Short-Term Reserves Flashcards

1
Q

Additional considerations in establishing claim reserves (13)

A

These are in addition to ASOP #5:

  1. ) Incurral dating method
  2. ) Reserve basis - statutory, GAAP, and tax bases differ in their use margin, interest rates, etc.
  3. ) Interest - reserves for claims with long payouts may be discounted to reflect interest
  4. ) Controls & reconciliation - the data used should be tested for accuracy
  5. ) Insurance characteristics - reserves vary depending on the type of risk covered
  6. ) Reserve cells - set up separate cells for each homogeneous category of business
  7. ) Managed care features - such as discounts & provider risk sharing arrangements
  8. ) Trends
  9. ) Seasonality
  10. ) Claims admin expenses - set up a reserve equal to a % of the claim reserve
  11. ) Morbidity assumptions - for long-term claims, morbidity is reflected in continuance tables
  12. ) Diagnosis-based tabular reserves - some companies have begun using different morbidity bases for different causes of disability
  13. ) Use of the case reserves method - very labor intensive, so only recommended for small blocks
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2
Q

ASOP #5: Considerations for estimating incurred claims (7)

A

ASOP #5 - Incurred Health & Disability Claims:

  1. ) Plan provision & business practices - reflect practices that materially affect the cost, frequency or severity of claims
  2. ) Economic influences - such as unemployment levels, cost shifting, and catastrophic events
  3. ) Organizational claims admin - lag factors may vary due to staffing levels, computer system changes, or seasonal backlogs
  4. ) Risk characteristics & organizational practices by block of business - consider the effects of marketing & underwriting practices can affect incurred claims
  5. ) Legislative requirements - consider how regulations mandating benefits, risk characteristics, rating, reserving, and underwriting practices can affect incurred claims
  6. ) Carve outs - consider the effect of carved-out benefits on incurred claims level
  7. ) Special considerations for long-term products - such as cost of living adjustments & inflation effects
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3
Q

Advantages of stochastic approaches for reserving (4)

A
  1. ) Provides explicit guidance for establishing provisions for adverse deviation in the reserves
  2. ) Provides guidance on potential variability in reported earnings and reserve levels
  3. ) Allows for quantification of variability in items such as seasonality and claim trend
  4. ) Allows for improved evaluation of reserve estimates (by knowing the variability of the estimates)
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4
Q

Disadvantages of stochastic approaches for reserving (3)

A
  1. ) Some audiences that are unfamiliar with this approach may have a false sense of confidence in the approach because of its sophistication
  2. ) May be too complex to be used by all individuals who must perform related functions (such as forecasting & pricing)
  3. ) Not every process can be modeled rigorously
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5
Q

Stochastic modeling techniques for reserving (5)

A
  1. ) Fitting a parametric distribution to the data - works best when process being modeled is stationary over time
  2. ) Ordinary least squares regression (OLS) - allows for investigation of the effects of specific explanatory variables, such as trend or seasonality
  3. ) Generalized linear models - these models improve upon OLS b/c they allow for cases where the dependent variable being modeled is either bounded (e.g. must be greater than 0) or not normally distributed.
  4. ) Stochastic time series models - these are useful for handling situations where values are correlated across time (e.g. seasonal or cyclical patterns)
  5. ) Monte Carlo simulation - this approach is of significant practical value when combining results from any of the other techniques
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6
Q

Considerations when developing a stochastic approach to reserve estimation (5)

A
  1. ) Availability of data - historical data is needed to validate the model & assumptions
  2. ) Appropriateness of data - consider whether the processes reflected in the historical data are representative of the process being modeled going forward
  3. ) Access to statistical software - lack of access to or understanding of modeling software will limit the available choices for modeling techniques
  4. ) Appropriateness of the model - this can be validated through goodness-of-fit testing, residual analysis, and hold-out sample evaluation
  5. ) Covariances of modeled estimates - when reserve estimates are calculated through component estimates the covariance between these components must be estimated
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