINANCIAL SCENARIOS

  • AGGREGATION THROUGH STATISTICAL CLUSTERING

  • CREDIT RISK

  • INTEREST RATE RISK

  • CONCENTRATION RISK

  • MEASURES AND RECOMMENDATIONS

  • CONCLUSION

  • REFERENCES

  • FIGURES

  • 1. Scenarios—Growth at Risk

  • 2. Scenarios—Inflation at Risk

  • 3. Bank Clustering

  • 4. Credit Risk

  • 5. Interest Rate Risk

  • 6. Concentration Risk

  • TABLES

  • 1. Table of Recommendations

  • 2. Composition of Synthetic Variables—GaR Model

  • 3. Composition of Synthetic Variables—IaR Model

  • 4. Financial Soundness Indicators

  • ANNEXES

  • I. At-risk Models on Small and Noisy Samples

  • II. Estimating Synthetic Variables by Partial Least Squares

  • III. Risk Assessment Matrix

  • IV. Grouping Banks by Statistical Clustering

  • V. Stress-Testing via Quantile Regressions

  • VI. Recursive Dynamic Projection Model

  • VII. Matrix of Banking Sector Stress Tests

Glossary

BCEAO

Central Bank of West African States (In French: Banque Centrale des États de l’Afrique de l’Ouest)

CBU

Banking Commission of the West African Monetary Union (In French: Commission Bancaire de l’UMOA)

FSAP

Financial Stability Assessment Program

GaR

Growth at Risk

GDP

Gross Domestic Product

IaR

Inflation at Risk

OLS

Ordinary Least Squares

PCA

Principal Component Analysis

PDs

Probabilities of Default

PLS

Partial Least Squares

RAM

Risk Assessment Matrix

RWA

Risk-weighted Assets

WAEMU

West African Economic and Monetary Union (Benin, Burkina Faso, Côte d’Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo)

Executive Summary

This technical note presents the stress tests on credit, interest rate, and concentration risk conducted by the WAEMU FSAP.1 Stress tests on contagion and liquidity risks are addressed separately.2 Stress tests are an important tool for detecting financial sector vulnerabilities, setting up targeted banking sector monitoring, imposing preventive measures, and informing public decision-makers of macrofinancial risks and costs.

The solvency and interest rate stress tests analyze the impact of macroeconomic crisis scenarios on bank capitalizations via an impairment of their credit portfolios and profitability. These stress tests are based on a new methodology that captures the macroeconomic, financial, and idiosyncratic sources of risk. The approach includes four steps: (i) construction of base and adverse macroeconomic scenarios; (ii) clustering of banks in homogenous groups using statistical methods; (iii) estimation of the sensitivities of the probabilities of default and return on assets to economic conditions; and (iv) projected deterioration of bank portfolios and profitability under the baseline and adverse scenarios.

The stress test scenarios consider a baseline and an adverse post-COVID “recovery-at-risk” paths. The baseline scenario represents a V-shaped recovery, with a strong and rapid resurgence of growth, while the adverse scenario depicts a U-shaped recovery, with a persistent weakening of growth before it converges with the baseline scenario at the end of the test period. The cumulative difference between the gross domestic product (GDP) levels in the adverse scenario and the base scenario is on the order of 15 percentage points, or 2.2 historical standard deviations on average. This could be described as a “severe but plausible” scenario.3

The concentration tests assess the effect of a default by the main private debtors on bank portfolios. The FSAP team tested bank concentration risks by conducting a reverse stress test that evaluated the breaking point, i.e., the maximum number of cumulative large exposures that a bank can cover with its capital.

The stress test results indicate that the WAEMU banking system’s recapitalization needs are moderate, but smaller banks and banks in certain member countries are vulnerable. Bank recapitalization costs due to shocks to economic growth and inflation are limited as a percentage of regional GDP—to between one and two percent, depending on the type of risk (credit, interest rate, or concentration), the scenario, and the degree of risk. The relatively small size of the banking sector as a percentage of regional GDP and the soundness of large banks explains the moderate system-wide recapitalization cost. However, this cost could be higher in certain countries (especially for concentration risk) and around 30 small banks (out of a sample 100) are vulnerable to deteriorating macrofinancial conditions—in addition to about 20 banks that already do not meet the regulatory capital requirement.

The FSAP recommends increasing capital for fragile banks. The imposition of additional capital buffers for fragile banks is necessary, as is the strict application of concentration limits.

The FSAP suggests that the regulator should draw upon the statistical methods presented in this technical note to strengthen financial supervision. The Central Bank of West African States (BCEAO) could improve its bank monitoring framework by using risk modeling and statistical methods to identify the most vulnerable banks. Some of these methods are presented in this technical note. This technical note introduces three main technical innovations to help BCEAO experts: (i) design macro-financial risks scenarios using a risk-based model; (ii) group banks by clusters to conduct cluster analysis; and (iii) estimate the probabilities of default and the shocks impact on banks’ ROA at different risk levels via quantile regressions. IMF technical assistance may be required to support the regulator in the rollout of these methods.

Table 1.

WAEMU: Table of Recommendations

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ST=short-term (1–2 years); MT=medium-term (3–5 years).

1

This technical note was prepared by Romain Lafarguette, with the assistance of Zhuohui Chen. The main Python packages used for the stress tests are available at https://romainlafarguette.github.io/.

2

See the 2022 WAEMU FSAP Technical Note “Systemic Risks and Macroprudential Policy Framework” (IMF 2022a) for stress tests focusing on contagion risks, and the Technical Note “Systemic Liquidity Analysis” (IMF 2022b) for stress tests focusing on liquidity.

3

In the peak year of stress, the difference would reach 2.3 standard deviations from historical mean.

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West African Economic and Monetary Union: Financial Sector Assessment Program-Technical Note-Stress Tests, Credit Concentration, and Interest Rate Risks
Author:
International Monetary Fund. African Dept.