## cr17342

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### Executive summary — structure and recent developments
- Financial system assets were 14 percent lower than in 2007, largely due to deleveraging of bank assets.
- Number of institutions fell to 220 from 336 following mergers and acquisitions.
- Contribution of the financial sector to employment and GDP declined by 5 and 33 percent respectively.
- Financial system assets stand at 360 percent of GDP.
- The system remains bank-dominated: the 14 Significant Institutions (SIs) account for more than 90 percent of banking sector assets.
- Spanish banks operate a universal model with strong retail orientation:
  - Mortgages: 44 percent of loans.
  - Loans to non-financial corporates (NFCs): 41 percent of loans.
  - Consumer credit and other loans: 15 percent of loans.
- Since 2012 recovery included increased capital, ECB long-term funding, and consolidation; however legacy assets and remaining vulnerabilities persist.

### Stress testing approach and scope
- FSAP stress tests employ a macroprudential, Top-Down (TD) framework focusing on system resilience over a three-year horizon (2017–2019); reference date: December 2016.
- Solvency TD tests used satellite models to forecast credit losses and other profit/loss items; ECB credit risk benchmarks were also used.
- Liquidity TD tests included maturity ladder (cash-flow based) analyses and LCR/NSFR-type assessments.
- IMF stress tests covered the 14 SIs; the Bank of Spain (BdE) conducted solvency and liquidity tests for LSIs covering over 95 percent of LSIs.

### Key vulnerabilities and strengths
- Sovereign exposure:
  - Exposures to own sovereign are 8 percent of total assets (second largest in the Euro-Area after Italy; Euro Area average: 5 percent).
- Low profitability:
  - ROE: 5.6 percent in consolidated terms at end-2015.
  - ROE: 4.4 percent for domestic banking.
  - Bank of Spain estimate of cost of capital: 6.8 percent for Spanish banks.
- Nonperforming and non-earning assets:
  - Non-earning assets roughly 7 percent of bank assets as of June 2016.
  - Non-earning assets equal close to 25 percent of total capital, net of provisions.
- Reliance on ECB funding and funding structure fragilities:
  - ECB funding makes up about 6 percent of banks’ total funding (system-wide); ECB funding share in total funding: 8.6 percent (part of 9.6 percent secured wholesale funding).
  - In one case ECB funding represented 17 percent of total funding.
  - Loan-to-deposit ratios largely above 1 for most banks; a few banks have ratios exceeding 120 percent.
  - Use of long-term ECB funding to buy government bonds increased interest rate and sovereign exposures.
- Market and interest-rate risk:
  - Large exposure to fixed income securities creates vulnerability to rapid increases in interest rates and potential trading losses.
- Capital composition risks:
  - Heavy reliance on CET1 elements that will be fully deducted under CRD IV transitional-to-fully-loaded changes.
  - Banks will need to replace roughly 160 bps of phased-out capital in the next three years.
- Strengths mitigating vulnerabilities:
  - CET1 ratio (transitional) at 12.8 percent as of end-2016 compared to 9.2 percent in December 2012.
  - Risk weight density above EU average; NPL provisioning ratio of 58 percent on average.
  - Loan-to-deposit ratio declined to 108 percent in 2016 from 145 percent in 2011.
  - Compliance with phased-in LCR (70 percent in 2016) and expected compliance with fully-loaded requirement in 2018.

### Solvency stress test highlights and outcomes
- Hurdle rates (Fully Loaded ratios as of Dec. 2016):
  - Total Capital ratio: 13.6; Tier I Capital ratio: 11.8; CET1 Capital ratio: 10.9; Leverage ratio: 5.6.
  - Hurdle rate: Total Capital ratio 8.0 + G-SIB/OSII buffer; Tier I Capital ratio 6.0 + G-SIB/OSII buffer; CET1 Capital ratio 4.5 + G-SIB/OSII buffer; Leverage ratio 3.0.
- G-SIB/OSII buffers (Capital Buffer in 2017 / Capital Buffer in 2019):
  - Santander: 0.50 / 1.00
  - BBVA: 0.375 / 0.75
  - Caixabank: 0.125 / 0.25
  - Bankia: 0.125 / 0.25
  - Sabadell: 0.125 / 0.25
  - Popular: 0.125 / 0.25
- System-level capital ratios under adverse scenarios:
  - CAR in 2016 initial level 13.6 percent of RWA; declines to 11.0 percent in scenario 1 and 10.0 percent in scenario 2 by 2019.
  - CET1 for the 14 SIs: declines from 10.9 at end-2016 to 8.5 percent in scenario 1 and 7.4 percent in scenario 2 in 2019.
- Overall capital shortfall:
  - CET1 shortfall amounts to 10.9bn Euros in adverse scenario 1 and 10.4bn in adverse scenario 2, or 1.0 percent of GDP in each adverse scenario.
- Profitability and income effects:
  - Net interest income (NII) declines from 3.9 percent of RWAs in 2016 to 2.4 percent (scenario 1) and 2.5 percent (scenario 2) in 2019.
  - Overall profitability declines from 0.8 percent of RWAs in 2016 to an average of -0.6 percent in 2017–19 in scenario 2; in scenario 1 final profitability falls to -0.9 percent.
- Main contributors to losses: decline in profitability, market losses from sovereign exposures, and credit losses.
- Leverage ratio:
  - System leverage ratio declines from 5.6 percent to 4.7 percent in scenario 1 and to 4.1 percent in scenario 2.
  - Capital shortage of Tier 1 capital in the adverse scenarios equivalent to 9.4 billion euros in both scenarios.

### Sensitivity analysis — selected single-factor shocks and impacts
- Concentration risk:
  - Average single gross largest exposure reaches 15.5 percent of Tier 1 capital; net largest exposure (after collateral and credit risk mitigation) is 5.4 percent.
  - Default of ten largest net exposures would cause several banks to be undercapitalized, translating into a capital shortfall of 0.3 percent of GDP.
  - If exempted corporate exposures were reintegrated and zero-recovery assumed, capital shortfalls for defaults of the largest, five largest and ten largest gross exposures increase to 1.1 percent, 1.5 percent, and 2.4 percent of GDP respectively.
- Sovereign yield shock:
  - A 500 bps increase in sovereign yields decreases system Tier 1 capital by 250 bps; maximum impact up to 890 bps for certain banks.
- Interest rate shock:
  - A 500 bps increase in interest rates reduces system Tier 1 ratio by 120 bps; maximum impact 260 bps for some banks.
- FX shock:
  - A 30 percent depreciation of the euro reduces total Tier 1 capital by 170 bps; maximum impact on an individual bank 530 bps.
- Equity price shock:
  - A 50 percent drop in equity prices reduces system capitalization by 120 bps; maximum impact 360 bps for one bank.
- House price shock:
  - A 50 percent decline in house prices affecting foreclosed assets reduces system-wide capitalization by 90 bps; one bank would see its Tier I ratio fall below the regulatory 6 percent with a 500 bps impact.
- IFRS 9 provisioning sensitivities:
  - A 20 percent increase in each bank’s existing provisions reduces system-wide Tier 1 capital ratio by -100 bps; maximum impact 300 bps for one bank.
  - Imposing a minimum 60 percent provisioning level has a system-wide impact of -60 bps and implies a 350 bps drop in one case.
  - Neither IFRS 9–motivated scenario causes any bank to fall short of regulatory minima.

### Scenario narratives and macro variables (selected)
- Scenario 1 — Financial Stress in Europe:
  - EA output 6.8 percent lower relative to baseline at end-2019; Spain cumulative output shortfall relative to baseline 9.6 percent at end of horizon.
  - Unemployment rises by 2.5 percent relative to baseline at end of horizon.
  - Long-term government bond yields increase 195 bps relative to baseline at the peak; equity prices fall by 23 percent relative to baseline at trough.
- Scenario 2 — De-globalization and Stagnation in Advanced Economies:
  - For Spain, end-of-horizon cumulative output shortfall with respect to baseline is 8.8 percent.
  - Long-term government bond yields rise by 185 basis points compared to baseline at peak; unemployment is 2.4 percentage points higher relative to baseline at peak.
- Macro variables under baseline and adverse scenarios (selected exact entries):
  - Real GDP (2016=100):
    - Adverse Scenario-1: 2017 = 98.1; 2018 = 95.2; 2019 = 96.5
    - Adverse Scenario-2: 2017 = 98.3; 2018 = 95.9; 2019 = 97.3
    - Baseline: 2017 = 102.4; 2018 = 104.6; 2019 = 106.7
  - Long-term government bond yield:
    - Adverse Scenario-1: 2017 = 3.6; 2018 = 4.6; 2019 = 4.8
    - Adverse Scenario-2: 2017 = 3.7; 2018 = 4.4; 2019 = 4.4
    - Baseline: 2017 = 2.2; 2018 = 2.7; 2019 = 3.1
  - Unemployment rate:
    - Adverse Scenario-1: 2017 = 21.0; 2018 = 22.3; 2019 = 22.1
    - Adverse Scenario-2: 2017 = 20.9; 2018 = 21.9; 2019 = 21.7
    - Baseline: 2017 = 17.8; 2018 = 16.8; 2019 = 16.0
  - Nominal GDP growth:
    - Adverse Scenario-1: 2017 = -1.1; 2018 = -4.6; 2019 = -0.8
    - Adverse Scenario-2: 2017 = -1.0; 2018 = -4.1; 2019 = -0.5
    - Baseline: 2017 = 4.0; 2018 = 3.6; 2019 = 3.7
  - Equity price growth:
    - Adverse Scenario-1: 2017 = -17.8; 2018 = -8.8; 2019 = -1.2
    - Adverse Scenario-2: 2017 = -16.8; 2018 = -10.5; 2019 = -4.0
    - Baseline: 2017 = 13.9; 2018 = 0.0; 2019 = 0.0

### Credit risk, PD/LGD methodology and projections
- LGD methodology:
  - Housing-related LGD derived from a country-specific structural model as a function of LTV and liquidation costs (ECB models).
  - Non-real estate segments: fixed multiplier relative to starting LGD (implying an increase of 13 to 18 percent for various portfolios).
  - Sovereign banking book exposures: fixed LGD of 40 percent.
- PD projections:
  - System-wide point-in-time PDs increase multiplier is 2.1 times the starting level.
  - Point-in-time LGDs increase from a weighted-average of 28 percent to 33 percent.
- Median PDs Across Banks (in percent, selected entries):
  - Retail SME: Initial PD 3.3; Scenario 1 Y1 5.9 Y2 7.8 Y3 7.0; Scenario 2 Y1 5.9 Y2 7.8 Y3 6.6
  - Mortgages: Initial PD 1.3; Scenario 1 Y1 2.1 Y2 3.1 Y3 2.7; Scenario 2 Y1 2.1 Y2 3.0 Y3 2.6
  - Corporate: Initial PD 2.1; Scenario 1 Y1 3.1 Y2 3.6 Y3 3.5; Scenario 2 Y1 3.1 Y2 3.7 Y3 3.3
- Credit loss projections and NPLs:
  - Stock of non-accrual loans almost double during the stress test horizon; most of this increase is due to exposures in Spain.
  - NPLs estimated for Brazil and the United Kingdom at an aggregate level where bank-specific historical data was not available.

### Interest income, market losses and valuation channels
- Funding costs and lending rates modeled via a Panel Vector Auto Regression (P-VAR) with short-term Euribor as exogenous.
- Finding: sovereign yields have a positive and significant impact on bank funding rates; estimated coefficients used to calibrate funding cost increases.
- Market valuation losses on debt securities:
  - Interest-rate risk measured using a modified duration approach.
  - Credit risk measured using the PD-LGD approach with sovereign PD and LGDs as in credit risk section.
- Foreclosed assets:
  - Drop in house prices contributes to a 90 bps reduction in Tier 1 capital ratio.

### Liquidity stress tests — LCR, NSFR and cash-flow results
- Funding composition (December 2016):
  - 66 percent of funding comes from retail sight and time deposits.
  - 9.6 percent comes from secured wholesale funding, including funding from the Eurosystem (8.6 percent) and covered bonds.
  - 24.4 percent is unsecured wholesale funding; non-financial corporates contribution to unsecured wholesale funding: 13 percent.
  - Foreign-currency-denominated liabilities share of total liabilities: 92 percent (noting concentration in three banks).
- LCR-based stress test scenarios and exact outcomes:
  - LCR phase-in: 2015 = 60 percent; 2016 = 70 percent; converge to 100 percent by January 2018.
  - Aggregate LCR (standard scenario): 159 percent.
  - Aggregate LCR (secured funding and retail stress): 99 percent; liquidity shortfall €35 billion; 1 percent of banks' assets; 3.1 percent of GDP.
  - Aggregate LCR (wholesale freeze scenario): 89 percent; liquidity shortfall EUR 76 billion; 2.1 percent of banks’ assets; 6.8 percent of GDP.
  - FX aggregate shortfall (USD test): EUR 127 million.
  - Reverse stress test: retail deposit withdrawals would need to reach 20 percent (covered) and 30 percent (uncovered) in a month to bring aggregate liquidity ratio below 100 percent; central bank funding reduction of 50 percent required to induce first bank LCR < 100 percent.
  - System liquid assets: 12 percent of total assets (including on- and off-balance sheet items).
- NSFR results (December 2016):
  - Aggregate available stable funding: EUR 2,287 billion.
  - Aggregate required stable funding: EUR 2,060 billion.
  - Aggregate NSFR: 111 percent.
  - One bank at individual level would experience a liquidity mismatch at the one-year horizon: EUR 2.1 billion, equivalent to 0.2 percent of GDP.
  - Sensitivity: replacement of long-term ECB funding by short-term unsecured wholesale funding would lower aggregate NSFR to 97 percent; aggregate shortfall EUR 54 billion, equivalent to 4.8 percent of GDP; NSFR of weakest bank would drop to 77.5 percent with EUR 25 billion shortfall.
- Outflow (cash-flow) analysis results:
  - All fourteen banks could meet substantial funding gaps up to one year by using:
    - Cash: EUR 45 billion.
    - Selling liquid assets: EUR 32 billion (equivalent to 2.6 percent of the total assets of banks experiencing a gap).
  - Sales mostly during first seven days: EUR 28.5 billion; sales end after three months.
  - Reliance on securities to fund short-term gaps could force fire sales and generate trading losses, creating negative feedback between liquidity and solvency.

### Policy recommendations and supervisory priorities (time horizons and responsibilities preserved where provided)
- Ensure that Pillar II requirements adequately reflect banks’ vulnerability to a further compression in NIMs (¶30).
  - Time: NT
  - Responsibility: ECB/BdE
- Ensure that banks’ Pillar II requirements adequately reflect their ability to withstand interest rate hikes (¶30).
  - Time: NT
  - Responsibility: ECB/BdE
- Ensure that CET1 deductions are replaced in line, and preferably ahead of, transitional arrangements in CRD IV (¶30).
  - Time: NT
  - Responsibility: ECB/BdE
- Ensure the banks improve their overall capital adequacy ratio, via issuance of Tier II and Tier 1 instruments (¶30).
  - Time: I
  - Responsibility: ECB/BdE
- Intensify monitoring of risks other than credit for the SIs (¶30).
  - Time: NT
  - Responsibility: BdE
- Perform liquidity stress tests for various time horizons and take supervisory action if imbalances emerge (¶48).
  - Time: NT
  - Responsibility: ECB/BdE
- Regularly review banks’ plans for ECB unconventional monetary policy exit (see ¶48).
  - Time: NT
  - Responsibility: ECB/BdE
- Improve liquidity monitoring by closing liquidity reporting gaps on a permanent basis with an expanded harmonized EU bank reporting (see ¶48).
  - Time: NT
  - Responsibility: ECB/European Commission
- Monitoring priorities:
  - Continue close monitoring of interest rate and government bond market risks in stress testing.
  - Design a carefully sequenced exit strategy from ECB unconventional monetary policy and search for alternative stable sources of funding.
  - Ramp up monitoring of liquidity, funding, and derivatives-related risks and address liquidity reporting gaps with harmonized EU bank reporting.
  - Leverage the ECB’s 2017 stress test dedicated to interest rate risk on the banking book.

### Institutional coverage, data and modeling details
- Perimeter and institutions included:
  - 14 SIs; 44 LSIs.
  - Market share: 93 percent of total banking sector assets (SIs); nearly 7 percent of total banking sector assets (LSIs).
- Latest data: December 2016; source: supervisory data (COREP/FINREP, BdE).
- NPL projection model (panel AR on logistic-transformed NPL ratio, 2006:Q2–2016:Q4):
  - Estimated coefficients:
    - Lag NPL: 0.29
    - Housing: -3.35
    - Unemployment: 0.11
    - LT rates: -0.22
    - Constant: -2.88
    - R Squared (percent): 89.6
- Sectoral PD / EDF projection models (2005:Q1–2016:Q4):
  - Corporate EDFs — Estimated coefficients:
    - Lag EDF: 0.74
    - Real GDP growth: -0.05
    - Euribor: 0.07
    - Constant: -0.02
  - Financial Institutions EDFs — Estimated coefficients:
    - Lag EDF: 0.76
    - Real GDP growth: -0.02
    - Euribor: 0.03
    - VIX: 0.31
    - Constant: 0.00

*Source: EXECUTIVE SUMMARY and chapter content, Spain FSAP technical note (IMF).*

### EXECUTIVE SUMMARY __________________________________________________________________________ 5

### EXECUTIVE SUMMARY

### Major findings on financial system structure and recent developments
- Financial system assets were 14 percent lower than in 2007, largely due to deleveraging of bank assets.
- Number of institutions fell to 220 from 336 following mergers and acquisitions.
- Contribution of the financial sector to employment and GDP declined by 5 and 33 percent respectively.
- Financial system assets stand at 360 percent of GDP.
- The system remains bank-dominated: the 14 Significant Institutions (SIs) account for more than 90 percent of banking sector assets.
- Spanish banks operate a universal model with strong retail orientation:
  - Mortgages: 44 percent of loans.
  - Loans to non-financial corporates (NFCs): 41 percent of loans.
  - Consumer credit and other loans: 15 percent of loans.
- Since 2012 recovery included increased capital, ECB long-term funding, and consolidation; however legacy assets and remaining vulnerabilities persist.

### Stress testing approach and scope
- FSAP stress tests employ a macroprudential, Top-Down (TD) framework focusing on system resilience to macrofinancial conditions and identification of systemic vulnerabilities rather than microprudential capital adequacy.
- Solvency scenario-based tests assess combined external and domestic shocks over a three-year horizon (2017–2019); reference date: December 2016.
- Solvency TD tests used satellite models to forecast credit losses and other profit/loss items; ECB credit risk benchmarks were also used.
- Liquidity TD tests included maturity ladder (cash-flow based) analyses and LCR/NSFR-type assessments.
- The IMF stress tests covered the 14 SIs; the Bank of Spain (BdE) conducted solvency and liquidity tests for Less Significant Institutions (LSIs) covering over 95 percent of LSIs.

### Key vulnerabilities (enumerated)
- Sovereign exposure:
  - Exposures to own sovereign are 8 percent of total assets (second largest in the Euro-Area after Italy; Euro Area average: 5 percent).
- Low profitability:
  - ROE: 5.6 percent in consolidated terms at end-2015.
  - ROE: 4.4 percent for domestic banking.
  - Bank of Spain estimate of cost of capital: 6.8 percent for Spanish banks.
  - Profitability is negatively affected by relatively higher provisioning ratios compared to European peers.
- Nonperforming and non-earning assets:
  - Non-earning assets roughly 7 percent of bank assets as of June 2016.
  - Non-earning assets equal close to 25 percent of total capital, net of provisions.
  - Problem assets increase further when including SAREB’s portfolio.
- Reliance on ECB funding and funding structure fragilities:
  - ECB funding makes up about 6 percent of banks’ total funding (system-wide).
  - In one case ECB funding represented 17 percent of total funding.
  - Loan-to-deposit ratios are largely above 1 for most banks; a few banks have ratios exceeding 120 percent.
  - The use of long-term ECB funding to buy government bonds (“carry trade”) increased interest rate and sovereign exposures.
- Market and interest-rate risk:
  - Large exposure to fixed income securities creates vulnerability to rapid increases in interest rates and potential trading losses.
- Capital composition risks:
  - Heavy reliance on CET1 elements that will be fully deducted under CRD IV transitional-to-fully-loaded changes.
  - Banks will need to replace roughly 160 bps of phased-out capital in the next three years.

### Solvency and liquidity stress test highlights
- Solvency:
  - Some banks may have difficulty enduring additional pressures on profitability; exposures to sovereign and interest-rate risk could generate large losses as monetary policy normalizes.
  - Sensitivity analyses and scenario tests identified banks with limited ability to absorb further Net Interest Margin (NIM) compression.
- Liquidity:
  - Near-term funding and liquidity risks seem limited; every bank in the FSAP sample meets the standard Liquidity Coverage Ratio (LCR) hurdle rate of 100 percent.
  - Funding risks in foreign currencies are limited; NSFR results indicate limited maturity mismatches at the one-year horizon.
  - However, banks could face liquidity shortfalls in:
    - An extreme event with large retail deposit withdrawals plus a significant reduction in central bank funding over a month.
    - A very severe wholesale funding shock scenario.
  - Cash-flow-based analysis suggests banks could cope with significant net liquidity outflows up to a year by using liquidity buffers, though this could translate into trading losses.

### Policy recommendations (time horizons and responsibilities preserved as in source)
- Ensure that Pillar II requirements adequately reflect banks’ vulnerability to a further compression in NIMs (¶30).
  - Time: NT
  - Responsibility: ECB/BdE
- Ensure that banks’ Pillar II requirements adequately reflect their ability to withstand interest rate hikes (¶30).
  - Time: NT
  - Responsibility: ECB/BdE
- Ensure that CET1 deductions are replaced in line, and preferably ahead of, transitional arrangements in CRD IV (¶30).
  - Time: NT
  - Responsibility: ECB/BdE
- Ensure the banks improve their overall capital adequacy ratio, via issuance of Tier II and Tier 1 instruments (¶30).
  - Time: I
  - Responsibility: ECB/BdE
- Intensify monitoring of risks other than credit for the SIs (¶30).
  - Time: NT
  - Responsibility: BdE
- Perform liquidity stress tests for various time horizons and take supervisory action if imbalances emerge (¶48).
  - Time: NT
  - Responsibility: ECB/BdE
- Regularly review banks’ plans for ECB unconventional monetary policy exit (see ¶48).
  - Time: NT
  - Responsibility: ECB/BdE
- Improve liquidity monitoring by closing liquidity reporting gaps on a permanent basis with an expanded harmonized EU bank reporting (maturity ladder) (see ¶48).
  - Time: NT
  - Responsibility: ECB/European Commission

### Monitoring priorities and supervisory actions suggested
- Continue close monitoring of interest rate and government bond market risks in stress testing given high sovereign and fixed-income exposures.
- Design a carefully sequenced exit strategy from ECB unconventional monetary policy and search for alternative stable sources of funding to reduce dependence on central bank funding.
- Ramp up monitoring of liquidity, funding, and derivatives-related risks and address liquidity reporting gaps with harmonized EU bank reporting.
- Leverage the ECB’s 2017 stress test dedicated to interest rate risk on the banking book.

*Source: EXECUTIVE SUMMARY, Spain FSAP technical note (IMF).*

### 10.      Laying bare these vulnerabilities is the Spanish banks’ moderate capacity to absorb

### 10.      Laying bare these vulnerabilities is the Spanish banks’ moderate capacity to absorb

### Key vulnerabilities and strengths of Spanish banks
- Aggregate solvency has been improving since 2012: CET1 ratio stood (transitional) at 12.8 percent as of end-2016 compared to 9.2 percent in December 2012.
- Spanish banks lag European peers on CET1, particularly on a Fully Loaded basis; the difference between fully-loaded and transitional CET1 is large due to reliance on goodwill and DTAs.
- Strengths mitigating vulnerabilities:
  - Risk weight density of Spanish banks is above average of EU banks due to a larger fraction of assets under the standardized approach and higher risk weights in the IRB portfolio; this increases shock-absorption capacity.
  - NPL provisioning: provisioning ratio of 58 percent on average, with significant dispersion; five banks display a provisioning ratio around 40 percent.
  - The 2014 ECB Asset Quality Review assigned the smallest adjustment to the Spanish banking system CET1 capital among euro area countries; provisions and collateral valuation were deemed broadly appropriate.
  - Funding improvements: loan to deposit ratio declined to 108 percent in 2016 from 145 percent in 2011.
  - Increased issuances of covered bonds and access to capital markets in recent years.
  - Compliance with liquidity coverage ratio: banks were complying with the phased-in requirement of 70 percent in 2016 and should be on time with the fully-loaded requirement in 2018.

### Selected balance-sheet and risk-weight statistics
- Table 2. Average Risk Weights Across IRB portfolios: Spain vs. European Average (June 2016, in percent)
  - Corporate Exposures: Spanish banks 66; European banks 51.8
  - Retail Exposures: Spanish banks 46; European banks 27
  - Mortgage Exposures: Spanish banks 14; European banks 15.5
- In December 2016, credit risk RWAs of 14 SIs accounted for 88 percent of total RWA.
- Market risk RWAs accounted for around 3 percent of RWA; operational risk accounted for around 9 percent of RWA.
- As of December 2016, 61 percent of system-wide RWAs for credit risk were treated under the STA approach.
- Seven of the 14 SIs (10 percent of banking sector assets) use standardized approach only; remaining seven use a combination of IRB and STA.

### Solvency stress tests — scenarios and narratives
- Two extreme but plausible adverse scenarios assessed using the IMF’s GFM model; baseline reflects January 2017 WEO projections.
- Scenario 1 — Financial Stress in Europe:
  - Realization of financial stability risks in the Euro Area with worldwide spillovers; reemergence of stress in high spread euro area economies.
  - Main transmission: government bond market-bank nexus through funding costs; NPLs affected by lower GDP growth and higher unemployment.
  - EA output 6.8 percent lower relative to baseline at end-2019; Spain cumulative output shortfall relative to baseline 9.6 percent at end of horizon.
  - Unemployment rises by 2.5 percent relative to baseline at end of horizon.
  - Long-term government bond yields increase 195 bps relative to baseline at the peak; equity prices fall by 23 percent relative to baseline at trough.
- Scenario 2 — De-globalization and Stagnation in Advanced Economies:
  - Political developments limit or reverse international trade and financial integration; stock-market sell-off; large capital outflows from Turkey and Latin America.
  - For Spain, end-of-horizon cumulative output shortfall with respect to baseline is 8.8 percent.
  - Long-term government bond yields rise by 185 basis points compared to baseline at peak; unemployment is 2.4 percentage points higher relative to baseline at peak.

### Scenario 1 exogenous shocks (selected layers and peak magnitudes)
- Layer 1: Tightening financial conditions in systemic economies, 2017Q1-2018Q2
  - Real equity price, Equity risk premium shocks — China, Euro area, Japan, United Kingdom, United States: -20 percent
  - Money market interest rate spread, Credit risk premium shocks — China: +100 basis points; Euro Area, Japan, United Kingdom, United States: +25 basis points
  - Long-term government bond yield, Duration risk premium shocks — High spread euro area economies: +200 basis points; Japan, United Kingdom, United States: +100 basis points; Low spread euro area economies: +50 basis points
  - Real bilateral exchange rate, Currency risk premium shocks — Euro area: +5 percent
- Layer 2: Fiscal consolidation in the euro area, 2017Q1-2019Q2
  - Primary fiscal balance ratio, Fiscal expenditure shocks — High spread euro area economies: +2 percentage points; Low spread euro area economies: +1 percentage point
- Layer 3: Credit cycle downturns in emerging market economies, 2017Q1-2019Q2
  - Loan default rate, Loan default shocks: 0 to +6.4 percentage points
- Layer 4: Suppressed economic risk taking worldwide, 2017-21
  - Private investment: -4 percent; Private consumption: -1 percent
- Layer 6: Suppressed economic risk taking in Spain, 2017-18
  - Private investment: -4 percent; Private consumption: -1 percent
- Note: High spread euro area economies include Greece, Ireland, Italy, Portugal, and Spain. Low spread euro area economies include Austria, Belgium, Finland, France, Germany, and the Netherlands.

### Scenario 2 exogenous shocks (selected layers and peak magnitudes)
- Layer 1: Risk-off reactions in Europe and the United States, 2017-18
  - Real equity price, Equity risk premium shocks — Euro area, United Kingdom, United States: -20 percent
  - Money market interest rate spread, Credit risk premium shocks — High spread euro area economies, United Kingdom: +100 basis points; Low spread euro area economies, United States: +50 basis points
  - Long-term government bond yield, Duration risk premium shocks — High spread euro area economies: +100 basis points; Exposed emerging market economies: +50 basis points; Low spread euro area economies, United Kingdom, United States: -25 basis points
- Layer 2: Heightened uncertainty in Europe and the United States, 2017-19
  - Private investment shocks — United Kingdom: -2 percent; Euro area, United States: -1 percent
  - Private consumption shocks — United Kingdom: -0.5 percent; Euro area, United States: -0.25 percent
- Layer 3: Balance sheet vulnerabilities in emerging market economies, 2017-19
  - Loan default rate in emerging economies: +0.0 to +3.2 percentage points
- Layer 4: De-globalization in Europe and the United States, 2017-21
  - Private investment — Euro area, United Kingdom, United States: -6 percent; Rest of the World: -3 percent
  - Private consumption — Euro area, United Kingdom, United States: -2 percent; Rest of the World: -1 percent
  - Exports and imports — Euro area, United Kingdom, United States: -20 percent; Rest of the World: -10 percent
  - Productivity — Euro area, United Kingdom, United States: -1 percent; Rest of the World: -0.5 percent
- Layer 5: Pressures on public finance in Spain, 2017-18
  - Long-term government bond yield: +100 basis points
  - Primary fiscal balance ratio: +1 percentage points
- Layer 6: Suppressed economic risk taking in Spain, 2017-18
  - Private investment: -4 percent; Private consumption: -1 percent
- Layer 7: Large capital outflows in Latin America and Turkey, 2017
  - Real equity price: -10 percent; Long-term government bond yield: +100 basis points; Real bilateral exchange rate: +20 percent
- Layer 9: Structurally weak growth in Spain, 2019-21
- Note: Selected economies in Layer 8 include Latin America (Argentina, Brazil, Chile, Colombia, and Mexico), Turkey, the United Kingdom, and the United States.

### Macro variables under baseline and adverse scenarios (Table 5 highlights)
- Real GDP (2016=100)
  - Adverse Scenario-1: 2017 = 98.1; 2018 = 95.2; 2019 = 96.5
  - Adverse Scenario-2: 2017 = 98.3; 2018 = 95.9; 2019 = 97.3
  - Baseline (from WEO): 2017 = 102.4; 2018 = 104.6; 2019 = 106.7
- Short-term money market rate
  - Adverse Scenario-1: 2017 = 0.4; 2018 = 0.5; 2019 = 1.4
  - Adverse Scenario-2: 2017 = 0.8; 2018 = 1.3; 2019 = 2.2
  - Baseline: 2017 = 0.1; 2018 = 0.1; 2019 = 1.0
- Long-term government bond yield
  - Adverse Scenario-1: 2017 = 3.6; 2018 = 4.6; 2019 = 4.8
  - Adverse Scenario-2: 2017 = 3.7; 2018 = 4.4; 2019 = 4.4
  - Baseline: 2017 = 2.2; 2018 = 2.7; 2019 = 3.1
- Exchange rate (EUR/USD)
  - Adverse Scenario-1: 2017 = 0.98; 2018 = 0.99; 2019 = 0.97
  - Adverse Scenario-2: 2017 = 0.94; 2018 = 0.94; 2019 = 0.94
  - Baseline: 2017 = 0.95; 2018 = 0.95; 2019 = 0.95
- Equity price growth
  - Adverse Scenario-1: 2017 = -17.8; 2018 = -8.8; 2019 = -1.2
  - Adverse Scenario-2: 2017 = -16.8; 2018 = -10.5; 2019 = -4.0
  - Baseline: 2017 = 13.9; 2018 = 0.0; 2019 = 0.0
- Inflation rate (CPI)
  - Adverse Scenario-1: 2017 = 1.7; 2018 = -1.3; 2019 = -2.0
  - Adverse Scenario-2: 2017 = 1.5; 2018 = -1.5; 2019 = -1.8
  - Baseline: 2017 = 2.4; 2018 = 1.4; 2019 = 1.5
- Unemployment rate
  - Adverse Scenario-1: 2017 = 21.0; 2018 = 22.3; 2019 = 22.1
  - Adverse Scenario-2: 2017 = 20.9; 2018 = 21.9; 2019 = 21.7
  - Baseline: 2017 = 17.8; 2018 = 16.8; 2019 = 16.0
- Nominal GDP growth
  - Adverse Scenario-1: 2017 = -1.1; 2018 = -4.6; 2019 = -0.8
  - Adverse Scenario-2: 2017 = -1.0; 2018 = -4.1; 2019 = -0.5
  - Baseline: 2017 = 4.0; 2018 = 3.6; 2019 = 3.7

### Stress test design, hurdle rates, and modeling approach
- Scope: solvency stress test covered credit, market and interest rate risk on the banking book, and shocks to profitability; single-factor sensitivity tests complemented scenario-based tests.
- Hurdle rates for solvency stress tests (in percent, fully loaded ratios as of Dec. 2016)
  - As of Dec. 2016 (Fully Loaded ratios): Total Capital ratio 13.6; Tier I Capital ratio 11.8; CET1 Capital ratio 10.9; Leverage ratio 5.6
  - Hurdle rate: Total Capital ratio 8.0 + G-SIB/OSII buffer; Tier I Capital ratio 6.0 + G-SIB/OSII buffer; CET1 Capital ratio 4.5 + G-SIB/OSII buffer; Leverage ratio 3.0
- G-SIB/OSII buffers (in percent)
  - Capital Buffer in 2017 / Capital Buffer in 2019:
    - Santander: 0.50 / 1.00
    - BBVA: 0.375 / 0.75
    - Caixabank: 0.125 / 0.25
    - Bankia: 0.125 / 0.25
    - Sabadell: 0.125 / 0.25
    - Popular: 0.125 / 0.25
- Credit risk modeling:
  - STA exposures: NPL stocks projected bank-by-bank using BdE NPL data; NPL rates regressed on lagged NPLs, housing price, unemployment rate, long interest rates, and bank fixed effects (see Appendix III).
  - IRB exposures: PDs estimated based on Moody’s Expected Default Frequency (EDF) and the ECB’s credit risk models; team lacked access to historical PDs (TTC or PiT), so relied on EDF data and ECB projections.
  - For corporate and institutions portfolios, EDF data used; for mortgages, household consumer credit and sovereign default probabilities, ECB projections used.
  - Given significance of lagged PDs, starting point PDs matter for maximum stress reached in scenarios; sovereign estimates from ECB were scenario dependent only.

*Source: IMF staff calculations and stress test documentation contained in the provided chapter.*

### 18.      Projections of Loss Given Default (LGD) were based on ECB models. The ECB has

### 18.      Projections of Loss Given Default (LGD) were based on ECB models. The ECB has

### Methodology for LGD and PD projections
- LGD for housing-related loan portfolios: derived from a country-specific structural model as a function of loan to value (LTV) ratio and costs associated with liquidation (ECB models).
- Non-real estate segments (corporate and consumer credit): a fixed multiplier relative to the starting point LGD is used (implying an increase of 13 to 18 percent for various portfolios).
- Sovereign banking book exposures: a fixed LGD of 40 percent is employed.
- PD and LGD aggregation: point-in-time PDs and LGDs estimated using credit risk models; PD and LGD averages are very close under the two adverse scenarios due to portfolio composition (IRB portfolios mostly domestic; foreign exposures mostly standardized).

### Credit risk projections and NPLs
- Stock of non-accrual loans almost double during the stress test horizon; most of this increase is due to exposures in Spain.
- NPLs were estimated for Brazil and the United Kingdom at an aggregate level where bank-specific historical data was not available; the increase in NPL ratios was applied to STA exposures for those countries.
- Adverse scenario PD dynamics:
  - System-wide point-in-time PDs increase multiplier is 2.1 times the starting level (with significant variation across exposure types).
  - Point-in-time LGDs increase from a weighted-average of 28 percent to 33 percent.
- Table 7. Median PDs Across Banks (in percent)
  - Retail SME: Initial (median) PD 3.3; Scenario 1 Y1 5.9 Y2 7.8 Y3 7.0; Scenario 2 Y1 5.9 Y2 7.8 Y3 6.6
  - Mortgages: Initial (median) PD 1.3; Scenario 1 Y1 2.1 Y2 3.1 Y3 2.7; Scenario 2 Y1 2.1 Y2 3.0 Y3 2.6
  - Other Retail: Initial (median) PD 2.0; Scenario 1 Y1 2.6 Y2 3.1 Y3 3.1; Scenario 2 Y1 2.6 Y2 3.2 Y3 2.9
  - Corporate: Initial (median) PD 2.1; Scenario 1 Y1 3.1 Y2 3.6 Y3 3.5; Scenario 2 Y1 3.1 Y2 3.7 Y3 3.3

### Interest income and interest rate risk modeling
- Funding cost, growth in funding, and long-term interest rates modeled via a Panel Vector Auto Regression (P-VAR) with short-term Euribor as an exogenous variable.
- Finding: sovereign yields have a positive and significant impact on bank funding rates; estimated coefficients used to calibrate funding cost increases given Euribor and sovereign rate changes.
- Lending rates linked to the 12-month Euribor; deviations from baseline of overnight money market rates projected using the P-VAR and Euro swap curve.
- Interest rate risk on the banking book assessed by time-to-repricing buckets (less than one month up to greater than one year); Spanish banks carry a large positive interest rate risk, implying lost net interest despite an increase in market interest rates.

### Market losses and other valuation channels
- Market valuation losses on debt securities split into:
  - Interest-rate risk: measured using a modified duration approach; for each year sovereign yield curves constructed by linear interpolation of short- and long-term risk-free government bond rates (German bunds). Valuation change approximated by Valuation = -MD ⋅ (MD_y ∂) (formula described).
  - Credit risk: measured using the PD-LGD approach; same sovereign PD and LGDs as in the credit risk section applied to Spanish securities exposures.
- Exchange rate risk: assessed via banks’ net open FX positions against USD, GBP, Mexican peso, Turkish lira; negative net FX position implies direct market losses in case of euro depreciation, but losses are small as open positions are limited.
- Foreclosed assets: losses from a drop in house prices accounted for directly and indirectly (via higher loss rates); this channel contributes to a 90 bps reduction in Tier 1 capital ratio.

### Stress test results — solvency and profitability (summary of main findings)
- System-level capital ratios under adverse scenarios:
  - CAR in 2016 initial level 13.6 percent of RWA; declines to 11.0 percent in scenario 1 and 10.0 percent in scenario 2 by 2019.
  - CET1 for the 14 SIs: declines from 10.9 at end-2016 to 8.5 percent in scenario 1 and 7.4 percent in scenario 2 in 2019.
- Overall capital shortfall:
  - CET1 shortfall amounts to 10.9bn Euros in adverse scenario 1 and 10.4bn in adverse scenario 2, or 1.0 percent of GDP in each adverse scenario (rounded as presented).
- Leverage ratio:
  - System (14 largest banks) leverage ratio declines from 5.6 percent to 4.7 percent in scenario 1 and to 4.1 percent in scenario 2.
  - Capital shortage of Tier 1 capital in the adverse scenarios equivalent to 9.4 billion euros in both scenarios.
- Main contributors to losses: decline in profitability, market losses from sovereign exposures, and credit losses.
  - Net interest margins tighten under both scenarios; net interest income (NII) declines from 3.9 percent of RWAs in 2016 to 2.4 percent (scenario 1) and 2.5 percent (scenario 2) in 2019.
  - Market gains of 0.1 percent of RWA in 2016 turn into a market loss of 0.7 percent in 2017 in scenario 2.
  - Credit loss impairments increase in absolute terms by 7 percent from 2016 to 2018 (peak), but remain roughly constant at 2 percent of RWAs as a share.
- Profitability impact:
  - Overall profitability declines from 0.8 percent of RWAs in 2016 to an average of -0.6 percent in 2017–19 in scenario 2; in scenario 1, final profitability falls to -0.9 percent.
- Table 8. Results of the TD Solvency Stress Test for SIs: Adverse Scenario
  - Aggregate CET1 ratio, Leverage ratio, Max. capital shortfall (% of GDP)
    - Before stress: 10.9% CET1, 5.6% leverage, 0.0% shortfall
    - Baseline scenario: 11.5% CET1, 5.9% leverage, 0.2% shortfall
    - Adverse scenario: 7.4% CET1, 4.1% leverage, 1.0% shortfall

### Sensitivity analysis (selected shocks and impacts)
- Shocks assessed: default of largest exposures (concentration risk), 500 bps sovereign yield shock, 500 bps interest rate shock, 30 percent euro depreciation, 50 percent decline in equity prices, 50 percent decline in house prices (impacting foreclosed assets), 20 percent increase in provisions, minimum 60 percent provisioning rate on nonperforming exposures.
- Concentration risk:
  - Banks can cope with simultaneous default of up to five of their largest exposures on average; some banks vulnerable beyond this.
  - Average single gross largest exposure reaches 15.5 percent of Tier 1 capital; net largest exposure (after collateral and credit risk mitigation) is 5.4 percent.
  - Default of ten largest net exposures would cause several banks to be undercapitalized, translating into a capital shortfall of 0.3 percent of GDP or 0.6 percent of the RWAs of this group.
  - If exempted corporate exposures were reintegrated and zero-recovery assumed on credit risk mitigation, capital shortfalls for defaults of the largest, five largest and ten largest gross exposures increase to 1.1 percent, 1.5 percent, and 2.4 percent of GDP respectively (or between 4.5 percent and 16 percent of RWAs).
- Sovereign yield shock:
  - A 500 bps increase in sovereign yields decreases system Tier 1 capital by 250 bps; maximum impact up to 890 bps for certain banks.
  - Several banks would fall short of the 6 percent Tier I capital ratio; one bank would be essentially at the threshold.
- Interest rate shock:
  - A 500 bps increase in interest rates reduces system Tier 1 ratio by 120 bps; maximum impact 260 bps for some banks. No bank fails regulatory minima solely from this shock.
- FX shock:
  - A 30 percent depreciation of the euro (against all major currencies) reduces total Tier 1 capital by 170 bps; maximum impact on an individual bank 530 bps, causing failure of the 6 percent Tier 1 minimum for that bank.
- Equity price shock:
  - A 50 percent drop in equity prices reduces system capitalization by 120 bps; maximum impact 360 bps for one bank. No bank fails Tier 1 ratio solely from this shock.
- House price shock:
  - A 50 percent decline in house prices affecting foreclosed assets reduces system-wide capitalization by 90 bps; one bank with significant foreclosed assets would see its Tier I ratio fall below the regulatory 6 percent, with a 500 bps impact on its capital-to-RWA ratio.
- IFRS 9 provisioning sensitivities:
  - A 20 percent increase in each bank’s existing provisions reduces system-wide Tier 1 capital ratio by -100 bps; maximum impact 300 bps for one bank.
  - Imposing a minimum 60 percent provisioning level has a system-wide impact of -60 bps and implies a 350 bps drop in one case.
  - Neither IFRS 9–motivated scenario causes any bank to fall short of regulatory minima.

*Source: IMF staff calculations and ECB models as described in source content.*

### 30.      The vulnerability analysis highlights several areas in which Spanish SIs could be made

### 30.      The vulnerability analysis highlights several areas in which Spanish SIs could be made

### Vulnerability analysis — key findings on profitability and risks
- Adverse scenarios would bring additional decline in profitability; supervisors should ensure that Pillar II requirements adequately reflect banks’ vulnerability to a further compression in NIMs.  
- Banks show sensitivity to any additional stresses on profitability while NIMs are already compressed; banks should be able to withstand the potential for continued compressed margins or even their further tightening.  
- Low current profitability is highly determined by large non-interest earning legacy assets; ensuring adequate loan classification and building on recent measures would make banks’ interest income more resilient and free up resources to respond to credit demand. A desirable time-horizon is three years, based on the remaining maturity of ECB liquidity lines. Supervisory action should be concentrated in the most vulnerable banks.  
- Focus on credit risk and legacy assets should not neglect other risks such as interest rate and sovereign risks. Large durations in government bond holdings expose banks to losses from changes in monetary policy or market sentiment about Spanish sovereign credit worthiness. The ECB and BdE include these risks in SREP and TD assessments respectively; continuous monitoring is encouraged.  
- Large deductions from CET1 should be replaced in line, and if possible ahead of, transitional arrangements in CRD IV. Spanish banks rely heavily on non-eligible elements that will be phased out as CRD-IV is implemented, showing one of the largest discrepancies between transitional and fully-loaded measurements of capital in Europe. The banks will need to replace the capital that will be phased out, roughly 160 bps, in the next three years.  
- Spanish banks’ capital is almost entirely in CET1 instruments; while reflecting high quality of capital (notwithstanding the debate regarding DTCs), this makes banks vulnerable to the 8 percent CAR threshold. Banks should continue to strengthen their overall capital adequacy ratio via issuance of Tier II and Tier 1 instruments.

### Liquidity stress tests — approach and scope
- Three types of liquidity stress tests were performed:  
  - LCR-based test (30-day horizon, stock of unencumbered HQLA). The LCR implementation: 2015 phase-in 60 percent, 2016 phase-in 70 percent, converging to 100 percent by January 2018.  
  - NSFR-based test (one-year horizon; informative complement while not yet binding until January 2018).  
  - Cash flow based analysis by maturity buckets (granular analysis using maturities from 1 day to more than a year).  
- Top-down cash-flow liquidity stress tests used supervisory maturity structures as of December 2016 for the same sample of fourteen banks covered in the solvency stress test. Tests aggregated every currency and included separate tests on U.S. dollar and British pound.  
- Foreign currency-denominated liabilities constitute 92 percent of total liabilities, but significant foreign currency exposure is concentrated in three banks whose foreign subsidiaries are locally funded and operate on a standalone basis.

### Banking system funding structure (December 2016)
- 66 percent of funding comes from retail sight and time deposits.  
- 9.6 percent comes from secured wholesale funding, including funding from the Eurosystem (8.6 percent) and covered bonds. Seven banks have a share of Eurosystem funding above 10 percent; one bank peaks at 17 percent.  
- 24.4 percent is unsecured wholesale funding, notably from non-financial corporates (13 percent) and operational deposits generated by clearing, custody, and cash management activities.

### LCR-based stress test — scenarios and assumptions
- Three LCR scenarios were run (aggregating across currencies, with separate FX tests for USD and GBP using standard LCR assumptions):  
  - Standard LCR scenario applying 2013 Basel III LCR parameters.  
  - Secured funding and retail stress scenario: run-off rates raised to 10 percent for stable and 15 percent for unstable retail and wholesale deposits; 20 percent reduction in central bank funding; tailored to replicate a deposit run and reduction in central bank funding.  
  - Wholesale funding stress scenario: complete freeze of wholesale funding on interbank market with run-off rates up to 100 percent for wholesale funding from other legal entity customers; 50 percent rates for operational deposits from clearing/custody/cash management; up to 50 percent outflows by non-financial corporates, central banks and multilateral development banks.  
- Roll-off and inflow assumptions (examples preserved from source): cash inflows from performing loans to non-financial customers assumed to decline by 50 percent in a month; maturing loans to financial institutions assumed to dry up completely (100 percent).  
- Banks were allowed to use sovereign securities as collateral to obtain liquidity through ECB standard lending facilities. At the banking system level, liquid assets equal 12 percent of total assets (including both on- and off-balance sheet items).

### LCR-based stress test — main results
- Under the standard scenario: aggregate LCR = 159 percent in December 2016. Each of the 14 banks passes the 80 percent national 2017 requirement and even the 100 percent hurdle rate binding in 2018. Retail deposit base explains resilience.  
- Under the adverse secured funding and retail scenario: banks lose 10 to 15percent of retail and small business deposits in a month and experience a 20 percent reduction in secured funding (including central bank funding); a 7 percent haircut applied to five-year Spanish government bond value. Four out of 14 banks would fall below the 100 percent LCR hurdle but all would meet the 80 percent rate. Aggregate LCR would fall to 99 percent, translating into a liquidity shortfall of €35 billion, equivalent to 1 percent of banks' assets and to 3.1 percent of GDP. No LSI would experience a liquidity shortfall.  
- Under the wholesale funding dry-up scenario: a loss of wholesale funding by 70 percent leaves most banks able to find alternatives; under a complete freeze (100 percent run-off on unsecured wholesale funding) the aggregate LCR would fall to 89 percent. Total liquidity shortfall would amount to EUR 76 billion, equivalent to 2.1 percent of banks’ assets and 6.8 percent of GDP. Liquidity shortfall for LSIs would be very limited.  
- FX-specific LCR tests (USD, GBP) showed no material shortfalls; a very small EUR 127 million shortfall in U.S. dollars on aggregate. This reflects foreign subsidiaries being locally funded with matching currency denominations.  
- Reverse stress test: retail deposit withdrawals would need to reach 20 percent (covered by guarantee scheme) and 30 percent (uncovered retail deposits) in a month to bring aggregate liquidity ratio below 100 percent. Secured funding from the central bank would have to be reduced by 50 percent for the first bank to display an LCR below 100 percent.

### Selected quantitative outcomes and parameters (preserved exactly)
- ECB funding share in total funding: 8.6 percent (part of 9.6 percent secured wholesale funding).  
- Banks will need to replace roughly 160 bps of capital phased out by CRD-IV within the next three years.  
- CET1-related CAR threshold cited: 8 percent.  
- LCR phase-in: 2015 = 60 percent; 2016 = 70 percent; converge to 100 percent by January 2018.  
- Aggregate LCR (standard scenario): 159 percent.  
- Aggregate LCR (secured funding and retail stress): 99 percent; liquidity shortfall €35 billion; 1 percent of banks' assets; 3.1 percent of GDP.  
- Aggregate LCR (wholesale freeze scenario): 89 percent; liquidity shortfall EUR 76 billion; 2.1 percent of banks’ assets; 6.8 percent of GDP.  
- FX aggregate shortfall (USD test): EUR 127 million.  
- Reverse stress retail withdrawal rates required to breach 100 percent LCR: 20 percent (covered) and 30 percent (uncovered) in a month.  
- Central bank funding reduction required to induce first bank LCR < 100 percent in reverse test: 50 percent.  
- System liquid assets: 12 percent of total assets (including on- and off-balance sheet items).  
- Foreign-currency-denominated liabilities share of total liabilities: 92 percent (noting concentration in three banks).  
- Funding composition: 66 percent retail deposits; 9.6 percent secured wholesale funding; 24.4 percent unsecured wholesale funding.  
- Non-financial corporates contribution to unsecured wholesale funding: 13 percent.

_Italic: IMF staff — content unit from the source PDF chapter/section provided._

### 45.      The liquidity stress test results based on the NSFR do not suggest large maturity

### cr17342 - 45.      The liquidity stress test results based on the NSFR do not suggest large maturity

### NSFR-based Liquidity Stress Test Results
- Aggregate available stable funding for the fourteen largest banks: EUR 2,287 billion (December 2016).
- Aggregate required stable funding for the fourteen largest banks: EUR 2,060 billion (December 2016).
- Aggregate NSFR: 111 percent (above the 100 percent minimum requirement binding in 2018).
- One bank at the individual level would experience a liquidity shortfall from maturity transformation:
  - Liquidity mismatch at the one-year horizon: EUR 2.1 billion, equivalent to 0.2 percent of GDP.
- Sensitivity to replacement of long-term ECB funding by short-term unsecured wholesale funding (based on supervisory data):
  - Aggregate NSFR would fall to 97 percent.
  - Aggregate shortfall in that event: EUR 54 billion, equivalent to 4.8 percent of GDP.
  - NSFR of the weakest bank would drop to 77.5 percent, with a EUR 25 billion liquidity shortfall.
- Observations:
  - Result reflects large reliance of Spanish banks on stable retail deposits.
  - Spanish banks’ NSFR positions might be distorted by extensive use of long-term ECB funding and could become less favorable if that funding had to be replaced by short-term unsecured wholesale funding.

### Outflow Analysis Stress Test: Method and Assumptions
- Maturity buckets used (seven): 1 to 7 days; 8 to 15 days; 16 to 30 days; 31 to 90 days; 91 to 180 days; 180 to 365 days; more than 365 days.
- Exercise captured:
  - (i) banks' liquidity needs from outflows;
  - (ii) available standby liquidity from inflows;
  - (iii) buffers available to counterbalance liquidity gaps.
- Assumed pace of deposit outflows: slowdown as the time horizon increases.
- Counterbalancing capacity (CC) treatment:
  - Liquid assets eligible as central bank collateral subject to a 20 percent haircut.
  - Non-central bank eligible assets subject to a 40 percent haircut.
- Table 11 run-off, roll-off and haircut assumptions (selected entries preserved exactly as in source):
  - Run-off rates on potential outflows:
    - Retail funding: sight deposits — Stable 2% 4% 4% 4% 0% 0% 0%
    - Retail funding: sight deposits — Unstable 8% 6% 6% 3% 0% 0% 0%
    - Retail funding: term deposits 5% 5% 5% 15% 10% 10% 10%
    - Other deposits 10% 10% 10% 10% 10% 10% 10%
    - Secured wholesale funding from other financial institutions 20% 20% 20% 20% 20% 20% 20%
    - Unsecured wholesale funding from other financial institutions 60% 60% 60% 60% 60% 60% 60%
    - Outflows from derivatives 100% 100% 100% 100% 100% 100% 100%
    - Other obligations 50% 50% 50% 50% 50% 50% 50%
  - Roll-off rates on cash inflows:
    - Securities in trading book 100% 100% 100% 100% 100% 100% 100%
    - Available for sale securities 100% 100% 100% 100% 100% 100% 100%
    - Held to maturity securities 100% 100% 100% 100% 100% 100% 100%
    - Inflows from derivatives 100% 100% 100% 100% 100% 100% 100%
    - Loans maturing 60% 60% 60% 60% 60% 60% 60%
    - Other 80% 80% 80% 80% 80% 80% 80%
  - Haircuts on liquid assets:
    - Cash items 0%
    - Securities in trading book 20%
    - Available for sale securities 40%
    - Held to maturity securities 20%

### Outflow Analysis Stress Test: Results and Implications
- Short-term resilience:
  - All fourteen banks would be able to meet substantial funding gaps at different maturity buckets from 1 day to 1 year by using:
    - Cash: EUR 45 billion.
    - Selling liquid assets: EUR 32 billion (equivalent to 2.6 percent of the total assets of banks experiencing a gap).
  - The sale of securities would be mostly during the first seven days: EUR 28.5 billion, and sales would end after three months.
- Implications and vulnerabilities:
  - Indicates a solid liquidity position of Spanish banks in the tested scenario.
  - Reliance on securities to fund short-term gaps could become a vulnerability in distress, potentially forcing fire sales and generating trading losses.
  - Trading losses could create a negative feedback loop between liquidity and solvency risks in a crisis.

### Policy Recommendations (from liquidity stress test findings)
- Main recommendations:
  - Design a carefully planned exit strategy from the ECB unconventional monetary policy.
  - Search for alternative stable sources of funding to reduce heavy reliance on central bank funding.
  - Recognize that replacement of ECB funding with short-term unsecured wholesale funding would be detrimental to Spanish banks’ stability.
  - Identify need for alternative income sources as profitability will be reduced when banks start repaying long-term ECB funding used in carry-trade operations.
- Data and supervisory recommendations:
  - Improve liquidity monitoring by performing liquidity stress tests using the structure of cash flows at various maturities.
  - Close liquidity reporting gaps on a permanent basis with an expanded harmonized EU bank reporting.
  - Collect data needed to compute the maturity ladder on a regular and permanent basis (instead of relying on one-off exercises like the Short-Term Exercise (STE) carried out by the ECB).

### Conclusion: System-wide Resilience and Remaining Vulnerabilities
- Solvency outcomes:
  - CET1 for the 14 SIs declines from 10.9 at end-2016 to 8.1 (7.2) percent in 2019 in adverse scenario 1 (adverse scenario 2).
  - Leverage ratio for the system (14 largest banks) declines from 5.5 percent to 4.1 (3.8) percent in adverse scenario 1 (2); several banks would fall below the 3 percent minimum hurdle.
  - Capital shortage of Tier 1 capital in adverse scenarios: equivalent to 9.4 and 10.5 billion euros respectively in scenarios 1 and 2.
- Sensitivity to market shocks:
  - Two single-factor sensitivity tests with largest impacts on Tier 1 Capital: a government bond yield shock and failure of the 5 largest counterparties.
  - A 500bps increase in sovereign yields decreases the system Tier I capital by 250 bps.
  - Simultaneous failure of the largest 5 counterparties results in a drop of 230 bps in the overall Tier I capital ratio.
- Funding and liquidity risks:
  - Funding from the Eurosystem makes up 9 percent of banks’ total funding.
  - Global liquidity stress tests: every bank in sample meets Liquidity Coverage Ratio hurdle rate of 100 percent.
  - Funding risks in foreign currencies and one-year maturity mismatches based on NSFR appear limited.
  - However, Spanish banks would face liquidity shortfalls in an extreme event with large retail deposit withdrawals and significant reduction in central bank funding over a month.
  - Cash-flow-based analysis: banks can cope with significant net liquidity outflows up to a year by using liquid buffers, but this may translate into trading losses.
- Recommended supervisory focus:
  - Continue reinforcing monitoring of interest rate, government bond yield, liquidity, funding and derivatives related risks.
  - Improve liquidity monitoring by performing liquidity stress tests at various maturities and close liquidity reporting gaps with expanded harmonized EU bank reporting.

*Source: IMF staff calculations, ECB, and supervisory data (chapter content).*

### 1. Institutional

### 1. Institutional

### Perimeter and Institutions Included
- Institutions included:
  - 14 SIs
  - 44 LSIs
- Market share:
  - 93 percent of total banking sector assets
  - Nearly 7 percent of total banking sector assets

### Data and Baseline Date
- Latest data: December 2016.
- Source: supervisory data (COREP/FINREP).
- Scope of consolidation: perimeter of individual banks.
- Latest data: December 2016.
- Source: supervisory data (BdE).
- Scope of consolidation: perimeter of individual banks.

### Methodology (Channels of Risk Propagation)
- Scenario frameworks used:
  - An extended Basel III LCR scenario with variants (retail/wholesale shock).
  - A Basel III NSFR scenario.
  - A cash-flow based scenario analyzing different maturity buckets.
  - An extended Basel III LCR scenario with variants (retail/wholesale shock).

### Risks and Buffers
- Risks:
  - Funding liquidity (liquidity outflows).
  - Market liquidity (price shocks).
  - Funding liquidity (liquidity outflows).
- Buffers:
  - Counterbalancing capacity.
  - Central bank facilities.
  - Counterbalancing capacity.
  - Central bank facilities.

### Tail Shocks (References for Shock Calibration)
- For LCR, see: BCBS (2013), The Liquidity Coverage Ratio and liquidity risk monitoring tools, Basel, January 2013.
- For NSFR, see: BCBS (2014), Basel III: The Net Stable Funding Ratio—Consultative Document, Basel, April 2014.

### Regulatory and Market-Based Standards and Parameters
- Regulatory standards:
  - Basel III liquidity standards for LCR and NSFR

### Reporting and Output Presentation
- Output presentation:
  - Liquidity ratios, disaggregated by type and size of bank
  - Counterbalancing capacity

### NPL Projection Model (Satellite Models for Credit Risk—Technical Details)
- Model specification:
  - Panel auto-regressive regression for logistic-transformed NPL ratio (adjusted overall NPL ratio provided by the BdE).
  - Indexes i (bank) and t (time).
  - NPL denotes the logistic transformation:
    - NPL_i,t = log( NPL_i,t / (1 − NPL_i,t) )
  - X = (HP, U, LT) where:
    - HP denotes the housing price growth
    - U denotes the unemployment rate
    - LT denotes the long-term interest rates
  - The model was estimated using quarterly data for the period 2006:Q2 through 2016:Q4.
- Estimated coefficients (except bank-specific fixed effects):
  - Lag NPL: 0.29
  - Housing: -3.35
  - Unemployment: 0.11
  - LT rates: -0.22
  - Constant: -2.88
  - R Squared (percent): 89.6

### Sectoral PD / EDF Projection Models
- Approach:
  - Regression of EDFs (log transformed) on macro variables on a quarterly basis, including quarterly dummies.
  - Model estimated using quarterly data for the period 2005:Q1 through 2016:Q4.
- Corporate EDFs — Estimated coefficients:
  - Lag EDF: 0.74
  - Real GDP growth: -0.05
  - Euribor: 0.07
  - Constant: -0.02
- Financial Institutions EDFs — Estimated coefficients:
  - Lag EDF: 0.76
  - Real GDP growth: -0.02
  - Euribor: 0.03
  - VIX: 0.31
  - Constant: 0.00

*Source: cr17342 - 1. Institutional (PDF chapter/section).*

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_Source: https://www.imf.org/-/media/files/publications/cr/2017/cr17342.pdf_