Description: The purpose of this article is to provide an overview of soft computing applications in actuarial science. Soft computing refers to modes of computing in which precision is traded for tractability, robustness and ease of implementation.

Description: Discusses a method for division of workload in a consulting firm in a way which will minimize cost.

Description: This 1978 session on classification models included 1. models demonstrating the effect of a classification system superimposed on a merit rating system and 2. models demonstrating the subsidization of poorer risks.

Description: This paper examines four and-a-half years of prescription records for an elderly population who have relatively comprehensive out-of-hospital drug coverage under the Pharmaceutical Assistance Contract for the Elderly program in Pennsylvania. The result is a discussion of the determination of non-parametric estimations of the distributions. From Actuarial Research Clearing House 1991, 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: A fuzzy random variable [FRV] has been conceptualized as a vague perception of a crisp but unobservable random variable [RV] and also as a random fuzzy set. Since actuaries seem receptive to these notions of FRV, and there are sources of uncertainty that RVs can not accommodate, but FRVs can, one would expect FRVs to be a component of the actuarial arsenal, but generally this is not the case. Assuming that the reason for this is that potential users are not sufficiently familiar with FRV methodology, the purpose of this article is to help alleviate this situation by presenting a FRV primer.

Description: Recent articles addressed the subject of fuzzy regression [FR] and the term structure of interest rates [TSIR]. Their approach relied on possibilistic regression. Although possibilistic regression has been used in many applications, it has a number of limitations, not the least of which is its nebulous relation to the least-squares concept. As an alternative to possibilistic regression, this paper uses fuzzy least square regression to investigate the TSIR.

Description: This people provides a derivation of continuous and curtate inequalities of life contingent functions and shows how the proofs of the continuous inequalities are of an entirely different nature from the usual proofs for the curtate inequalities Followed by discussion papers submitted by several authors