Marshall Flashcards
Summary of Risk Margin analysis framework
Framework for assessing risk margin
Why are both quantitative and qualitative analysis necessary to properly assess risk margins?
Quantitative analysis can only reflect uncertainty in historical experience and can’t adequately capture all possible sources of future uncertainty
Judgment is necessary to estimate future uncertainty
Preparing the claims portfolio: Considerations for splitting into valuation classes
Preferable to split the claims portfolio into valuation classes the same way as split used for developing central estimates
this allows analyzed sources of uncertainty to be aligned with the central estimate analysis
if the valuation of central estimate is at a granular level, it may make sense to do the quantitative analysis on aggregated valuation classes (which are more credible) and allocate results down
Preparing the claims portfolio: allocation of valuation classes to claims groups
If diff groups of claims within a valuation class have materially different uncertainty, they should be treated separately in the risk margin analysis
- eg splitting CAT nonCAT
Balance the benefit gained and practicality/cost
Sources of Uncertainty
Systemic Risk
Independent Risk
Sources of Systemic Risk
Internal Systemic Risk
External Systemic Risk
Sources of Independent RIsk
Random component of parameter risk
Random component of process risk
Sources of uncertainty that quantitative modeling is best able to assess
Quantitative modeling is best for analyzing independent risk and past episodes of external systemic risk
Quantitative modeling must be supplemented with other qualitative or quantitative analysis to incorporate internal systemic risk and external systemic risk
Main sources of internal systemic risk
Specification Error
Error arising from an inability to build a model that fully represents the underlying insurance process
Parameter Selection Error
Error that the model can’t adequately measure all predictors of claim cost outcomes or trends in predictors
Data Error
Error from poor data
External Systemic Risk: Risk categories
Economic and social
Legislative, political and claims inflation risks
Claim management process change risks
Expense risk
Event risk
Latent claims risk (?)
Recovery risk
Why quantitative methods might not be appropriate for assessing correlation effects
Techniques tend to be complex and require substantial data - time/effort outweigh benefits
Correlations would be heavily influenced by past correlations
Difficult to separate past correlation effects between independent risk and systemic risk or identify the effects of past systemic risks
Internal systemic risk can’t be modeled with standard correlation risk techniques
Results unlikely to be aligned with the framework, which splits between independent, internal systemic, and systemic risks
Correlation effects on independent risks
Assumed to be uncorrelated with any other source of uncertainty either within or between valuation classes
Correlation effects in internal systemic risks
Assumed to be uncorrelated with independent risk and external systemic risk sources
There is correlation between classes and between outstanding claim and premium liabilities due to:
Same actuary effect -> effect of common valuation models or approaches across different valuation classes
Linkage between premium liability methodology and outcomes from the outstanding claims valuation
Correlation effects on external systemic risks
Uncertainty from each risk category is assumed to be uncorrelated with independent risk, internal systemic risk and the uncertainty from external systemic risk categories
There is correlation between classes and between outstanding claim and premium liabilities from similar risk categories (eg claims inflation risk across all long-tail portfolios)
Independence Risk CoV consolidation formula
Internal Systemic Risk CoV consolidation formula
External Systemic Risk CoV consolidation formula
Risk Margin Formula
