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Advanced (Economic) Capital
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                           Michel Rochette, MBA, FSA
                        2009 Valuation Actuary Symposium
                                  Anaheim, CA
                              September 25th 2009
Topics
 General topics:
    Purpose and principles of capital model development
    Major components of a capital model
    Uses of a capital model
 Specialized topics:
    Approaches to building a capital model
    Validation considerations
    Calibration considerations
    Correlation in the tail: diversification
    Emerging risk considerations
25/09/2009                                      Enterprise Risk Advisory LL
Purpose
 ¨ Risk management system of an insurer for the
  analysis of the overall risk situation of the insurance
  undertaking, to quantify risks and determine the
  capital requirement on the basis of the company
  specific risk profile¨ CEA Groupe Consultatif
 Required capital is assessed in light of:
     available capital & other financial resources
     enterprise risk management processes
     strategic goals & risk appetite
     regulatory requirements

25/09/2009                                            Enterprise Risk Advisory LL
Principles
 All material risks should be covered: links to ERM
    and emerging risks
   Models must be appropriate for the scale and
    complexity of the firm
   Models must be dynamic and flexible
   Models must be embedded in the financial, strategic
    and operational processes: Use Test in Solvency II
   Governance of models development:
     Board/top management oversight and involvement
     documentation of models, limitations & changes
      internal controls over development: auditableEnterprise Risk Advisory LL
25/09/2009
Major components
 Exposure models of key risks:
    financial risks & underwriting risks: assets and liabilities
     models cash flows
    non financial risks: operational and business models
    strategic risks: strategic models
 Risk drivers models: ESG, catastrophic, scenarios,
   stochastic, EVT, competitor, behaviour, management
   actions
 Aggregation approaches: correlation with var/cov,
   copulas, none
 Time horizon: short-term view versus run-off
25/09/2009                                    Enterprise Risk Advisory LL
Uses
   Investment decisions: existing and new
   Product development
   Strategic decisions
   Corporate finance decisions: financial leverage
   Hedging strategies
   External events and emerging risks
   Regulatory proposals: CP 37 & CP 56 in Solvency II
     “…widely used and plays an important role in the course
       of conducting an insurer's regular business, particularly
       in risk management. "
25/09/2009                                           Enterprise Risk Advisory LL
Approaches
 Top down economic and business scenarios:
      obtain an overall EC estimates for all risks combined
 Stress tests:
      judgmental and test specific risks and impact on capital
 Stochastic:
      random scenarios and obtain distribution of risks
 Insurance approach:
      Frequency, severity, recovery
 Factor based: used for regulatory
 Others:
25/09/2009                                            Enterprise Risk Advisory LL
      Regression, neural networks, Bayesian, fuzzy logic, EVT
Validation principles
 Integrates both qualitative and quantitative elements
 Provides that the models were designed, work as
   planned and are implemented correctly – quality
   assurance
 Analyses the predictive properties of the models:
   testing against experience, backtesting
 Iterative process to assess that assumptions & data are
   appropriate with a certain degree of confidence:
   regular cycle
 Need independence of validation to satisfy basic risk
   management principles: internal and/or external Risk Advisory LL
25/09/2009                                     Enterprise
Validation elements
 Model development, design, implementation and
  operations: similar to IT systems controls in place like
  COBIT
 Review of models inputs:
    assumptions & key risks
    continuous appropriate mathematics and
     methodologies
    data accuracy
 Review of basic functioning of the models:
      gaps to internal standards and best industry practices
      model replication with a different set of random
25/09/2009                                           Enterprise Risk Advisory LL
Validation elements
 Historical performance:
    back testing to external sources: industry studies,
     academic papers, regulatory and rating agencies’ capital
 Profit and loss attribution: comparison of actual
  results to risk drivers predicted by the models. Idem
  to a source of earnings analysis
 Management oversight:
    has management been using the models?
    has management put in place processes to obtain
     assurance that the models are still appropriate
 Documentation and independent validationEnterprise Risk Advisory LL
25/09/2009
Calibration principles
 For each risk drivers, should aim to calibrate four
  elements:
   level of the risk factor and its uncertainty
   trend of the risk
   inherent volatility
   calamity/catastrophic/tail
 Market conditions : impact on pro/counter cyclicality
 Frequency of calibration: at least annually and
   probably more often for financial risks
 Should be performed before hedging
 Should be based on best assumption. No margin Risk Advisory LL
25/09/2009                                 Enterprise
Calibration by risk
 Interest rate risk:
      take into account the parallel , twists, inversion of the
        term structure
      QIS4 tail up shocks: 94% at 1yr – low - to 40%
        multipliers at 10yr
      interest rate volatility: usually set separately: * 1.5
 Equity risk:
      use different calibrations for publicly-traded, private
        equity, hedge funds, emerging markets
      for publicly-traded: tail risk decline of 40% at 99.5%
      for hedge funds: recent decline around 20% Enterprise Risk Advisory LL
25/09/2009
   
Calibration by risk
 Credit, counterparty & asset risk:
    in a total return context, spread risk anticipates future
     defaults and migration. No need for an explicit default
     model
    spread risk varies by type of assets, rating and currency
    in Q1S4, spread volatility around 30% and shocks of
     about 90 bps to treasuries. Probably too low given recent
     experience
    concentration risk must be assessed
    for default risk: recovery assumption crucial in the 30%
     to 40% range
25/09/2009                                        Enterprise Risk Advisory LL
Calibration by risk
 Life underwriting risk:
    QIS4 mortality rate increased by 15% permanent with a
     2.5 additional per mille mortality catastrophe shock –
     debate in light of potential pandemic
    lapse shock depends on impact. Can go as high as 100%
     multiplicative
    longevity rate increased by a permanent 25%
 Operational risk: must move beyond the factor based
   approach to modelling explicitly and map to insurance
   coverage and other internal controls
 Liquidity risk: can be modeled and not simply
                                              Enterprise Risk Advisory LL
25/09/2009
   managed
Correlation in the tail
 Correlations exist at different levels:
    within a risk category:

       Market Risk     Interest rate   Equity    FX
       Interest rate   1

       Equity          75%             1

       FX              25%             25%       1




     between risk categories within an entity
     between legal entities: should probably be zero because
       of the non-fungibility of capital and the non recognition
25/09/2009                                            Enterprise Risk Advisory LL
Correlation in the tail
 Recent experience seems to indicate otherwise
    According to a recent Pimco study:
             Correlation to   Early   Early 2008 2008 Meltdown
             S & P 500        90s                % yearly loss
             S & P 500        1       1          37%
             High-Yield       20%     80%        26%
             Bonds            -30%
             International    30%     70%        45% - 55%
             stocks           -40%
             Real Estate      30%     60% -70%   37%
             Commodities      0%      -20% -30% 37%


25/09/2009                                                   Enterprise Risk Advisory LL
Correlation in the tail: lessons
 Correlations are unstable in the tail and this what EC
  is trying to determine
 Independent risks become dependent in extreme
  times:
     subprime business practices – operational risks ›
     enhanced defaults - credit risk ›
     market losses on securitized investments – market risk ›
     capital problems at many FIs – liquidity risk ›
     bankruptcies of many FIs – systemic risk ›
     lawsuits by investors and regulators – legal risk ›
      enhanced regulations – regulatory risk ›
25/09/2009                                           Enterprise Risk Advisory LL
Correlation in the tail: lessons

 “When people start buying an asset, the act of them
  diversifying ultimately makes the asset less of a
  diversifier .“ Pimco’s Head of analytics
 Rule: total diversification benefit should not be above
  30%
 One potential approach is to use Clayton copulas
  which measure non-linear dependency
 This is difficult as we trying to assess 1 in 200 year
  events
25/09/2009                                     Enterprise Risk Advisory LL
Emerging risk
 EC must be a forward looking process , tied to ERM
  and thus must anticipate emerging risks
 Risk issues and impact on EC – mostly Solvency II
     liquidity premium: not allowed in the calculation of the
      market consistent value of liabilities
     discount rate: most likely the risk-free not swap rates
     group support: not allowed and impact on
      diversification assumptions in EC calculation
     MVM: currently set at 6% with no diversification benefit


25/09/2009                                         Enterprise Risk Advisory LL
Emerging risk
 Environmental risks – US based:
      Fiduciary Responsibility: Legal and Practical Aspects of
        Integrating ESG Issues into Institutional Investment –
        UNEP FI
      NAIC is requiring insurance companies with at least 500
        million in annual premiums to start estimating and
        publishing an Insurer Climate Risk Disclosure Survey
        starting in May 2010.
      NAIC seeks to determine "how insurers are altering their
        risk-management and catastrophe-risk modeling in
        light of the challenges posed by climate change. “ › direct
25/09/2009 implications
        EC                                            Enterprise Risk Advisory LL
CONTACT




         Michel Rochette, MBA, FSA
        Enterprise Risk Advisory, LLC
                954-607-6969
michel.rochette@enterprise-risk-advisory.com

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Advanced Economic Capital

  • 1. Advanced (Economic) Capital Topics Cliquez pour modifier le style des sous-titres du masque Michel Rochette, MBA, FSA 2009 Valuation Actuary Symposium Anaheim, CA September 25th 2009
  • 2. Topics  General topics:  Purpose and principles of capital model development  Major components of a capital model  Uses of a capital model  Specialized topics:  Approaches to building a capital model  Validation considerations  Calibration considerations  Correlation in the tail: diversification  Emerging risk considerations 25/09/2009 Enterprise Risk Advisory LL
  • 3. Purpose  ¨ Risk management system of an insurer for the analysis of the overall risk situation of the insurance undertaking, to quantify risks and determine the capital requirement on the basis of the company specific risk profile¨ CEA Groupe Consultatif  Required capital is assessed in light of:  available capital & other financial resources  enterprise risk management processes  strategic goals & risk appetite  regulatory requirements 25/09/2009 Enterprise Risk Advisory LL
  • 4. Principles  All material risks should be covered: links to ERM and emerging risks  Models must be appropriate for the scale and complexity of the firm  Models must be dynamic and flexible  Models must be embedded in the financial, strategic and operational processes: Use Test in Solvency II  Governance of models development:  Board/top management oversight and involvement  documentation of models, limitations & changes  internal controls over development: auditableEnterprise Risk Advisory LL 25/09/2009
  • 5. Major components  Exposure models of key risks:  financial risks & underwriting risks: assets and liabilities models cash flows  non financial risks: operational and business models  strategic risks: strategic models  Risk drivers models: ESG, catastrophic, scenarios, stochastic, EVT, competitor, behaviour, management actions  Aggregation approaches: correlation with var/cov, copulas, none  Time horizon: short-term view versus run-off 25/09/2009 Enterprise Risk Advisory LL
  • 6. Uses  Investment decisions: existing and new  Product development  Strategic decisions  Corporate finance decisions: financial leverage  Hedging strategies  External events and emerging risks  Regulatory proposals: CP 37 & CP 56 in Solvency II  “…widely used and plays an important role in the course of conducting an insurer's regular business, particularly in risk management. " 25/09/2009 Enterprise Risk Advisory LL
  • 7. Approaches  Top down economic and business scenarios:  obtain an overall EC estimates for all risks combined  Stress tests:  judgmental and test specific risks and impact on capital  Stochastic:  random scenarios and obtain distribution of risks  Insurance approach:  Frequency, severity, recovery  Factor based: used for regulatory  Others: 25/09/2009 Enterprise Risk Advisory LL  Regression, neural networks, Bayesian, fuzzy logic, EVT
  • 8. Validation principles  Integrates both qualitative and quantitative elements  Provides that the models were designed, work as planned and are implemented correctly – quality assurance  Analyses the predictive properties of the models: testing against experience, backtesting  Iterative process to assess that assumptions & data are appropriate with a certain degree of confidence: regular cycle  Need independence of validation to satisfy basic risk management principles: internal and/or external Risk Advisory LL 25/09/2009 Enterprise
  • 9. Validation elements  Model development, design, implementation and operations: similar to IT systems controls in place like COBIT  Review of models inputs:  assumptions & key risks  continuous appropriate mathematics and methodologies  data accuracy  Review of basic functioning of the models:  gaps to internal standards and best industry practices  model replication with a different set of random 25/09/2009 Enterprise Risk Advisory LL
  • 10. Validation elements  Historical performance:  back testing to external sources: industry studies, academic papers, regulatory and rating agencies’ capital  Profit and loss attribution: comparison of actual results to risk drivers predicted by the models. Idem to a source of earnings analysis  Management oversight:  has management been using the models?  has management put in place processes to obtain assurance that the models are still appropriate  Documentation and independent validationEnterprise Risk Advisory LL 25/09/2009
  • 11. Calibration principles  For each risk drivers, should aim to calibrate four elements:  level of the risk factor and its uncertainty  trend of the risk  inherent volatility  calamity/catastrophic/tail  Market conditions : impact on pro/counter cyclicality  Frequency of calibration: at least annually and probably more often for financial risks  Should be performed before hedging  Should be based on best assumption. No margin Risk Advisory LL 25/09/2009 Enterprise
  • 12. Calibration by risk  Interest rate risk:  take into account the parallel , twists, inversion of the term structure  QIS4 tail up shocks: 94% at 1yr – low - to 40% multipliers at 10yr  interest rate volatility: usually set separately: * 1.5  Equity risk:  use different calibrations for publicly-traded, private equity, hedge funds, emerging markets  for publicly-traded: tail risk decline of 40% at 99.5%  for hedge funds: recent decline around 20% Enterprise Risk Advisory LL 25/09/2009 
  • 13. Calibration by risk  Credit, counterparty & asset risk:  in a total return context, spread risk anticipates future defaults and migration. No need for an explicit default model  spread risk varies by type of assets, rating and currency  in Q1S4, spread volatility around 30% and shocks of about 90 bps to treasuries. Probably too low given recent experience  concentration risk must be assessed  for default risk: recovery assumption crucial in the 30% to 40% range 25/09/2009 Enterprise Risk Advisory LL
  • 14. Calibration by risk  Life underwriting risk:  QIS4 mortality rate increased by 15% permanent with a 2.5 additional per mille mortality catastrophe shock – debate in light of potential pandemic  lapse shock depends on impact. Can go as high as 100% multiplicative  longevity rate increased by a permanent 25%  Operational risk: must move beyond the factor based approach to modelling explicitly and map to insurance coverage and other internal controls  Liquidity risk: can be modeled and not simply Enterprise Risk Advisory LL 25/09/2009 managed
  • 15. Correlation in the tail  Correlations exist at different levels:  within a risk category: Market Risk Interest rate Equity FX Interest rate 1 Equity 75% 1 FX 25% 25% 1  between risk categories within an entity  between legal entities: should probably be zero because of the non-fungibility of capital and the non recognition 25/09/2009 Enterprise Risk Advisory LL
  • 16. Correlation in the tail  Recent experience seems to indicate otherwise  According to a recent Pimco study: Correlation to Early Early 2008 2008 Meltdown S & P 500 90s % yearly loss S & P 500 1 1 37% High-Yield 20% 80% 26% Bonds -30% International 30% 70% 45% - 55% stocks -40% Real Estate 30% 60% -70% 37% Commodities 0% -20% -30% 37% 25/09/2009 Enterprise Risk Advisory LL
  • 17. Correlation in the tail: lessons  Correlations are unstable in the tail and this what EC is trying to determine  Independent risks become dependent in extreme times:  subprime business practices – operational risks ›  enhanced defaults - credit risk ›  market losses on securitized investments – market risk ›  capital problems at many FIs – liquidity risk ›  bankruptcies of many FIs – systemic risk ›  lawsuits by investors and regulators – legal risk ›  enhanced regulations – regulatory risk › 25/09/2009 Enterprise Risk Advisory LL
  • 18. Correlation in the tail: lessons  “When people start buying an asset, the act of them diversifying ultimately makes the asset less of a diversifier .“ Pimco’s Head of analytics  Rule: total diversification benefit should not be above 30%  One potential approach is to use Clayton copulas which measure non-linear dependency  This is difficult as we trying to assess 1 in 200 year events 25/09/2009 Enterprise Risk Advisory LL
  • 19. Emerging risk  EC must be a forward looking process , tied to ERM and thus must anticipate emerging risks  Risk issues and impact on EC – mostly Solvency II  liquidity premium: not allowed in the calculation of the market consistent value of liabilities  discount rate: most likely the risk-free not swap rates  group support: not allowed and impact on diversification assumptions in EC calculation  MVM: currently set at 6% with no diversification benefit 25/09/2009 Enterprise Risk Advisory LL
  • 20. Emerging risk  Environmental risks – US based:  Fiduciary Responsibility: Legal and Practical Aspects of Integrating ESG Issues into Institutional Investment – UNEP FI  NAIC is requiring insurance companies with at least 500 million in annual premiums to start estimating and publishing an Insurer Climate Risk Disclosure Survey starting in May 2010.  NAIC seeks to determine "how insurers are altering their risk-management and catastrophe-risk modeling in light of the challenges posed by climate change. “ › direct 25/09/2009 implications EC Enterprise Risk Advisory LL
  • 21. CONTACT Michel Rochette, MBA, FSA Enterprise Risk Advisory, LLC 954-607-6969 michel.rochette@enterprise-risk-advisory.com