## 1.   Interest Rate, Exchange Rate, Credit Risk Sensitivity Tests, and Credit Risk Tequila

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### Overview
- Presents risk management practices and stress test results for Mexican commercial banks and the insurance sector.
- Stress test results include scenario analyses undertaken as part of the Mexico FSAP update to assess financial system resilience to key risks.
- Scenario analyses are not general equilibrium analysis and are a poor guide if the macro policy framework or financial system diverges fundamentally from the current one.
- Tests performed: sensitivity and scenario analyses based on hypothetical and historical events, primarily using a bottom-up approach.
  - Single shocks measured sudden shifts in key variables (interest rate, exchange rate) by revaluing banks’ balance sheets and tracking impacts on the system’s capital adequacy ratio (CAR).
  - Scenarios assessed simultaneous proportional shifts in groups of macro variables and tracked impacts on commercial banks’ and insurers’ CAR over some simulations with a 12 to 18-month horizon.
- Key conclusion: results point to a resilient private banking and insurance system, though further work is needed on consumer and mortgage credit risk and on coordination for top-down approaches.

### Banking sector — Institutions and risk management practices
- Risk management units of systemically important banks appear independent from treasuries and are charged with:
  - Monitoring liquidity risk under normal and stress scenarios.
  - Proposing market and credit exposure limits in VaR terms.
  - Reporting sensitivity analyses and stress scenarios to Boards regularly.
  - Supporting risk-adjusted credit pricing and monitoring operational risks.
- Each bank chooses its own risk management methodology.
  - Systemically important banks monitor risk taking with Value at Risk (VaR) and backtesting; risk committees must report VaR and stress test results to Boards.
  - Practices supported by internal models, specialized vendors, and foreign headquarters where applicable.

### Banking sector — Supervisors
- Oversight evolved toward a risk-based approach.
- Bank of Mexico (BOM) sets a liquidity coefficient for U.S. dollar operations.
- BOM and Comisión Nacional Bancaria y de Valores (CNBV) perform sensitivity and scenario analyses for credit and market risks and carry out monthly exercises reporting VaR analysis results to Boards.
- Supervisors contact institutions when increases in risk taking are detected to discuss controls.

### Market risk — stress tests and key findings
- Stress tests assessed resilience to a variety of shocks; methodologies and shocks chosen in consultation with the FSAP team and based on historical stress scenarios and peer-country distributions.
- Individual shocks included:
  - Depreciation and appreciation of the peso against the U.S. dollar.
  - Parallel shifts in the term structure of interest rates.
  - Inversion of the yield curve.
  - A sovereign risk shock proxied by a 180 bp increase in the EMBI.
  - A drop in domestic equity prices on trading books.
- Key findings:
  - As of December 2005, exchange rate risk is not the main market risk.
  - A 180 bp increase in the EMBI did not have an appreciable impact on the system’s CAR on average.
  - The most relevant shock is a sharp upward parallel shift in the yield curve; under that shock one bank’s capital drops below the regulatory CAR.
- Tequila and Oil scenarios (CNBV):
  - Shocks calibrated proportionally to those observed up to 12 months from onset of the 1994–95 crisis (Tequila) and the 1997–98 oil price drop (Oil).
  - Tequila scenario affects banks’ capital more severely than the oil scenario.
  - Largest banks would be affected proportionally more but their CAR would not drop below the regulatory CAR due in part to hedging strategies.
  - In the most extreme scenario, on average, large commercial banks lost 40 percent of regulatory capital.
- Peer scenario (CNBV):
  - Peer macro scenario combined: a 180 EMBI+ spread, a 30 percent depreciation in the exchange rate, an increase of 600 bp in the short term (Cete 28) interest rate, and a drop in the U.S. dollar-peso exchange rate by 30 percent.
  - Under the peer scenario the system’s CAR would go down to about 12.9 percent.

### Credit risk — methodology and results
- BOM’s forward-looking default model (CyRCE) is closed form and characterizes the loan portfolio loss distribution by its mean and variance, allowing parameterization of obligor concentration.
- CyRCE VaR formulation and notation preserved in BOM methodology (portfolio F = (f1,..., fN), default probabilities π = (p1,..., pN), default covariance matrix M, confidence level α, Rayleigh’s Quotient, concentration index H(F), etc.).
- BOM traced impact on commercial banks’ CAR of shocks to default rates of the corporate sector across activities: agriculture; commerce; construction; communications and transportation; services; industrial activity.
  - Default rates estimated for December 2005 using SENICREB data.
  - Default rates stressed proportionally based on 1994–96 crisis for all sectors and within each bank cumulatively for 18 consecutive months.
  - For expected losses LGD was assumed equal to one hundred percent.
  - A one-month horizon, 99 percent confidence level VaR was calculated for each of 18 months; six-month cumulative expected losses matched peak of the 1994 crisis.
  - Result: at the peak of the stress event (six months after initial trigger), two small banks could see their CAR falling under the regulatory 8 percent.
- Distribution of estimated default probabilities and stressed default probabilities at December 2005 (Number of Banking Institutions):
  - 0-0.10 percent: 0 / 0
  - 0.10-0.25 percent: 5 / 1
  - 0.25-0.50 percent: 16 / 5
  - 0.5-1.00 percent: 3 / 3
  - 1.0-5.0 percent: 0 / 8
  - 5.0-10.0 percent: 0 / 3
  - >10 percent: 0 / 4

### Public sector exposure and sovereign risk
- Commercial banks’ exposure to the public sector has been declining recently but still amounts to about half of commercial banks’ earning assets.
- A sudden shock to sovereign confidence is considered unlikely by private analysts; sovereign risk shock results provide additional comfort.
- Value of government securities remains a function of sustained macro policy discipline.

### Liquidity management and contagion analysis
- BOM classifies assets and liabilities by remaining maturity and computes each bank’s liquidity gap at 8- and 30-day intervals.
- "Normal scenario" assumptions:
  - Withdrawal of deposits each bank faces in a month = maximum drop in deposits experienced during the last nine years.
  - Remaining deposits assumed fairly stable based on internal analysis.
- Stress scenario assumptions:
  - Idiosyncratic run of large depositors (balances exceeding insured limit): all large demand deposits assumed withdrawn within 30 days; time deposits assumed held to maturity.
- BOM’s estimates suggest an adequate and stable liquidity buffer even under the stress scenario (Figure 1).
- Proportion of liquid assets to total assets, and to short-term liabilities remains at high levels and stable.
- Contagion analysis:
  - BOM constructs a matrix of bilateral daily bank exposures (net loans, securities, credit lines, foreign exchange transactions, net positions in OTC forwards).
  - A bank failure triggers contagion if it causes one or more institutions’ CAR below 4 percent.
  - Based on 2005 daily data, contagion did not appear systemic: a relatively small number of institutions, representing a small share of sector assets, would end up with CAR below 4 percent.

### Recommendations (banking sector)
- Build a macro model to generate sensible shocks and scenarios for financial sector vulnerability analysis, incorporating key financial sector variables to capture feedback effects from the financial system to the real sector.
  - Achieve through coordination between BOM research and credit risk units, and between CNBV and the treasury’s macro unit for top-down approaches.
- Coordinate BOM, CNBV, and commercial banks on a specific set of shocks and scenarios to be analyzed with banks’ own methodologies and request test results to cross-check.
- Improve analysis of credit risk from consumer and mortgage lending by enhancing default history data for these sectors.
  - Consumer and mortgage credit share of commercial banks’ assets: on average around 15 percent.
  - Household indebtedness to household disposable income: 17 percent.
- Combine hypothetical run-on-deposits analysis with an interest rate shock, since liquidity stress scenarios are often associated with increases in interest rates.
- Strengthen liquidity stress analysis by introducing less favorable assumptions on withdrawals of time deposits.

### Insurance sector — stress testing and solvency
- Dynamic solvency exercise coordinated with supervisor Comisión Nacional de Seguros y Fianzas (CNSF) performed on the universe of insurance companies’ balance sheet exposures as of December 2005.
- CNSF implemented a dynamic solvency model using historical data to construct claim distributions for different lines of business.
  - Model allows calculation of probability of bankruptcy by stressing variables affecting underwriting and profit.
  - Output guides supervisory conversations to monitor adequacy of reserves.
- Solvency regulation has evolved to include projections of liabilities to better assess reserve adequacy and moves toward Solvency II-style statutory solvency rules.

### Insurance sector: sensitivity tests and scenario analysis
- Method:
  - The CNSF conducted a series of sensitivity tests and scenario analysis based on a forward-looking, dynamic solvency testing models developed internally.
- Individual shocks and scenarios included:
  - no premium growth in nominal terms (premium shock);
  - an interest rate drop by 190 basis points in peso rates, 114 basis points in UDI rates and 114 basis points in the reference foreign interest rate;
  - premiums shock plus loss rate increases;
  - premiums shock plus interest rate shock plus rate shock (combined scenario).
- Key results (Table 5):
  - Number of insurance institutions with a solvency ratio below 1 percent:
    - increases from 4 as of December 2005 to 11 under the combined scenario.
  - These institutions represent only about 7 percent of the market solvency requirement.
- Solvency ratio distribution (number of insurance companies):
  - Solvency ratio as of December 2005:
    - More than 1.5: 43
    - between 1.3-1.5: 4
    - between 1.1-1.3: 4
    - between 1.0-1.1: 5
    - below 1: 4
  - After Premiums Shock:
    - More than 1.5: 44
    - between 1.3-1.5: 0
    - between 1.1-1.3: 4
    - between 1.0-1.1: 4
    - below 1: 6
    - % of insurance companies below solvency ratio of 1: 13.3
    - Capital insufficiency as % of market solvency requirement: 2.7
  - After Interest rate Shock:
    - More than 1.5: 44
    - between 1.3-1.5: 0
    - between 1.1-1.3: 2
    - between 1.0-1.1: 5
    - below 1: 8
    - % of insurance companies below solvency ratio of 1: 15
    - Capital insufficiency as % of market solvency requirement: 3.4
  - After Loss rate Shock:
    - More than 1.5: 44
    - between 1.3-1.5: 0
    - between 1.1-1.3: 1
    - between 1.0-1.1: 5
    - below 1: 9
    - % of insurance companies below solvency ratio of 1: 16.7
    - Capital insufficiency as % of market solvency requirement: 5.7
  - Scenario (Premiums shock + Interest rate shock + Loss rate shock):
    - More than 1.5: 41
    - between 1.3-1.5: 3
    - between 1.1-1.3: 1
    - between 1.0-1.1: 4
    - below 1: 11
    - % of insurance companies below solvency ratio of 1: 18.3
    - Capital insufficiency as % of market solvency requirement: 7.3
- Shock specifics (source notes):
  - Solvency ratio is defined as assets covering capital requirement to capital requirement.
  - No premium growth in nominal terms.
  - Premiums shock + Interest rate fall from current values to: Pesos (5.5%), Foreign currency (4.0%), and Indexed currency (3.5).
  - Premiums shock + Loss rate increase: Life (10%), Accidents and Health (13%), Property and Casualty (20%), Automobile (5%), Catastrophic risks (10%).
  - Premiums shock + Interest rate shock + Loss rate shock.
  - Insurers with solvency ratio below 1 as of December 2055 are currently subject to regularization plans in order to meet regulatory requirements.

### The derivatives exchange (MexDer) stress testing and contingency planning
- MexDer stress test assumptions included:
  - a 100 percent depreciation of the peso-U.S. dollar exchange rate;
  - a 15 percent drop in the IPC;
  - an increase in Cete 91 by 360 basis points;
  - an increase in the TIIE by 270 basis points.
- Findings:
  - Assuming different levels of default on this loss, MexDer found that the resources in each clearing trust in default and those belonging to the same financial group would have sufficed to stem the problem without Mexican Derivatives Exchange Clearinghouse (ASIGNA) having to mutualize any of the losses or to use its own equity.
  - Thus, MexDer’s five-step contingency plan appears adequate.
- MexDer’s five-step contingency plan:
  - (a) drawing from the resources of each of the clearing trusts in default;
  - (b) drawing on the resources of other clearing trusts;
  - (c) ASIGNA using the resources of the clearing fund;
  - (d) ASIGNA requiring the mutualization of the loss using the resources of the rest of the clearing trusts and their minimum equity;
  - (e) ASIGNA contributing from its own equity, if necessary.

### Selected market-risk and banking stress-test highlights
- Table references and figures in source:
  - Table 1 reports CAR effects across several shocks for 27–29 institutions; minimum capital adequacy ratios for banks are 8 percent.
  - Table 2 reports CAR Dec 2005 for commercial banks as 14.31.
  - Table 3a and 3b provide assumptions for “Tequila” and “Oil Crisis” scenarios with percentage changes of average rates across maturities.
  - Table 4a and 4b show Market Risk effects on CAR under “Tequila” and “Oil Crisis” scenarios over horizons of 1 day, 5 days, 1 month, 3 months, 6 months, 12 months.
  - Figure 1: Asset/Liability Ratio for Commercial Banks (Normal and Stress Scenarios), A/L for 30-day maturity band (three-month moving average) from Feb-03 to Dic-05.

*Prepared by Marco Espinosa-Vega. Source: Excerpt from IMF staff report chapter as provided (CNSF, CNBV, MexDer, BOM data reproduced in source).*

### 1.   Interest Rate, Exchange Rate, Credit Risk Sensitivity Tests, and Credit Risk Tequila

### 1.   Interest Rate, Exchange Rate, Credit Risk Sensitivity Tests, and Credit Risk Tequila

### Overview
- The note presents an overview of the risk management practices and stress test results for the Mexican commercial banks and the insurance sector.
- Stress test results include scenario analyses undertaken as part of the Mexico FSAP update to assess financial system resilience to key risks.
- Scenario analyses are not general equilibrium analysis and are a poor guide if the macro policy framework or financial system diverges fundamentally from the current one.
- Tests performed: sensitivity and scenario analyses based on hypothetical and historical events, primarily using a bottom-up approach.
  - Single shocks measured sudden shifts in key variables (interest rate, exchange rate) by revaluing banks’ balance sheets and tracking impacts on the system’s capital adequacy ratio (CAR).
  - Scenarios assessed simultaneous proportional shifts in groups of macro variables and tracked impacts on commercial banks’ and insurers’ CAR over some simulations with a 12 to 18-month horizon.
- Key conclusion: results point to a resilient private banking and insurance system, though further work is needed on consumer and mortgage credit risk and on coordination for top-down approaches.

### Banking sector — Institutions and risk management practices
- Risk management units of systemically important banks appear independent from treasuries and are charged with:
  - Monitoring liquidity risk under normal and stress scenarios.
  - Proposing market and credit exposure limits in VaR terms.
  - Reporting sensitivity analyses and stress scenarios to Boards regularly.
  - Supporting risk-adjusted credit pricing and monitoring operational risks.
- Each bank chooses its own risk management methodology.
  - Systemically important banks monitor risk taking with Value at Risk (VaR) and backtesting; risk committees must report VaR and stress test results to Boards.
  - Practices supported by internal models, specialized vendors, and foreign headquarters where applicable.

### Banking sector — Supervisors
- Oversight evolved toward a risk-based approach.
- Bank of Mexico (BOM) sets a liquidity coefficient for U.S. dollar operations.
- BOM and Comisión Nacional Bancaria y de Valores (CNBV) perform sensitivity and scenario analyses for credit and market risks and carry out monthly exercises reporting VaR analysis results to Boards.
- Supervisors contact institutions when increases in risk taking are detected to discuss controls.

### Market risk — stress tests and key findings
- Stress tests assessed resilience to a variety of shocks; methodologies and shocks chosen in consultation with the FSAP team and based on historical stress scenarios and peer-country distributions.
- Individual shocks included:
  - Depreciation and appreciation of the peso against the U.S. dollar.
  - Parallel shifts in the term structure of interest rates.
  - Inversion of the yield curve.
  - A sovereign risk shock proxied by a 180 bp increase in the EMBI.
  - A drop in domestic equity prices on trading books.
- Key findings:
  - As of December 2005, exchange rate risk is not the main market risk.
  - A 180 bp increase in the EMBI did not have an appreciable impact on the system’s CAR on average.
  - The most relevant shock is a sharp upward parallel shift in the yield curve; under that shock one bank’s capital drops below the regulatory CAR.
- Tequila and Oil scenarios (CNBV):
  - Exercises assessed sensitivity of trading books to simultaneous valuation changes (inflation, domestic and international equity prices, interest rates).
  - Shocks calibrated proportionally to those observed up to 12 months from onset of the 1994–95 crisis (Tequila) and the 1997–98 oil price drop (Oil).
  - Tequila scenario affects banks’ capital more severely than the oil scenario.
  - Largest banks would be affected proportionally more but their CAR would not drop below the regulatory CAR due in part to hedging strategies.
  - In the most extreme scenario, on average, large commercial banks lost 40 percent of regulatory capital.
- Peer scenario (CNBV):
  - Shocks based on historical volatility for peer countries with S&P sovereign ratings BBB-, BBB and BBB+ (Bulgaria, Croatia, Malaysia, Poland, South Africa, Tunisia).
  - Peer macro scenario combined: a 180 EMBI+ spread, a 30 percent depreciation in the exchange rate, an increase of 600 bp in the short term (Cete 28) interest rate, and a drop in the U.S. dollar-peso exchange rate by 30 percent.
  - Under the peer scenario the system’s CAR would go down to about 12.9 percent.

### Credit risk — methodology and results
- BOM’s forward-looking default model (CyRCE) is closed form and characterizes the loan portfolio loss distribution by its mean and variance, allowing parameterization of obligor concentration.
- CyRCE VaR formulation and notation preserved in BOM methodology (portfolio F = (f1,..., fN), default probabilities π = (p1,..., pN), default covariance matrix M, confidence level α, Rayleigh’s Quotient, concentration index H(F), etc.).
- BOM traced impact on commercial banks’ CAR of shocks to default rates of the corporate sector across activities: agriculture; commerce; construction; communications and transportation; services; industrial activity.
  - Default rates estimated for December 2005 using SENICREB data.
  - Default rates stressed proportionally based on 1994–96 crisis for all sectors and within each bank cumulatively for 18 consecutive months.
  - For expected losses LGD was assumed equal to one hundred percent.
  - A one-month horizon, 99 percent confidence level VaR was calculated for each of 18 months; six-month cumulative expected losses matched peak of the 1994 crisis.
  - Result: at the peak of the stress event (six months after initial trigger), two small banks could see their CAR falling under the regulatory 8 percent.
- Distribution of estimated default probabilities and stressed default probabilities at December 2005 (Number of Banking Institutions):
  - Range Default Probability Dec-05 / Stressed Default Probability Dec-05
  - 0-0.10 percent: 0 / 0
  - 0.10-0.25 percent: 5 / 1
  - 0.25-0.50 percent: 16 / 5
  - 0.5-1.00 percent: 3 / 3
  - 1.0-5.0 percent: 0 / 8
  - 5.0-10.0 percent: 0 / 3
  - >10 percent: 0 / 4

### Public sector exposure and sovereign risk
- Commercial banks’ exposure to the public sector has been declining recently but still amounts to about half of commercial banks’ earning assets.
- A sudden shock to sovereign confidence is considered unlikely by private analysts; sovereign risk shock results provide additional comfort.
- Value of government securities remains a function of sustained macro policy discipline.

### Liquidity management and contagion analysis
- BOM classifies assets and liabilities by remaining maturity and computes each bank’s liquidity gap at 8- and 30-day intervals.
- "Normal scenario" assumptions:
  - Withdrawal of deposits each bank faces in a month = maximum drop in deposits experienced during the last nine years.
  - Remaining deposits assumed fairly stable based on internal analysis.
- Stress scenario assumptions:
  - Idiosyncratic run of large depositors (balances exceeding insured limit): all large demand deposits assumed withdrawn within 30 days; time deposits assumed held to maturity.
- BOM’s estimates suggest an adequate and stable liquidity buffer even under the stress scenario (Figure 1).
- Proportion of liquid assets to total assets, and to short-term liabilities remains at high levels and stable.
- Contagion analysis:
  - BOM constructs a matrix of bilateral daily bank exposures (net loans, securities, credit lines, foreign exchange transactions, net positions in OTC forwards).
  - A bank failure triggers contagion if it causes one or more institutions’ CAR below 4 percent.
  - Based on 2005 daily data, contagion did not appear systemic: a relatively small number of institutions, representing a small share of sector assets, would end up with CAR below 4 percent.

### Recommendations (banking sector)
- Build a macro model to generate sensible shocks and scenarios for financial sector vulnerability analysis, incorporating key financial sector variables to capture feedback effects from the financial system to the real sector.
  - Achieve through coordination between BOM research and credit risk units, and between CNBV and the treasury’s macro unit for top-down approaches.
- Coordinate BOM, CNBV, and commercial banks on a specific set of shocks and scenarios to be analyzed with banks’ own methodologies and request test results to cross-check.
- Improve analysis of credit risk from consumer and mortgage lending by enhancing default history data for these sectors.
  - Consumer and mortgage credit share of commercial banks’ assets: on average around 15 percent.
  - Household indebtedness to household disposable income: 17 percent.
- Combine hypothetical run-on-deposits analysis with an interest rate shock, since liquidity stress scenarios are often associated with increases in interest rates.
- Strengthen liquidity stress analysis by introducing less favorable assumptions on withdrawals of time deposits.

### Insurance sector — stress testing and solvency
- Dynamic solvency exercise coordinated with supervisor Comisión Nacional de Seguros y Fianzas (CNSF) performed on the universe of insurance companies’ balance sheet exposures as of December 2005.
- CNSF implemented a dynamic solvency model using historical data to construct claim distributions for different lines of business.
  - Model allows calculation of probability of bankruptcy by stressing variables affecting underwriting and profit.
  - Output guides supervisory conversations to monitor adequacy of reserves.
- Solvency regulation has evolved to include projections of liabilities to better assess reserve adequacy and moves toward Solvency II-style statutory solvency rules.

*Prepared by Marco Espinosa-Vega.*

### 20.      The insurance sector appears resilient to severe shocks. The CNSF conducted a

### 20.      The insurance sector appears resilient to severe shocks. The CNSF conducted a

### Insurance sector: sensitivity tests and scenario analysis
- Method:
  - The CNSF conducted a series of sensitivity tests and scenario analysis based on a forward-looking, dynamic solvency testing models developed internally.
- Individual shocks and scenarios included:
  - no premium growth in nominal terms (premium shock);
  - an interest rate drop by 190 basis points in peso rates, 114 basis points in UDI rates and 114 basis points in the reference foreign interest rate;
  - premiums shock plus loss rate increases;
  - premiums shock plus interest rate shock plus rate shock (combined scenario).
- Key results (Table 5):
  - Number of insurance institutions with a solvency ratio below 1 percent:
    - increases from 4 as of December 2005 to 11 under the combined scenario.
  - These institutions represent only about 7 percent of the market solvency requirement.
- Table 5 detailed solvency outcomes (Solvency Ratio After Shocks):
  - Solvency ratio as of December 2005: distribution by solvency bands (number of insurance companies)
    - More than 1.5: 43
    - between 1.3-1.5: 4
    - between 1.1-1.3: 4
    - between 1.0-1.1: 5
    - below 1: 4
  - After Premiums Shock:
    - More than 1.5: 44
    - between 1.3-1.5: 0
    - between 1.1-1.3: 4
    - between 1.0-1.1: 4
    - below 1: 6
    - % of insurance companies below solvency ratio of 1: 13.3
    - Capital insufficiency as % of market solvency requirement: 2.7
  - After Interest rate Shock:
    - More than 1.5: 44
    - between 1.3-1.5: 0
    - between 1.1-1.3: 2
    - between 1.0-1.1: 5
    - below 1: 8
    - % of insurance companies below solvency ratio of 1: 15
    - Capital insufficiency as % of market solvency requirement: 3.4
  - After Loss rate Shock:
    - More than 1.5: 44
    - between 1.3-1.5: 0
    - between 1.1-1.3: 1
    - between 1.0-1.1: 5
    - below 1: 9
    - % of insurance companies below solvency ratio of 1: 16.7
    - Capital insufficiency as % of market solvency requirement: 5.7
  - Scenario (Premiums shock + Interest rate shock + Loss rate shock):
    - More than 1.5: 41
    - between 1.3-1.5: 3
    - between 1.1-1.3: 1
    - between 1.0-1.1: 4
    - below 1: 11
    - % of insurance companies below solvency ratio of 1: 18.3
    - Capital insufficiency as % of market solvency requirement: 7.3
- Shock specifics (as defined in source notes):
  - 1/ Solvency ratio is defined as assets covering capital requirement to capital requirement.
  - 2/ No premium growth in nominal terms.
  - 3/ Premiums shock + Interest rate fall from current values to: Pesos (5.5%), Foreign currency (4.0%), and Indexed currency (3.5).
  - 4/ Premiums shock + Loss rate increase: Life (10%), Accidents and Health (13%), Property and Casualty (20%), Automobile (5%), Catastrophic risks (10%).
  - 5/ Premiums shock + Interest rate shock + Loss rate shock.
  - 6/ Insurers with solvency ratio below 1 as of December 2055 are currently subject to regularization plans in order to meet regulatory requirements.

### The derivatives exchange (MexDer) stress testing and contingency planning
- MexDer stress test assumptions included:
  - a 100 percent depreciation of the peso-U.S. dollar exchange rate;
  - a 15 percent drop in the IPC;
  - an increase in Cete 91 by 360 basis points;
  - an increase in the TIIE by 270 basis points.
- Findings:
  - Assuming different levels of default on this loss, MexDer found that the resources in each clearing trust in default and those belonging to the same financial group would have sufficed to stem the problem without Mexican Derivatives Exchange Clearinghouse (ASIGNA) having to mutualize any of the losses or to use its own equity.
  - Thus, MexDer’s five-step contingency plan appears adequate.
- MexDer’s five-step contingency plan (order of measures in case of a default on the loss under a stress scenario):
  - (a) drawing from the resources of each of the clearing trusts in default;
  - (b) drawing on the resources of other clearing trusts;
  - (c) ASIGNA using the resources of the clearing fund;
  - (d) ASIGNA requiring the mutualization of the loss using the resources of the rest of the clearing trusts and their minimum equity;
  - (e) ASIGNA contributing from its own equity, if necessary.

### Selected related market-risk and banking stress-test highlights (tables and figures referenced)
- Table 1 (Interest Rate, Exchange Rate, Credit Risk Sensitivity Tests, and Credit Risk “Tequila” Scenario): reports CAR effects across several shocks for 27–29 institutions, including counts above minimum CAR and below minimum CAR; minimum capital adequacy ratios for banks are 8 percent.
- Table 2 (Interest Rate, Exchange Rate, Sovereign Risk, Sensitivity Analysis and “Peer” Scenario): shows CAR before and after shocks for commercial banks and for Banca Múltiple I and II; CAR Dec 2005 for commercial banks reported as 14.31.
- Table 3a and 3b: provide assumptions for market risk under “Tequila” and “Oil Crisis” scenarios with percentage changes of average rates across maturities for variables including Mexican stock market price index, exchange rate, Treasury certificates, U.S. T-bills, U.S. bonds, LIBOR rates, and Consumer Price Index (domestic).
- Table 4a and 4b: show Market Risk effects on CAR under “Tequila” and “Oil Crisis” scenarios over horizons of 1 day, 5 days, 1 month, 3 months, 6 months, 12 months for Banca Comercial, Banca Múltiple I, and Banca Múltiple II.
- Figure 1: Asset/Liability Ratio for Commercial Banks (Normal and Stress Scenarios), A/L for 30-day maturity band (three-month moving average) from Feb-03 to Dic-05; source BOM.

*Source: Excerpt from IMF staff report chapter as provided (CNSF, CNBV, MexDer, BOM data reproduced in source).*

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