Description: This paper suggests that using the entire runoff triangle to keep a tail on the runoff curve was not necessary, and that doing so was actually a disadvantage if group medical and dental claim payment patterns changed over the period being used. An alternative was presented. From Actuarial Research Clearing House 1993, VOL. 3.

Description: This paper develops a parametric model for health care insurance claims to fit parametric models to the data. Model selection is based on the ChJ-squared goodness-of-fit test and a comparison of the empirical limited expected value function to parametric limited expected value functions. A copula function was used to model the bivariate portion of the data. From Actuarial Research Clearing House 1993, VOL. 3.

Description: This paper suggests that many problems in health insurance pricing can be solved by requiring a minimum mandatory paid-up period [i.e., premium period shorter than insurance period], and by encouraging insureds to persist by providing them adequate pricing information. This will generate significant investment income for insuring programs and reduce the cost of insurance.

Description: This paper presents Bayesian models for analysis of claim lag data. The analysis of claim runoff patterns investigate the extraction of information on trend and seasonal patterns in incurred claims. This is investigated on the basis of individual group data, and also relative to a larger aggregation of pooled experience. The models are implemented based on Markov chain Monte Carlo methods. The models are applied to examples using simulated claim lag data. From Actuarial Research Clearing House, 2003, Vol. 1.

Description: A mathematical framework for benefits and choices must be created, in order to model flexible benefit selection. This paper creates such a framework by defining benefit plans as reimbursement functions. These are then used with a defined choice function to calculate the cost deviation due to selection. From Actuarial Research Clearing House 1992, VOL. 1.

Description: In this paper the authors analyze data from group medical expense insurance claims and show that many insurance loss distributions have very 'heavy tails' because large losses represent a disproportionate fraction of the total cost. They also present a simple model to reproduce and explain the large loss behavior. From Actuarial Research Clearing House 1990, VOL. 2

Description: This paper develops a parametric model for health care insurance claims using currently available software to fit parametric models to the data. Model selection is based on the Chi-squared goodness-of-fit test and a comparison of the empirical limited expected value function to parametric limited expected value functions. From Actuarial Research Clearing House 1993, VOL. 3.

Description: This paper investigates the accuracy of loss reserves by comparing some reserves with the actual results five years hence. The ultimate purpose was to provide an estimate of the amount of variability which cannot be explained by listed factors. The resulting amount of variability gives an indication of the amount required for a provision for adverse deviation. From Actuarial Research Clearing House 1991, VOL. 1

Description: This Fellowship credit research paper describes the use of fuzzy sets applications to the selection of group health risks. In general, fuzzy set theory is implemented to describe collections of objects whose boundaries are not precisely defined, as in the judgment of what constitutes a good risk group. First, single-plan underwriting is considered, then the work is extended to multiple-option plans.

Description: This paper provides an outline of the pricing methodology used by Blue Cross and Blue Shield of Virginia which incorporates trend analysis by trend component. From Actuarial Research Clearing House 1993, VOL. 3.