Marshall Flashcards
2 sources of uncertainty
systemic risk and independent risk
Describe systemic risk
Systemic risk represents risks that are common across valuation classes or claim groups
2 sources of systemic risk
- Internal Systemic risk
- External systemic risk
Describe internal systemic risk
Risks internal to the insurance liability valuation/modeling process. such as model structure, model parameterization and data accuracy.
This risk is also called Model Specification risk
Describe External systemic risk
Risks external to the insurance liability valuation/modeling process. such as future trends in claim cost outcomes (material costs, labor costs) that may cause actual experience to differ from what is expected based on the current environment and trends
Describe independent risks
Risks that occur due to the randomness inherent in the insurance process
Two sources of independent risk
- The random component of parameter risk
- The random component of process riskD
Describe the random component of parameter risk
represents the extent to which the randomness associated with the insurance process affects the ability to select appropriate parameters in the valuation models
Describe the random component of process risk
Represents the pure effect of the randomness associated with the insurance process
What techniques are best suited for analyzing sources of independent risk and historical external systemic risk
Traditional quantitative modeling techniques (bootstrapping, stochastic chain-ladder)
Reasons stochastic modeling techniques do NOT capture all sources of uncertainty
- Good models fit past data well. This tends to remove past episodes of external systemic risk, leaving only random sources of uncertainty behind
- When past episodes of external systemic risk are not completely removed from the model, consideration must be given to whether or not we should expect these episodes to continue into the future
- Models normally do not capture uncertainty arising from internal systemic risk
3 sources of internal systemic risks
- Specification error
- Parameter selection error
- Data error
Describe specification error
The error that arises because the model cannot perfectly model the insurance process
Describe Parameter selection error
the error that arises because the model cannot adequately measure all predictors of future claim costs or trends in these predictors
Describe the data error
The error that arises due to the lack of credible data. This can also refer to an inadequate knowledge of the portfolio being analyzed, including pricing, underwriting, and claims management processes
Approach to analyzing internal systemic risk
- A balanced scorecard is developed to objectively assess the model specification against a set of criteria
- for each of the sources of internal systemic risk, risk indicators are developed and scored against the criteria.
- The scores are aggregate for each valuation class and mapped to a quantitative measure (CoV) of the variation arising from internal systemic risk
Examples of external systemic risks
- Economic and social risks (uncertainty associated with inflation, social trends)
- Legislative, political and claim inflation risks (the uncertainty associated with changes in the political landscape, shifts/trends in the level of claim settlements)
- Claim management process changing risk (uncertainty associated with changes in claim reporting, payment, estimation)
- Expense risk (uncertainty associated with the cost of managing the run-off of the insurance liabilities or the cost of maintaining the unexpired risk until the date of loss)
5.Event risk (uncertainty associated with claim costs arising from events, either natural or man-made) - Latent claim risk (uncertainty associated with claims that arise from sources that are not currently covered such as asbestos)
- Recovery risk (uncertainty associated with recoveries either reinsurance or non-reinsurance)
Correlation effect for independent risk
assumed to be uncorrelated with any other source of uncertainty, either within a particular valuation class or between classes
Correlation effect for internal systemic risk
Assumed to be uncorrelated with independent risk, and with each source of external system risk.
However, internal system risk tends to be correlated between valuation classes AND between OLC’s and OL’s
Correlation effect for external systemic risk
Assume that each risk category is uncorrelated with independent risk and internal systemic risk.
However, correlation may exist between risks that belong to similar external system risk categories.
If correlation occurs, correlated risk categories can be aggregated into broader categories that are not correlated
For independent risk, internal benchmarking should be done for 2 main dimensions
- Portfolio size - the larger the portfolio, the lower the volatility arising from the random effects
- Length of claim run-off - the longer a portfolio takes to run-off, the more time there is for random effects to have an impact
Describe Outstanding claim liability independent risk CoV for long-tail vs. short-tail
OCL CoVs for short-tail portfolios should be lower than similarly sized long-tailed portfolios, and substantially lower than smaller long-tailed portfolio
Compare independent risk CoV for long-tailed vs. short-tailed and PL vs. OLC
PL CoVs for long-tailed portfolios should be higher than OCL CoV for the same portfolio due to the law of large numbers. The PLs for long-tailed lines will be smaller resulting in more volatility.
PL CoVs for short-tailed portfolios should be lower than OCL CoVs for the same portfolios due to the law of large numbers. The PLs for short-tailed lines will be larger since most of the OCLs will have already closed, resulting in less volatility for the PLs.
Comparing internal systemic risk CoVs for long-tailed vs. short-tailed
Long-tailed portfolios should have higher CoVs than short-tailed portfolios sine the long-tailed tend to be more complicated.
Classes with homogeneous claim groups should have similar CoVs
Comparing external systemic risk CoV for long-tailed vs. short-tailed
Long-tailed portfolios should have higher CoVs than short-tailed
Except: event risk and liability risk for home classes
What factors should we consider when choosing the statistical method
- The valuation class being assessed
- The materiality of the independent risk for that class relative to the overall claims portfolio risk margin
- The cost and effort associated with applying the method
What method should we use for independent risk assessment for OCL
GLM
GLM is used for reserving purposes to identify the key factors that have contributed to past claim costs.
Bootstrapping is less flexible than GLM, but can be used to help assess random effects
Methods used for independent risk assessment for premium liabilities
Bootstrapping, GLM, Bayesian
Goal of sensitivity testing
Gain insights about the sensitivity of the final risk margin to key assumptions.
Goal of scenario testing
Tie the risk margin to a set of valuation outcomes. We adjust the assumptions used for the central estimate in order to align the central estimate with the assessed provisions including the risk margin
Goal of internal benchmarking
Compare the proposed CoVs to one another to check for internal consistency and reasonableness
Goal of external benchmarking
compare the reasonableness of CoVs and risk margins to those from external sources
Goal of hindsight analysis
Compare the past reserve estimates of liabilities against the latest view of the same liabilities to review the actual volatility in the past
Goal of independent risk assessment
use a model to ‘fit away’ past systemic episodes in order to analyze the residual volatility in order to get the CoVs for independent risk
Goal of balanced scorecard (internal systemic risk assessment)
Assess the adequacy of the modeling infrastructure and its ability to reflect and predict the underlying insurance process
