A.1. AAA - Risk Classification

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A.1. AAA - Risk Classification
2015-09-02 09:52:43
AAA Risk Classification

AAA Risk Classification
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  1. Define Risk Classification
    • grouping of risks with similar risk characteristics for the purpose of setting prices
    • intent is not to predict experience for individual risk in class or identify good/bad risks
  2. 3 Primary Purposes of Risk Classification
    • protect the insurance system's financial soundness: avoid adverse selection
    • promote fairness in the insurance system: produce prices that are valid and equitable, i.e. not unfairly discriminatory
    • permit economic incentives to operate, and thus encourage widespread availability of coverage: ensure insurers can earn profit on all risks, but beware that additional expense of obtaining more refinement should not be greater than the reduction in expected costs.
  3. Adverse Selection
    Adverse selection occurs when an insurer doesn’t use a risk characteristic that is being used by other insurers. Since other insurers will attract the lower risk insureds based on this risk characteristic, the insurer not using the risk characteristic will be left with a higher than proportional share of the higher risks, for which it does not accurately price or underwrite. As such, the insurer will have a higher loss ratio
  4. Basic Principles of Risk Classification
    • the system should reflect expected cost differences
    • the system should distinguish among risks on the basis of relevant cost-related factors
    • the system should be applied objectively
    • the system should be practical and cost-effective
    • the system should be acceptable to the public
  5. Coping with impact of chance occurrences
    • hazard avoidance: not driving
    • hazard reduction: driving less, installing sprinklers
    • transfer of financial uncertainty: govt, (self)insurance
  6. Public vs private programs:
    • similarities: transfer of risk, pool risks, try to predict losses
    • differences: law vs contract, compulsory vs voluntary (competition)
  7. Consideration in designing a risk classification system
    • UW: independent of UW review; UW can help validate classification
    • marketing: impacts mix of business; don’t necessarily sell to all classes
    • program design
    • statistical considerations
    • operational considerations
    • hazard reduction incentives: e.g. sprinklers; desirable but not necessary
    • (social) public acceptability
    • (social) causality: helps boosting confidence that information is useful
    • (social) controllability: must use judgement to weigh against malicious manipulation
    • (social) affordability: want to ensure we're not further penalizing economically challenged risks
  8. Public acceptance considerations
    • should not differentiate unfairly among risks
    • should be based upon clearly relevant data
    • should respect personal privacy
    • should be structured so that risks tend to identify naturally with their classification
  9. Problems with public acceptance
    • difficult to ascertain
    • vary among segments of the society
    • changes over time
  10. Program design considerations
    • degree of choice available to the buyer
    • experience based pricing
    • premium payer
  11. Statistical considerations
    • homogeneity: expected loss cost should be reasonably similar within a class, with no clearly identifiable subclasses with significantly different loss experience
    • credibility: classes should be large enough, but need not be credible on their own
    • predictive stability: responsive to changes in nature of insurance losses, but avoid unwarranted abrupt changes in prices
  12. Operational considerations
    • expense: including obtaining & maintaining data required (cost-benefit)
    • constancy: should lower need to reclassify
    • availability of coverage: avoid affordability issues e.g. through exclusions
    • avoidance of extreme discontinuities
    • absence of ambiguity: definition should be clear and objective
    • manipulation: minimize ability to manipulate or misrepresent information
    • measurability: convenient and reliable measurement (e.g. age vs driving pattern)