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 is the abstract for the paper entitled 'Pricing Long Term Insurance Contracts.' This paper considers several models describing the changes in the needs of the insured for care over time. From Actuarial Research Clearing House 1994, VOL. 1.

Description: This presentation provides actuarial implications of COVID-19.

Description: This is article identifies and quantifies how one of several prospective cures for chronic conditions will impact healthcare.

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 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 1993 paper examined the premium rate changes that could have resulted from the passage of The Health Insurance Reform and Cost Control Act of 1991. From Actuarial Research Clearing House 1993, VOL. 3.

Description: This is an internal letter from an actuary to an associate regarding a claims study that established, in the mind of the writer, the adequacy and conclusiveness of a small sample size in certain situations. Actuarial Research Clearing House ARCH 1988, 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.