2. Topics
ERM and Solvency II
Similarities and differences between them
Purpose of an economic capital model
Major components of a capital model
Uses of a capital model
Validation issues
Calibration issues
Emerging issues
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3. Similarities
Economic capital models:
ERM: focus is on internal models only
Solvency II: SCR approach, partial and full internal models
Governance:
ERM: many potential standards like COSO, SP ERM, ISO
31000
Solvency II: Pillar II with ORSA, governance and risk
management functions
Implementation of ERM:
ERM: embedded in operations
Solvency II: Use test
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4. Differences
Overall goal:
ERM: value creation through risk management
Solvency II: risk control through capital, SCR and protection
of policyholders
Risk taxonomy:
ERM: all risks with a focus on key risks
Solvency II: specific risks as defined in Pillar I and additional
risks with capital add-0ns in Pillar II
Risk champion:
ERM: need a CRO to oversee all processes
Solvency II: actuarial function is defined and participates in
setting up risk system, complemented by Audit and a risk
function
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5. Differences
Risk Appetite:
ERM: essential as it guides firms in setting up risk limits and
tolerances. Focus is on shareholders’ wealth.
Solvency II: focus is on the control of the negative side of risk
through capital and policyholders’ protection.
Financial resources:
ERM: all financial resources available to face risks: existing
and contingent capital
Solvency II: available capital: Tiers I, II, III
Value & time framework:
ERM: Economic basis, EEV, MCEV over a flexible time, two-
sided VAR, TVAR..
Solvency II: target IFRS, over a one-sided 1-yr VAR
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6. Purpose of an EC framework
¨ 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
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7. Principles: EC development
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: auditable
independent review: More than peer review
Others:
consistency between valuation and EC models: valuation framework
input data verifiable and controllable
validation and calibration
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8. 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 approach
Confidence level: internal, regulatory, rating agencies
Frequency of calculations: quarterly to monthly
Valuation framework: economic, EV, EEV, MCEV
Metric chosen: VAR, T-VAR, EVT
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9. 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. "
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10. 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, back testing
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 reviews
Must go beyond the pure regulatory ticking the box
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11. 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 numbers
stress testing and reverse stress testing: sensitivity of the
results
models capture business environmental changes
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12. 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 validation
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13. 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 embedded as
the purposed is to estimate required capital for the risks facing
the organization
Time horizon and risk measures chosen per risk category
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14. 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%
implied equity volatility of around 35%
Currency risk: usually set around +/- 20% for a well-diversified
portfolio
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15. 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
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16. 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 managed
Contagion (systemic ) risk: Large FIs might be subject to additional
capital if viewed as systematically important.
Strategic risk: can deplete capital and should be modeled
Reputation risk: doesn’t affect capital but value of the firm
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17. 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 for Solvency II: should probably
be zero because of the non-fungibility of capital and the
non recognition of group capital support
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18. Correlation in the tail
Recent experience seems to indicate otherwise
According to a recent Pimco study:
Correlation Early Early 2008 Meltdown
to S & P 500 90s 2008 % 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%
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19. 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 ›
diminished reputation for the financial industry – reputation
risk and loss in value
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20. 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
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21. Emerging issues
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
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22. ERM: 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 EC implications
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23. Solvency II: ORSA
Pillar II requirement: Own Risk & Solvency Assessment
Goal is to demonstrate “sound and prudent management
of the business and assess overall solvency needs”
Useful references:
BMA paper: “opopportunity to align management and
regulatory reporting & encourage sound risk management
practices within the jurisdiction”
CEIOPS: explains its preliminary views on the definition and
importance of the ORSA as a management tool,
requirements and guidance
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