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### Introduction and financial sector structure
- Total financial sector assets: about 298 percent of GDP.
- Commercial banks’ assets: 112 percent of GDP.
- Insurance sector’s gross assets: 67 percent of GDP.
- Return on equity of the four largest banks remained above 20 percent during the crisis.
- Non-performing loans declined from 6 percent in late 2009 to 3.6 percent in 2013.
- Regulatory tier one ratio: 13.5 percent in 2013.
- Systemic vulnerabilities identified:
  - Systemic liquidity risk from large current account and fiscal deficits and high dependence on short-term wholesale funding; exposure to OTC counterparty credit risk.
  - Household and corporate indebtedness risks, including a large share of floating-rate mortgages and rapid expansion of unsecured lending (unsecured lending to low-income households grew by 50 percent year-on-year in 2011).
  - Concentration and interconnectedness: five large banks account for 90.5 percent of total banking assets; top five insurance companies account for 74 percent of the market for long-term insurance and 44 percent for short-term insurance; seven largest fund managers control 60 percent of the unit trust collective investment schemes industry.
  - Cross-border expansion: claims of South African banks on other African countries have more than tripled over five years to 2 percent of total assets.

### Stress test coverage and scope
- Bank STs:
  - Top-down (TD) covers four large IRB banks and 86 percent of banking assets.
  - Bottom-up (BU) covers six banks (including cross-border activities) and 94 percent of banking assets.
- Insurance BU ST covers five major life insurers (70 percent of the sector’s assets) and four non-life insurers (50 percent of the sector’s premiums).
- Risks assessed: credit risks, market risks, liquidity risks, contagion risks, interest-rate sensitivity of household debt, counterparty risks (including failure of a large bank for insurers), and insurance underwriting risks (e.g., catastrophic event).

### Macro-financial scenarios and modeling assumptions
- Scenarios:
  - Baseline: modest GDP growth, persistent high unemployment, gradual upward normalization of interest rates (aligned with IMF April 2014 projections, subsequently adjusted downward in August 2014; baseline has become considerably worse since STs were conducted).
  - Adverse: mild decline in GDP growth due to disorderly exit from unconventional monetary policy in advanced economies, causing capital outflows, increased volatility, and higher-than-expected interest rates.
  - Severely adverse: three years of negative growth and cumulative eight standard deviation event from baseline; described as “perfect storm.”
  - BU severely adverse includes additional market shocks in 2015 calibrated to be consistent with those observed in 2008.
- TD LGD downturn mapping:
  - Adverse scenario LGD = 0.08 + 0.92*LGD_TTC.
  - Severe scenario LGD = 0.10 + 0.92*LGD_TTC.
- PD models: logit transformation and first differences; explanatory variables include GDP growth, policy rate, 10-year bond yield, property price growth, household debt-to-income, government debt/GDP, unemployment, domestic credit, M3 growth, NEER, ZAR/USD, commodity prices, stock index, crude oil, capital ratio, exposure growth; current value and up to four lags; model selection by Bayesian information criteria.
- Balance sheet growth and income assumptions:
  - Banks with capital ratios above minimum CET1 increase balance sheet at own estimated rate or at same pace as nominal GDP if positive; capped at zero if nominal GDP negative.
  - Banks failing Tier 1 requirements keep balance sheet in TD ST; some deleverage in BU STs.
  - Provision = expected loss = PD × LGD × exposure; expected loss assumed equal to realized loss.
  - TD net income grows with nominal GDP; BU disaggregates income components and reports pre-tax and after-tax projections.
- Market risk shocks: instantaneous shocks applied to second year of severely adverse scenario following US CCAR methodology; large changes in levels, spreads, and volatilities calibrated to 2008.

### Banking solvency results (overview and TD vs BU)
- Overall conclusion: Banks have adequate capital to withstand severe shocks in the scenarios tested.
- Maximum recapitalization need in the severe scenario: ZAR 72 bn (equivalent to 1.6 percent of 2018 nominal GDP).
- TD ST outcomes:
  - System-wide CET1 ratio declines from 11.2 percent to 7.0 percent in year three in the severely adverse scenario.
  - Extending to year five reduces CET1 by another 100 basis points.
  - Three of four banks would have a capital shortfall with respect to their minimum CET1 requirements starting from 2016; all banks would fall below minimum capital requirements in 2017 and 2018.
  - Performing PD for the performing floating-rate mortgage portfolio rises to a peak of 12 percent from 3.4 percent.
  - Performing PD for retail revolving credit portfolio rises almost four times to 19 percent from 4.4 percent.
  - Credit losses exceed net income in 2017 and 2018, resulting in a total loss equivalent to 4.4 percent of post-shock CET1 capital.
  - Higher PDs drive RWAs to grow by 16.8 percent per year on average versus 2.5 percent nominal average growth of the portfolio.
- BU ST outcomes:
  - Average CET1 ratio of the six banks was about 11.8 percent of RWAs as of 2013Q4 (regulatory minimum = 6.74 percent).
  - BU tests show smaller declines in net income and smaller PDs compared with TD; net interest income is only 0.6 percent lower than baseline in BU STs even with a 3 percent smaller loans and advances amount.
  - Non-interest revenue declines by 7 percent from the baseline; gross operating income is 4 percent lower; aggregate credit losses are 40 percent higher than baseline.
  - System-wide CET1 ratio declines by one percentage point by year three, even though average annual credit loss in the severely adverse scenario increases by 80 percent.
- Drivers of divergence TD vs BU:
  - BU allows positive net interest income effect from higher rates; TD does not.
  - TD uses stricter LGD and PIT PD assumptions, generating higher RWAs.
  - BU management actions (slower balance sheet growth, dividend restraint) and use of TTC PDs for some portfolios reduce RWAs and losses.

### Banking sensitivity tests and large exposures
- Total exposure to five largest non-financial borrowers: around 35 percent of total CET1 capital.
  - Default by all five non-financial borrowers would lower CET1 ratio by 1 percent.
  - Average LGD for non-financial borrowers: 27 percent.
- Aggregate exposure to five largest financial borrowers: 50 percent of CET1 capital.
  - Failure of all five financial borrowers would decline CET1 ratio by 1.9 percent.
  - Average LGD for financial borrowers: 54 percent.
  - In particular, one bank would lose almost all of its equity under the shock.
- Interest-rate sensitivity (BU STs):
  - Unsecured credit:
    - 100 bps increase → expected losses of 9.0 percent of total capital; translates into reduction of 1.8 percent of total capital considering provisions.
    - 500 bps increase → expected losses of 9.9 percent of total capital; translates into reduction of 2.2 percent of total capital considering provisions.
  - Floating-rate mortgage portfolio:
    - 100 bps increase → expected losses of 6.2 percent of total capital and capital level decline of 0.8 percent.
    - 500 bps increase → expected losses of 6.9 percent of total capital and capital level decline of 1.5 percent.
  - Caveats: interest-rate sensitivity tests do not include simultaneous increases in unemployment or declines in house and asset prices; usually assessed over a 12-month horizon so lagged effects beyond 12 months are not captured.
- Market risk on trading and fair-valued banking books:
  - Single-factor shocks produce limited losses; failure of the three largest counterparty exposures would reduce system CET1 ratio by 28 bps, highest impact on one bank 42 bps.
  - Concern remains on counterparty risk related to long gamma strategies.

### Liquidity risk, LCR and NSFR results
- LCR:
  - LCR measures stock of high-quality assets to total net cash outflow over next 30 calendar days.
  - LCR of five of six large banks tested was below 100 percent and for some banks below the 60 percent minimum requirement effective from 2015, without using SARB’s Committed Liquidity Facility (CLF).
  - Without the CLF, banks would experience a liquidity shortfall in less than 20 days under tested cash outflow assumptions.
  - Structural drivers: dependence on wholesale short-term funding, limited HQLA pool; 60 percent of bank deposits is wholesale funding from NBFIs and the corporate sector.
  - Short-term deposits (6 months maturity) rose to 63.3 percent of total deposits from 60.3 percent in 2008.
  - SARB’s CLF provides up to 40 percent of HQLA.
- NSFR:
  - All banks except one would have less than 100 percent coverage for the NSFR.
  - Banks face difficulty meeting minimum NSFR effective from 2018 due to small retail deposit base, costly long-term capital market funding, and FX risks from offshore funding.
  - Possible responses: reduce long-term assets, raise interest rates on deposits.
  - Staff affordability analysis: offering interest rate of 8.7 percent to attract longer term funding implies additional funding cost of ZAR 10 bn per year, equivalent to 1/6 of banks’ after tax profit as of end-2013; this implies an ROE of 14 percent assuming proportionate ROE reduction.
  - The 8.7 percent rate is 3 percent higher than historical average deposit rate of 5.7 percent (2010Q1–2013Q4); the 3 percent spread exceeds average spread between government bond yield and deposit rate of 2.7 percent (same sample).

### Insurance sector stress test results
- Aggregate outcome:
  - Insurance sector remains solvent and profitable on aggregate despite market value losses.
  - Capital shortfall for insurance companies: 0.1 percent of nominal GDP.
- Life insurers (participating sample of five):
  - Median CAR coverage ratio declines from 317 percent at end-2013 to 125 percent immediately after the shock.
  - One company’s CAR coverage drops below 100 percent with capital shortfall of ZAR 4 billion (4 percent of sample’s available capital before stress, or 0.1 percent of GDP).
  - By end-2014 median CAR coverage reverts to 177 percent; by end-2018 expected at 300 percent.
  - Aggregated profit of five life insurers declines by 58 percent to ZAR 9 billion in 2014 (after ZAR 21 billion in 2013); median RoE increases slightly from 16.5 percent in 2013 to 17.6 percent in 2014.
  - Annual net income expected to fluctuate around ZAR 16 billion in 2015–2018 with all five reporting positive earnings from 2015 onwards.
- Non-life insurers (participating sample):
  - Median CAR coverage ratio drops from 175 percent at end-2013 to 138 percent immediately after shock; one company below 100 percent.
  - Capital shortfall equals 2 percent of participating non-life companies’ available capital before stress.
  - By end-2014 median CAR coverage expected to increase to 151 percent and by end-2018 to 218 percent.
  - Aggregated net income declines by 37 percent in 2014; median RoE drops from 22.3 percent to 16.8 percent.
- Main contributors to solvency deterioration:
  - Life insurers: equity shock reduces available capital by 28 percent on average; default of largest banking counterparty reduces available capital by about 23 percent; interest rate shock also substantial.
  - Non-life insurers: equity shock reduces available capital by 19 percent; banking default reduces available capital by 13 percent.
- Catastrophe sensitivity:
  - A 1-in-100 year catastrophic loss reduces solvency ratios by 14 percentage points on average for large non-life companies.
  - Modeled event: strong earthquake in the Johannesburg region; followed by default of largest reinsurer with LGD 45 percent in sensitivity.
- Valuation and projection assumptions:
  - Statutory values under South African insurance solvency regime used; five-year projections with no new business assumed to assess recovery.
  - Under forthcoming SAM regime, current STs planned to be phased out; ORSA and supervisory committee under Twin Peaks to continue ST usage.

### Aggregation of banking and insurance stresses and conglomerate implications
- Combined assessment:
  - Financial institutions could weather combined losses from banking and insurance operations.
  - Maximum banking recapitalization need: ZAR 72 bn (1.6 percent of nominal GDP).
  - Insurance capital shortfall: 0.1 percent of nominal GDP.
  - Recapitalizing insurance companies would be within capacity of corresponding conglomerates given small size relative to aggregate group capital.

### Contagion episodes and systemic resilience
- African Bank episode:
  - Contagion risk was limited; SARB’s decisive resolution and market interventions soothed jitters when some money market funds “broke the buck” in 2014.
  - African Bank’s debt accounted for 1.3 percent of assets held by 43 money market funds; at least 10 funds “broke the buck.”
  - Capitec saw only a slight share price decline; Moody’s downgrade related to reduction in “too big to fail premium,” not bank soundness.
  - Vulnerability measure used: conditional probability of an institution’s default given default of another institution.
- Interconnectedness concerns:
  - Concentration and cross-holdings expose insurers and fund managers to counterparty risks from large banks.
  - Funding provided by NBFIs to banks is large; concentrated market structures mean idiosyncratic shocks can propagate across sectors.

### Key policy recommendations
- Banking sector:
  - Continue building a top-down stress test framework for the banking sector; TD ST to be conducted at least annually and complement BU exercises. — Implementation time: NT
  - Allocate more resources to validate models and assumptions used in BU STs by banks. — Implementation time: MT
- Insurance sector:
  - Develop a macroprudential stress testing framework for the insurance sector that is severe (but plausible), comprehensive (include sovereign risk), forward-looking (multi-year), and easy to communicate. — Implementation time: MT
  - Establish a stringent monitoring framework for assessing concentration risk of the insurance sector towards the largest domestic banks; request contingency plans from insurance companies covering financial planning and operational risk measures. — Implementation time: NT

*Source: South Africa — IMF FSAP Executive Summary (stress testing results and recommendations).*

### EXECUTIVE SUMMARY ___________________________________________________________________________  5

### EXECUTIVE SUMMARY

### Introduction
- Financial sector size and structure:
  - Total financial sector assets: about 298 percent of GDP.
  - Commercial banks’ assets: 112 percent of GDP.
  - Insurance sector’s gross assets: 67 percent of GDP.
- Sector performance and indicators:
  - Return on equity of the four largest banks remained above 20 percent during the crisis.
  - Non-performing loans declined from 6 percent in late 2009 to 3.6 percent in 2013.
  - Regulatory tier one ratio: 13.5 percent in 2013.
- Systemic vulnerabilities identified:
  - Systemic liquidity risk from large current account and fiscal deficits and high dependence on short-term wholesale funding; exposure to OTC counterparty credit risk.
  - Household and corporate indebtedness risks, including a large share of floating-rate mortgages and rapid expansion of unsecured lending (unsecured lending to low-income households grew by 50 percent year-on-year in 2011).
  - Concentration and interconnectedness: five large banks account for 90.5 percent of total banking assets; top five insurance companies account for 74 percent of the market for long-term insurance and 44 percent for short-term insurance; seven largest fund managers control 60 percent of the unit trust collective investment schemes industry.
  - Cross-border expansion: claims of South African banks on other African countries have more than tripled over five years to 2 percent of total assets.
- Coverage of stress tests:
  - Bank STs include both top-down (TD) and bottom-up (BU) components, covering 86 and 94 percent of banking assets, respectively (TD covers four large IRB banks; BU covers six banks and both local and foreign operations).
  - Insurance BU ST covers five major life insurers (70 percent of the sector’s assets) and four non-life insurers (50 percent of the sector’s premiums).
- Scope of risks assessed in STs: credit risks, market risks, liquidity risks, contagion risks, interest-rate sensitivity of household debt, counterparty risks including failure of a large bank for insurers, and insurance underwriting risks (e.g., catastrophic event).

### Solvency Risk — Methodologies and Scenarios
- Macro-financial scenarios:
  - Scenarios aligned with IMF Global Risk Assessment Matrix (G-RAM) and generated using SARB’s Global Projection Model and Core Model.
  - Baseline scenario: modest GDP growth, persistent high unemployment, gradual upward normalization of interest rates (aligned with IMF April 2014 projections, subsequently adjusted downward in August 2014; baseline has become considerably worse since STs were conducted).
  - Adverse scenario: mild decline in GDP growth due to disorderly exit from unconventional monetary policy in advanced economies, causing capital outflows, increased volatility, and higher-than-expected interest rates.
  - Severely adverse scenario: “perfect storm,” GDP growth falls sharply and stays negative for three consecutive years; scenario equivalent to a cumulative eight standard deviation event from the baseline.
- Bank stress test methodologies:
  - TD ST uses supervisory data, panel data models for PDs across 10 asset classes, linear mapping functions for LGD downturn adjustments, and covers four large IRB banks (domestic operations).
  - BU STs use banks’ proprietary data, internal models, and expert judgment; cover six banks including cross-border activities.
  - Key methodological notes:
    - TD LGD mapping for downturns: Adverse scenario LGD = 0.08 + 0.92*LGD_TTC; Severe scenario LGD = 0.10 + 0.92*LGD_TTC.
    - PD panel models use logit transformation and first differences; explanatory variables include GDP growth, policy rate, 10-year bond yield, property price growth, household debt-to-income, government debt/GDP, unemployment, domestic credit, M3 growth, NEER, ZAR/USD, commodity prices, stock index, crude oil, capital ratio, exposure growth; current value and up to four lags considered; model selection by Bayesian information criteria.
- Insurance ST methodology:
  - BU approach covering major life and non-life insurers; sensitivity analyses for market shocks, default of largest banking counterparty, and catastrophic underwriting events.

### Solvency Risk — Banking Sector Results
- Overall conclusion:
  - Banks have adequate capital to withstand severe shocks in the scenarios tested.
  - Recapitalization need in the severe scenario: ZAR 72 bn at the maximum, equivalent to 1.6 percent of 2018 nominal GDP.
  - Banks appear resilient to market risks in both trading and banking books.
- Liquidity-related solvency caveats:
  - Impact of a large default could be significant despite aggregate capital adequacy.
- TD vs BU coverage and limitations:
  - TD limited to four large IRB banks due to supervisory data availability for PD, LGD, and EAD.

### Solvency Risk — Insurance Sector Results
- Aggregate sector outcome:
  - Despite market value losses, the insurance sector on aggregate remains solvent and profitable.
  - Capital shortfall for insurance companies: 0.1 percent of nominal GDP.
- Sensitivities and heterogeneity:
  - High sensitivity to market risks, especially equity price movements and the default of the largest banking counterparty.
  - Life insurers:
    - Solvency ratios declined sharply under shocks.
    - Decline mitigated by passing on lower investment returns to policyholders.
  - Non-life insurers:
    - More resilient due to more conservative investment strategies.
- Conglomerate-level implications:
  - Recapitalizing the few insurance companies would be within the capacity of corresponding conglomerates, given the small size of required capital relative to aggregate group capital.

### Aggregation of Banking and Insurance Stresses
- Combined assessment:
  - Financial institutions could weather combined losses from banking and insurance operations.
  - Maximum banking recapitalization need: ZAR 72 bn (1.6 percent of 2018 nominal GDP).
  - Insurance capital shortfall: 0.1 percent of nominal GDP.
  - Insurance recapitalization feasible within conglomerate group capital resources.

### Liquidity Risk (Summary)
- Key findings:
  - Banks need larger liquidity capacity to meet regulatory requirements.
  - Some banks would have difficulty meeting the Liquidity Coverage Ratio (LCR) without the Committed Liquidity Facility (CLF) provided by the South African Reserve Bank (SARB).
  - Meeting the Net Stable Funding Ratio (NSFR) poses bigger challenges unless banks reduce the maturity profile of assets.

### Contagion Risk (Summary)
- Interconnectedness implications:
  - Concentration and cross-holdings expose insurers and fund managers to counterparty risks from large banks.
  - Sensitivity analyses include failure of a large bank and global market shocks to assess spillover effects.

### Key Policy Recommendations (Table 1 summarized)
- Continue building a top-down stress test framework for the banking sector. — Implementation time: NT
- Allocate more resources to validate models and assumptions used in the bottom-up stress tests by banks. — Implementation time: MT
- Develop a macro stress test for insurance companies. — Implementation time: MT
- Establish a stringent monitoring framework for assessing the concentration risk of the insurance sector towards the largest domestic banks. — Implementation time: NT

*Source: South Africa — IMF FSAP Executive Summary (stress testing results and recommendations).*

### Box 1. Modeling Approaches and Assumptions in the TD and BU STs (continued)

### Box 1. Modeling Approaches and Assumptions in the TD and BU STs (continued)

### Balance sheet growth
- The relative proportion of the balance sheet items and the trading positions remain the same under all scenarios in both the TD and BU STs.
- Banks with capital ratios above the minimum common equity tier one (CET1) capital requirements:
  - increase their estimated balance sheet at an own estimated rate or at the same pace as nominal GDP, if the latter is positive.
  - If the nominal GDP growth rate is negative, balance sheet growth will be capped at zero.
- Banks that fail to meet the Tier 1 capital requirements:
  - will keep their balance sheet even under positive nominal GDP growth in the TD ST.
  - some banks would deleverage in the BU STs.
- Note: In particular, in the TD ST, it is assumed that all banks grow the balance sheet at the same rate as the nominal GDP.

### Loan loss provision
- Provision = expected loss = PD × LGD × amount of exposure.
- Assumption: the expected loss is equal to the realized loss.

### Net income growth
- TD ST:
  - Net income for each bank assumed to grow at the same rate as nominal GDP.
  - Net income defined as income before deducting the loan loss provision.
- BU STs:
  - Income projections disaggregated into interest income, interest expenses, trading income, and operating expenses to reflect asset–liability structure.
  - Both pre-tax and after-tax projections reported.

### Risk weighted assets (RWAs)
- TD approach:
  - Changes in RWAs calculated following an approximate Basel II internal ratings-based (IRB) approach.
  - IRB formula used to determine regulatory RWAs for the loan book and their changes over the stress horizon.
  - For regulatory RWAs, point-in-time (PIT) PD and the above downturn LGDs are assumed and exposures are net of provisions.
  - Percentage changes in regulatory RWAs from the base year (i.e., year 2013) are applied to the base year realized RWAs to generate the final RWAs.
  - Note: The realized RWAs include RWAs for credit risk, market risk, and operational risk. They are based on the total assets rather than on the loan book.
- BU STs:
  - Banks follow the regulatory approach to formulate RWAs with the one exception that PIT PDs, rather than TTC PDs, are used in the exercise.
  - Regulatory requirement would use TTC PDs to avoid procyclicality, but PIT PDs are preferred in STs since they fully incorporate unexpected loss measured by RWAs under stress.
  - Some banks noted capacity constraints to generate PIT equivalent results for certain loan portfolios.

### Dividend, hurdle rates, and capital formulation
- Dividend payout depends on a bank’s buffer over the minimum capital ratio, following the maximum payout ratio in the table (Source: IMF Staff).
  - In the BU STs, banks pay out less than the maximum assumed in the TD ST.
- Hurdle rates:
  - Minimum capital ratio consists of Basel III minimum CET1 requirements, and Pillar 2A and Pillar 2B charges.
  - Reflects phase-in of the Domestic Systemically Important Bank (D-SIB) charge and the capital conservation buffer.
  - Source: SARB D5/2013.
  - Note: The Pillar 2B charge and D-SIB charge are bank-specific and confidential information.
- Capital formulation:
  - Capital(t) = Capital(t-1) + net income(t) − dividend payout(t) − loan loss provisions(t).

### Market risk shocks in scenario analysis
- To assess market risks, a comprehensive set of instantaneous market shocks were added to the second year of the severely adverse scenario, following US CCAR methodology.
- Trading positions (interest rate, exchange rate, equity, commodity, credit-risk sensitive instruments) and financial assets classified as “available for sale” and “designated at fair value through profit and loss” were valued under large, sudden changes in levels, spreads, and volatilities calibrated to be consistent with those observed in 2008.

### Complementary sensitivity tests
- Sensitivity tests include:
  - Failures by large financial and non-financial borrowers to study concentration and counterparty risks.
  - Sensitivity of mortgage portfolio and unsecured lending credit quality to large interest rate hikes.
  - Sensitivity to market risks (e.g., Prime-JIBAR basis risk and widened credit spreads) on trading book and banking book.

### Insurance stress test—approach and assumptions
- Main focus: market risks; counterparty risks and specific insurance underwriting risks also tested.
- BU solvency ST performed for life and non-life insurers, based on the FSB solvency ST conducted semiannually.
- South Africa to implement Solvency Assessment and Management (SAM) by 2016; a quantitative impact study was ongoing, so a comprehensive SAM-based ST was not practical at time of exercise.
- FSB ST includes single-factor shocks and a combined economic scenario addressing interest rate, equity, property, exchange rate, and (corporate) credit risks.

### Insurance ST—stress level and specific shocks
- Overall stress level in the solvency test was higher for insurers than under the macro-financial scenario used for the banking ST, due to FSB’s conservative ST specification and additional FSAP shocks:
  - An increase in sovereign spreads, reaching 262 basis points for South African government bonds.
  - Default of the largest banking counterparty with LGD on contractual obligations assumed to be 45 percent of gross exposure; equity exposures assumed a price decline of 100 percent (instead of standard 50 percent).
  - Single-factor sensitivity: a catastrophic event of magnitude expected once in 100 years; following the event, default of the largest reinsurer assumed with an LGD of 45 percent.

### Box 2 — Insurance Stress Testing by the FSB (single-factor and economic scenario specifications)
- Single factor stresses:
  - Interest rates: Shift in the yield curve – 50% up; Shift in the yield curve – 35% down
  - Equity prices: Ordinary shares – 50% down; Preference shares (fixed rate) – 30% down; Preference shares (variable rate) – 10% down
  - Property prices: 30% down
  - Exchange rate: 30% depreciation; 30% appreciation
  - Volatility: 15% addition for equity; 10% addition for interest rate
  - Credit risk: Double the CAR credit risk allowance
- Economic scenario stress:
  - Interest rates: Shift in the yield curve – 35% down
  - Equity prices: Ordinary shares – 50% down; Preference shares (fixed rate) – 30% down; Preference shares (variable rate) – 10% down
  - Property prices: 30% down
  - Exchange rate: 30% depreciation
  - Credit risk: Double the CAR credit risk allowance
  - Volatility: 15% addition for equity; 10% addition for interest rate
- Notes:
  - The FSB economic scenario includes a decline in interest rates; compared to an increase, this is more severe for life insurers in South Africa (FSB sensitivity analysis as of end-2013).
  - Under forthcoming SAM regime, current STs planned to be phased out; ORSA and supervisory committee under Twin Peaks will continue ST usage.

### Insurance ST—valuation and projection assumptions
- Statutory values of assets and liabilities under South African insurance solvency regime formed basis of ST calculations.
- Companies reported on a solo basis; impact on CAR calculated based on statutory valuation and solvency regime at reference date.
- Five-year projections requested to assess medium-term recovery ability; projections included asset returns below historic averages and strict assumption of no new business underwritten, resulting in gradually declining premium income.

### Results for the Banking Sector—overview
- STs confirm banks’ capital levels are adequate to withstand credit losses in the adverse and severe scenarios, partly due to high capital buffers.
- As of 2013Q4, the average CET1 ratio of the six banks was about 11.8 percent of RWAs, well above the regulatory minimum of 6.74 percent.
  - Note: The capital ratio is for bank solo, including foreign and local banking operations. The number is based on data submitted in the BU STs.
  - Note: 6.74 percent is the RWA weighted average of minimum CET1 requirements, which include the Basel III minimum CET1 requirements, Pillar 2A and Pillar 2B charges.

### Scenario analyses—BU STs findings
- Banks’ capital positions remain resilient in the BU STs since net income is not much affected in the stress scenarios, offsetting credit losses.
- Key quantified outcomes:
  - Non-interest revenue declines by 7 percent from the baseline owing to lower business volume.
  - Gross operating income is only 4 percent lower than in the baseline.
  - Aggregate credit losses are 40 percent higher than in the baseline.
  - Compared to end-2013 starting point, system-wide CET1 ratio declines by one percentage point by year three, even though average annual credit loss in the severely adverse scenario increases by 80 percent.

### Scenario analyses—TD ST findings
- TD ST has larger negative impact on capital ratios, but capital shortfall remains manageable.
- Key quantified outcomes:
  - System-wide CET1 ratio declines from 11.2 percent to 7.0 percent in year three in the severely adverse scenario.
  - Extending the test to year five reduces the CET1 ratio by another 100 basis points.
  - Three of the four banks would have a capital shortfall with respect to their minimum CET1 requirements starting from 2016; all banks would fall below minimum capital requirements in 2017 and 2018.
  - Maximum capital shortfall = 1.6 percent of 2018 nominal GDP.
  - Performing PD for the performing floating-rate mortgage portfolio rises to a peak of 12 percent from 3.4 percent.
  - Performing PD for retail revolving credit portfolio rises almost four times to 19 percent from 4.4 percent.
  - Credit losses exceed net income in 2017 and 2018, resulting in a total loss equivalent to 4.4 percent of post-shock CET1 capital.
  - Higher PDs drive RWAs to grow by 16.8 percent per year on average, far exceeding the 2.5 percent nominal average growth rate of the entire portfolio.

### Differences between TD and BU STs—drivers of divergence
- BU tests allow banks to benefit from higher interest rates in the severely adverse scenario due to positive net rate-sensitive asset positions; TD does not consider this effect (TD net income grows with nominal GDP).
  - Net interest income is only 0.6 percent lower than in the baseline in BU STs, even though amount of loans and advances is 3 percent smaller.
  - Loans and advances are mostly prime-linked and rate-sensitive. Non-rate-sensitive funding (shareholders’ funds and non-repricing transactional deposits) together account for a quarter of banks’ funding.
- TD relies mostly on a statistical approach to project credit quality; banks in BU STs use modeling plus expert judgment and report smaller PDs.
- TD uses more stringent assumptions on LGDs; overall credit quality deteriorates much more in TD than in BU STs.
- RWAs modeling:
  - BU STs: some banks use TTC PDs for certain portfolios, yielding lower RWAs.
  - TD ST: uses PIT PDs for all portfolios, generating higher RWAs.
- Other reasons for differences:
  1. Management action: balance sheet growth slower in BU STs than TD ST, yielding smaller credit losses and smaller RWAs.
  2. Time constraints: some banks could not adjust existing ST frameworks from a three-year horizon to a five-year horizon and therefore used a shorter horizon than TD ST. Conversations indicated ST results could have been worse if horizon extended due to lagged effects (e.g., 18 months for macro downturn to affect credit quality of some portfolios).
  3. TD ST assumes a maximum dividend payout ratio while BU STs may restrict dividends.

### Trading and market-loss results
- Banks’ trading and fair valued banking books appear resilient to global market shocks in the macro-financial scenarios; losses are within group risk limits.
- Largest losses come from interest rate directional movements and widening credit spreads.
- Higher interest rates and larger credit spreads reduce mark-to-market value of sovereign and corporate bond portfolios in trading book (held partly for liquidity).
- Other large losses due to:
  - Credit value adjustment (CVA) – market value of counterparty default risk.
  - Incremental default risk (IDR) – capital charge to trading book exposures to credit-risk related and often illiquid products.

*Source: IMF Staff.*

### 19.      Sensitivity tests indicate that the default of large exposures could impact banks

### _cr1554 - 19.      Sensitivity tests indicate that the default of large exposures could impact banks

### Large-exposure sensitivity findings
- Total exposure to the five largest non-financial borrowers was around 35 percent of total CET1 capital.
- A default by all the five non-financial borrowers would lower the CET1 ratio by 1 percent.
- Aggregate exposure to the five largest financial borrowers amounted to 50 percent of CET1 capital.
- The CET1 ratio would decline by 1.9 percent due to a jump in default losses owing to the failure of all the five financial borrowers.
- In particular, one bank would lose almost all of its equity if the shocks were realized.
- Banks regarded the shock as extreme because these were exposures to top tier entities and highly regulated banks in South Africa and abroad, and they were partly held to meet liquidity needs.
- Banks assumed different LGDs: average LGDs are 27 percent for non-financial borrowers and 54 percent for financial borrowers.

### Interest-rate sensitivity on unsecured credit and mortgages (BU STs)
- Unsecured credit exposures due to higher interest rates:
  - Interest rate increases of 100 bps correspond to expected losses of 9.0 percent of total capital.
  - Interest rate increases of 500 bps correspond to expected losses of 9.9 percent of total capital.
  - Considering the level of provisions, these losses translate into reductions of 1.8 percent and 2.2 percent of total capital for the 100 bps and 500 bps shocks, respectively.
  - Banks noted limited impact partly because unsecured lending combined floating-rate and fixed-rate loans and because large-bank customer bases are high-income professionals and/or government employees.
- Floating-rate mortgage portfolio:
  - A 100 bps interest-rate increase would correspond to expected losses of 6.2 percent of total capital and a capital level decline of 0.8 percent.
  - A 500 bps increase would correspond to expected losses of 6.9 percent of total capital and a capital level decline of 1.5 percent.
  - The limited impact is attributed to the good quality of customers.
- Caveats of sensitivity tests:
  - Sensitivity analyses of interest rate shocks only account for changes in interest rates without including increases in unemployment or declines in house and asset prices.
  - Sensitivity analyses usually assess the impact over a 12-month horizon and hence lagged effects beyond 12 months are not considered.
- Note: The 9.0 and 9.9 percent include the expected losses under the current business condition and the added losses caused by the higher interest rates.

### Market risk on trading and fair-valued banking books
- Single-factor shocks on trading and fair-valued banking books produce limited losses.
- The most adverse outcome: failure of the three largest counterparty exposures would reduce the system CET1 ratio by 28 bps, with the highest impact on one bank being 42 bps.
- Limited impact attributed to hedging practices, daily monitoring, and some banks following long gamma strategies that benefit from increased currency or equity price fluctuations.
- Concern: success of long gamma strategies relies on solvency and creditworthiness of trading counterparties, raising counterparty risk and diversification concerns.

### Interest-rate risk on the banking book
- Banks remain asset sensitive, accumulating ZAR 235 billion of net, cumulative interest sensitive assets over a 6 to 12 month horizon.
- A downward parallel move of the interest rate by 200 bps causes the CET1 ratio to fall by 32 bps.
- An upward parallel move of rates by 200 bps would benefit banks by 36 bps.
- Basis risk: assets are linked to the prime rate and liabilities are based on JIBAR.
- The CET1 ratio would decline, on average, by 18 bps if the spread narrows by 50 bps.

### Insurance sector stress-test results
- Participating life insurers:
  - Median CAR coverage ratio declines from 317 percent at end-2013 to 125 percent immediately after the shock (assumed at the beginning of 2014).
  - One company’s CAR coverage drops below 100 percent with a capital shortfall of ZAR 4 billion, corresponding to 4 percent of the ST sample’s available capital before stress, or 0.1 percent of GDP.
  - By end-2014, median CAR coverage reverts to 177 percent; by end-2018 the ratio is expected to stand at 300 percent.
  - Recovery driven by operating profits and the assumption that no new business is underwritten (reducing variable costs).
- Participating non-life insurers:
  - Median CAR coverage ratio drops from 175 percent at end-2013 to 138 percent immediately after the shock, with one company below 100 percent.
  - Capital shortfall amounts to 2 percent of participating non-life companies’ available capital before stress.
  - By end-2014, median CAR coverage expected to increase to 151 percent, surpassing pre-stress levels in 2015; by end-2018 rises to 218 percent.
- Net income impact:
  - Life insurers: aggregated profit of the five life insurers declines by 58 percent to ZAR 9 billion in 2014 (after ZAR 21 billion in 2013). Only one of the five life companies records a loss in 2014. Median RoE increases slightly from 16.5 percent in 2013 to 17.6 percent in 2014. Annual net income expected to fluctuate around ZAR 16 billion in 2015–2018, with all five companies reporting positive earnings from 2015 onwards.
  - Non-life insurers: aggregated net income declines by 37 percent in 2014 and median RoE drops from 22.3 percent to 16.8 percent.
- Main contributors to solvency deterioration:
  - Life insurers: equity shock reduces available capital on average by 28 percent; default of the largest banking counterparty reduces available capital by about 23 percent; interest rate shock also has a substantial impact.
  - Non-life insurers: equity shock reduces available capital by 19 percent on average; banking default would cause a reduction in available capital of 13 percent. Liabilities are unchanged due to statutory rules; required capital remains constant.
- Catastrophe sensitivity:
  - Assuming a 1-in-100 year catastrophic loss, solvency ratios decline by 14 percentage points on average for large non-life companies, due to wide-ranging reinsurance coverage with foreign reinsurers.
  - The main modeled risk is a strong earthquake in the Johannesburg region.
- Risk-sharing and buffers:
  - Life insurers can pass investment losses partially to policyholders by reducing and smoothing bonus allocations.
  - South African life insurers held high levels of capital in recent years; a prolonged period of lower or negative investment returns could diminish this buffer.
- Table excerpt (changes in available and required capital, in million ZAR):
  - Life insurers pre-stress: Assets 1,481; Liabilities 1,376; Excess assets 105; Required capital 324.
  - Life insurers post-stress: Assets 1,015; Liabilities 966; Excess assets 48; Required capital 25.
  - Percentage changes for life insurers: Assets -31%; Liabilities -30%; Excess assets -54%; Required capital -25%.
  - Non-life pre-stress: Assets 353; Liabilities 202; Excess assets 151; Required capital 99.
  - Non-life post-stress: Assets 30; Liabilities 200; Excess assets 15; Required capital 9.
  - Percentage changes for non-life insurers: Assets -15%; Liabilities 0%; Excess assets -35%; Required capital -90%.

### Aggregation of banking and insurance stresses
- On a conglomerate level, financial institutions could weather combined losses from banking and insurance operations.
- Recapitalization needs:
  - Banking recapitalization need at the maximum is 1.6 percent of nominal GDP.
  - Capital shortfall for insurance companies is 0.1 percent of nominal GDP.
- Recapitalizing insurance companies would be within the capacity of corresponding conglomerates given the small size of required capital relative to aggregate group capital.

### Liquidity risk and LCR/NSFR results
- BU STs use Basel III framework and BCBS (2013) and BCBS (2014) regulatory standards to test LCR and NSFR.
- LCR definition and considerations:
  - The LCR measures stock of high-quality assets to total net cash outflow over the next 30 calendar days.
  - Liquidity risk from funding withdrawals by related parties was assessed by imposing a 100 percent run-off rate.
- NSFR definition:
  - NSFR tests whether banks hold minimum acceptable stable funding over one year; ratio of available stable funding to required stable funding.
- LCR compliance:
  - The LCR of five of the six large banks tested was below 100 percent and for some banks below the 60 percent minimum requirement that will become effective from 2015, without using the proposed Committed Liquidity Facility (CLF) of the SARB.
  - Banks and authorities indicated banks have capacity to meet the 60 percent minimum requirement, mainly through selling tri-party repo assets to acquire more HQLA.
- Structural drivers of shortfall:
  - Dependence on wholesale, short-term funding and limited availability of HQLA.
  - In South Africa, 60 percent of bank deposits is wholesale funding from NBFIs and the corporate sector.
  - The average funding maturity has shortened; short-term deposits (6 months in maturity) rose to 63.3 percent of total deposits from 60.3 percent in 2008.
  - Wholesale and short-term funding attract higher run-off rates, increasing liquidity needs in LCR tests.
  - South Africa has a limited pool of level 1 assets and virtually no level 2 assets that satisfy BCBS (2013) criteria.
- Role of the SARB’s CLF:
  - CLF provides up to 40 percent of HQLA and is necessary given insufficient HQLA.
  - Without the CLF, banks would experience a liquidity shortfall in less than 20 days under the tested cash outflow assumptions.
  - Banks indicate plans to increase securitization of home loans to boost collateral eligible for the CLF.

*Source: _cr1554 - 19.      Sensitivity tests indicate that the default of large exposures could impact banks*

### 37.      Regarding the NSFR, all banks except one would have less than 100 percent coverage.

### _cr1554 - 37.      Regarding the NSFR, all banks except one would have less than 100 percent coverage.

### Net Stable Funding Ratio (NSFR) and bank funding
- All banks except one would have less than 100 percent coverage for the NSFR.
- Banks indicated difficulty in fully complying with the minimum NSFR, effective from 2018, given:
  - structural small retail deposit base;
  - difficulty in obtaining long-term funding from the capital markets (partly because it is expensive);
  - funding sourced through the off-shore markets could introduce FX risks.
- Banks may need to reduce the amount of long-term assets to meet the NSFR requirement.
- Banks could consider raising the interest rate offered to attract more retail deposits and obtain more funding with maturity beyond one year.
- Staff analysis on affordability of higher deposit rates:
  - Assuming banks offer an interest rate of 8.7 percent to attract longer term funding, the additional funding cost would amount to ZAR 10 bn per year, equivalent to 1/6 of banks’ after tax profit as of end-2013.
  - Assuming a proportionate reduction in return on equity (ROE), this would imply an ROE of 14 percent.
  - The 8.7 percent rate is 3 percent higher than the historical average deposit rate of 5.7 percent (historical data from 2010Q1 to 2013Q4).
  - The 3 percent spread is greater than the average spread between the government bond yield and deposit rate of 2.7 percent (based on the same historical sample).

### Contagion risk and recent episode (African Bank)
- Contagion risk from the recent failure of African Bank was limited.
- SARB acted decisively in resolving African Bank and in soothing market jitters when some money market funds with exposure to African Bank “broke the buck” in 2014.
- African Bank’s debt accounted for only 1.3 percent of the assets held by the 43 money market funds, yet at least 10 of these funds “broke the buck.”
- Capitec saw only a slight decline in its share price as it was perceived to have a more conservative credit risk policy.
- Market participants recognized that the Moody’s downgrade related to a reduction in the “too big to fail premium,” not to the soundness of the large banks.
- The vulnerability of financial institutions to contagion risk remained low throughout the African Bank episode (Figure 10).
- The vulnerability measure: conditional probability of an institution’s default given the default of another financial institution.

### Recommendations (banking sector stress testing and model validation)
- The SARB should continue to develop a top-down (TD) macro stress testing framework.
  - A TD stress test (ST), to be conducted at least annually, should complement existing bottom-up (BU) exercises conducted by banks.
  - The scenario should be derived from the macroeconomic baseline projection taking the latest risk assessments into account.
- Allocate more resources to the validation of banks’ models and assumptions, as a substantial gap in the TD and BU results was found in this assessment.

### Insurance sector: stress-testing and monitoring recommendations
- Develop a macroprudential stress testing framework for the insurance sector that is:
  - Severe (but plausible): address structural specificities, especially concentrated exposures to domestic banks.
  - Comprehensive: include risk factors not covered by the standard formula of the forthcoming solvency regime, e.g., sovereign risk.
  - Forward-looking: capture long-term dynamics using a multi-year projection horizon and assess feasibility and effectiveness of risk-mitigating strategies.
  - Easy to communicate: each scenario should be based on a clear narrative.
- The FSB, and in the future the prudential regulator, should establish a stringent monitoring framework for assessing concentration risk of the insurance sector towards the largest domestic banks.
  - Request from insurance companies contingency plans that cover financial planning and measures to address operational risks.

### Key stress test and system vulnerability findings (RAM and ST summaries)
- Liquidity risk and NSFR/LCR outcomes:
  - Five out of the six banks maintain LCR and NSFR lower than 100 percent.
  - Some banks are yet to meet the minimum 60 percent target (effective 2015).
  - The SARB’s CLF and banks’ strong capitalization should limit systemic run risks.
- Interconnectedness and spillovers:
  - The financial sector has a high degree of interconnectedness; major banks belong to conglomerates that own banks and NBFIs or own shares in NBFIs.
  - Funding provided by NBFIs to banks is large; concentrated and interconnected market structures mean idiosyncratic shocks can propagate across sectors.
  - Stress test result: failure of banks’ five largest financial borrowers causes the CET1 ratio to decline by 1.9 percentage points.
- Cross-border exposure:
  - Claims of South African banks on Sub-Saharan Africa have tripled over the last five years.
  - Combined African exposure accounts for only 2 percent of banking assets.
- Household and macro vulnerabilities:
  - Banks’ reliance on short-term deposits, which already exceed 60 percent of total deposits, appears to be increasing.
  - Higher interest rates would affect households’ ability to service debt; deterioration in household debt quality would have a large impact on bank capital.
- System-wide resilience in adverse scenarios:
  - Stress tests show capital ratios of banks remain adequate in the adverse scenarios with lower growth and capital outflows.
  - Bottom-up and top-down ST methodologies differ in perimeter, horizon, and assumptions (e.g., six banks included in BU ST covering 93.9 percent of assets vs. four banks in TD ST covering 85.7 percent of assets; BU ST horizon 3-year (2014-2016) vs. TD ST horizon 5-year (2014-2018)).

### Stress testing design elements (selected)
- Banking sector scenarios and shocks:
  - Baseline, adverse, and severely adverse scenarios used for TD and BU STs.
  - Adverse scenario: GDP declines to -1.8 percent in the first year, recovering afterwards and turning positive in 2017 (first year shock corresponds to the 2.5 percent left tail).
  - Severely adverse scenario: three years of negative growth (-3.9, -3.9 and -1 percent from 2015 to 2017, respectively); the “-3.9” percent growth corresponds to the 0.25 percent left tail.
  - BU STs include additional market shocks in 2015 in the severely adverse scenario calibrated to be consistent with those observed in 2008.
- Sensitivity analyses include:
  - Failure of five largest non-financial or financial borrowers;
  - Interest rate shocks affecting floating-rate mortgages and unsecured credit;
  - Market risk shocks: upward parallel moves in rates by 200, 300, and 500 bps, downward move by 200 bps;
  - Widening/narrowing of Prime-JIBAR spread by 50 and 100 bps;
  - Credit spread widenings: 300 and 500 bps for investment grade, 400 and 1000 bps for sub-investment grade, 500 and 2000 bps for speculative grade;
  - FX shocks: depreciation/appreciation of the Rand by 30 and 50 percent;
  - Commodity price shocks: strengthening by 15 and 30 percent, weakening by 15 and 40 percent;
  - Volatility increases: interest rates 50 and 100 percent; equity prices 50 and 100 percent; rand/USD exchange rate 20 and 50 percent; commodity prices 50 and 100 percent.
- Insurance sector calibration highlights:
  - Interest rates: +50 percent parallel shift; sensitivity include -35 percent parallel shift.
  - Equity: -50 percent for ordinary shares, -30 percent for fixed-rate preference shares, -10 percent for variable-rate preference shares.
  - Real estate: -30 percent.
  - FX: 30 percent depreciation of ZAR.
  - Corporate spreads: +173bp (investment grade, advanced economies), +321bp (non-investment grade, advanced economies), +217bp (investment grade, emerging economies), +148bp (non-investment grade, emerging economies).
  - Sovereign spreads: +262bp for South African government bonds.
  - Default of largest banking counterparty: 45 percent LGD on obligations, -100 percent for equity exposures.
  - Sensitivity catastrophe: 1-in-100 years probable maximum loss followed by default of the largest reinsurer (45 percent LGD).

*Source: IMF staff assessment and stress-testing material as presented in the supplied content.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/scr/2015/_cr1554.pdf_