11_Brehm Flashcards
Enterprise Risk Management
Enterprise Risk Management is the process of systematically and comprehensively identifying critical risks, quantifying their impacts, and implementing integrated strategies to maximize enterprise value.
Key Aspects of ERM
- An effective ERM program should be a regular process, not a one-time project
- Should consider risks on an enterprise-wide basis
- Focus on risks that represent a material impact to the value of the firm
- Risk can be positive or negative; it’s the fact that actual outcomes vary from expected
- Risks must be quantified where possible, including correlations among risks
- Create strategies to avoid, mitigate, or exploit risk factors
- Evaluate risk management strategies for risk/return to maximize firm value
Types of Insurance Company Risk Factors
Insurance Hazard Risk - Risk assumed by insurer
* Underwriting (non-cat) – in force
* Accumulation/cat-risk – in force
* Reserve Deterioration <— from past exposures
Financial Risk - Risk to asset portfolio due to volatility in interest rates, foreign exchange rates, equity prices, credit quality, liquidity
Operational Risks - Risks in the operation/execution of the company; the actions the company takes
Strategic Risks – The risks of strategic choices the company takes –> The risk of choosing the wrong plan
Enterprise Risk Management Process
(different phases of risk management process)
Diagnose - High-level risk assessment of risk factors that pose a potentially serious threat to the firm
-> General environment risks
-> Industry risks
-> Firm-specific risks
Analyze - Quantify risks with probability distributions of potential outcomes. Include correlations.
Implement Risk Management (forms of traditional risk management) - Avoidance, reduction, mitigation, elimination/transfer, or retain/assume risks
Monitor - Monitor results vs. expectation, update plans
Enterprise Risk Modeling
Helps with the Following Strategic Decisions
- Determining capital needed to support risk or maintain rating
- Identifying sources of significant risk
- Deciding on reinsurance strategies
- Planning growth
- Managing asset mix
- Valuing companies for M&A
Most Important Elements for Model Quality
- Model reflects relative importance of different risks to business decisions
- Modelers have a deep knowledge of the risk fundamentals
- Model incorporates the dependencies between different risks
- Modelers have a trusted relationship with senior management
“Essential Elements” of an Enterprise Risk Model
- Underwriting risk
- Reserving risk
- Asset risk
- Dependencies (correlation)
Underwriting Risk
Loss Frequency and Severity Distributions
Used to quantify loss potential
Pricing Risk
Underwriting cycle, risk of unnoticed underpricing until losses accumulate, resulting in a reserve deficiency
Parameter Risk
Risks from mis-estimated parameters, imperfect model form, unmodeled risks
(Estimation, projection event, systemic risk)
Catastrophe Modeling Uncertainty
Uncertainty in 3rd party CAT models (e.g. probability of events/loss)
Parameter Risk
Estimation Risk
Risk that the form and parameters of the frequency/severity distributions don’t reflect the “true” form and parameters
Projection Risk
* Changes over time and uncertainty in the projection of changes
* Trends in frequency/severity from time of data to current/future periods
* Development of losses to ultimate
Event Risk – Events outside company control that impact frequency/severity trends (e.g. class action suits, asbestos, new cause of loss)
Systematic Risk – Nondiversifying, impacting many policies (e.g. inflation)
Reserving Risk
- Risk that reserves develop differently than expected
- Reserve uncertainty impacts the amount of required capital and time that capital must be held
- A model can understate both a reserve estimate and reserve uncertainty
-> We need a model of reserve uncertainty in an enterprise risk model
Asset Risk and its key aspect
- Model asset risk by generating probabilistic scenarios based on historical patterns and testing the insurer’s strategy against the scenarios, taking into account the scenario likelihood
- Model should account for:
o Bonds
o Equities
o Foreign exchange/interest rates
Asset risk refers to variability in asset values. Important asset classes to model include bonds, equities, real estate and exchange rates. A key aspect of asset modeling is modeling scenarios consistent with historical patterns.
Sources of Dependencies
- Simultaneous impact of macroeconomic conditions on multiple risks
o E.g. Inflation impacts both underwriting losses and loss reserve development - Dependencies that impact multiple lines of business
o E.g. UW cycles, loss trends, reserve developments, catastrophes (event risk)
Modeling Dependency
- Use copulas to incorporate dependency if there’s higher correlation in the tail
- Correlation through a multivariate normal distribution has low tail dependency
Why Default Avoidance isn’t the Most Important Reference Point to Set Capital
- Default avoidance is about protecting current policyholders
- To protect shareholders, should avoid significant partial losses of capital that could damage franchise value
-> which would impact customer base, agency relationships, reputation - Loss that would cause a significant ratings downgrade is a more meaningful reference point
Meaningful Reference Points for Setting Capital (Besides Default)
- Maintaining enough capital to avoid ratings downgrade below a certain level
- Maintaining enough capital to service renewal business
-> If writing renewal business requires 80% of capital, an appropriate reference point is a 20% loss of capital - Maintaining enough capital so insurer thrives after a catastrophe (not just survives)
Challenge When Using Extreme Reference Points to Set Capital
- Model is least reliable in the extreme tail (e.g. exhausting all capital)
-> Little data far in the tail
-> Results are sensitive to assumptions about the distribution
-> Far tail is poorly understood
Deterministic Project Analysis
- Uses a single deterministic forecast to estimate present value or IRR
- Uncertainty is handled judgmentally by decision makers
Risk Analysis
And why it is better than deterministic project analysis
DFA
* Uses forecasted distributions of the critical inputs in a Monte Carlo simulation to calculate a distribution of present value.
* The risk judgment is intuitively applied by decision makers.
Better because it directly incorporate the uncertainty of the critical variables in the model
Certainty Equivalent
Certainty Equivalent
Similar to risk analysis, but quantifies the risk judgment with a corporate risk preference or utility function for consistency.
Internal Risk Model:
Corporate Risk Tolerance
Helps answer the question: How much risk (standard deviation) are we willing to tolerate?
Corporate risk tolerance depends on:
* Ability and willingness to tolerate volatility
* Company size
* Financial resources
These considerations determine the impact a loss has on the company.
Internal Risk Model:
Cost of Capital Allocated
Cost of risk capital is allocated to the individual risk sources (e.g. Line of business).
RORAC = Risk-AdjustedCapital ⋅ HurdleRate
Internal Risk Model:
Cost-Benefit Analysis for Risk Mitigation
Any risk-mitigation effort with a positive EVA is worth doing. This means the reduction of capital cost is greater than the cost of risk-mitigation.
EVA = NPV Return − Cost of Capital
Cost of Capital = RiskCapital ⋅HurdleRate
How is economic capital measured and what’s the advantages of Economic Capital
Measured with VaR at a remote probability level.
- It’s a unifying measure for all risks across the enterprise
- More meaningful to management than risk-based capital or capital adequacy ratios
- Forces a firm to quantify and aggregate risks into a probability distribution
- Provides a framework for setting risk levels for the organization and individual business units
所以model challenge是ERM model aren’t reliable at such remote probabilities because of the approximation, assumptions and lack of data in the tail
Moment-Based Measures:
Advantages and Disadvantages
Advantages
Reflects all losses in the distribution
Disadvantages
Standard Deviation treats favorable distributions the same as unfavorable ones
Exponential moment -> responds more to larger losses
Semi-standard deviation -> only uses unfavorable deviations (but this won’t highlight the tail risk enough, better for LR or pricing adequacy)
同理,VaR and TVaR wouldn’t be suitable for LR or pricing adequacy because they are more focusing on tail events
For lines not as extreme as CAT, like excess casualty, can use semi-SD