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: In a product warranty, the renewal function is the expected number of failures in a specific warranty duration. To estimate the renewal function, cross-sectional regression data is assumed to be available and the data is assumed to be semiparametric. In this article, the observations are a11owed to be residuals from a complex regression model. It is observed that estimation can be accomplished using reasonable models for the contracts and data collection. From Actuarial Research Clearing House 1992, VOL. 2.

Description: In this paper the author proposes a proof for new formulas that derive exposure formulas of the valuation-schedule type on the basis of the Balducci assumption. In addition he provides a short cut for the coefficients of the terms involving deaths. Then he derives a general exposure formula of the valuation-schedule type that may be used for all mortality studies with an observation period covering an integral number of consecutive years. From ACTUARIAL RESEARCH CLEARING HOUSE, 1980 VOL. 2.

Description: This model arose from a project to evaluate the cost of a health care access' program to provide comprehensive medical care to uninsureds in Minnesota, for the Minnesota Health Care Access Commission. The project was to provide estimates of the impact on per-person and aggregate costs for various participation percentages in the access program. In order to evaluate those costs, the antiselection model described in this was developed. Of note, this was the ACTUARIAL EDUCATION AND RESEARCH FUND 1991 PRACTITIONERS AWARD WINNER. From Actuarial Research Clearing House 1991, VOL. 2.

Description: This paper explores the use of linear programming as a tool to guide policyholders in getting the most value out of their combined insurance and investment programs. Concentrating on flexible premium universal life within the tax environment of the United States, several linear programming models are developed that can be used at the point of sale, to select the most cost effective policy from those available in the marketplace, and after issue to maximize the present value of future cash flows on the policy of an insured who is in ill-health. From Actuarial Research Clearing House 1991, VOL. 3.

Description: This paper is written totally under present Indian conditions, but keeping an eye on the future, when there will be number of insurers, and this model can be applied to any condition where a number of insurers already exist. The purpose of this paper is to attempt to measure, from the point of view of a potential life insurance policyholder, the quality of the insurers and the variability between them so that it will be helpful for potential policyholders to choose their insurers according to their requirements.

Description: Shiu derives two formulas for calculating the probability of eventual ruin in a collective risk model. This paper implements one of the formulas by incorporating an algorithm to reduce round-off error due to convolution. It gives the results of the programs for some claim distributions.

Description: This paper investigates how the concepts of asset-liability matching can be used to shape investment strategy. From Transactions of Society of Actuaries 1980, Vol. 32.

Description: This article investigates the properties of the Gompertz distribution function. Explicit formulas for continuous life insurances and annuities are given in terms of the left-truncated gamma function. Moreover, approximations for the mean, variance, skewness and kurtosis of the Gompertz distribution are also given. Finally, the article shows that using a Gompertz assumption at fractional ages produces better a approximation than the usual UDD assumption.

Description: Automobile insurers classify the risks that they underwrite in order to subdivide the portfolio into classes of risks with similar profiles. While some insurers may have sufficient historical data, several others may not have significant volume of experience data in order to produce reliable claims predictions to help enhance their risk classification systems. A database containing a pooled experience of several insurers thereby helps to produce a more fair, reliable, and equitable premium structure for all risks concerned. This paper uses multilevel models to analyze the data on claim counts provided by the General Insurance Association of Singapore, an organization consisting of most of the general insurers in Singapore. The multilevel nature of the data is due to the following: a certain vehicle is observed over a period of years and is insured by a particular insurance company under a certain 'fleet' policy. The authors show how intercompany data lead to a priori premiums and a posteriori corrections to these initial premiums. Specific focus is made in understanding the intercompany effects using various count distribution models [Poisson, negative binomial, zero–inflated and hurdle Poisson]. The performance of these various models is compared the authors also investigate how to use the historical claims of a company, fleet and/or vehicle in order to correct for the premium initially set.