Description: The purpose of this paper is to illustrate the use of a new approximation to determine contingency reserves against adverse mortality experience for a portfolio of life annuity contracts.

Description: This is a discussion of the paper, Frequency Distribution of Mortality Costs by John M. Boermeester, which used a series of random numbers to estimate variables under study.

Description: The purpose of this paper is to introduce a practical method for interpolation and smoothing and give a number of numerical examples using the method. The method is a variation of the Whittaker-Henderson method. Discussions of this paper are included.

Description: This paper presents a few formulaic examples displaying the advantages of geometric methods over arithmetic methods and provides some theorems proving the increased accuracy geometric methods can provide for interpolation or extrapolation

Description: This paper by John Mereu describes a method for mathematically computing the expected loss under a group life contract in excess of a stated limit. The paper also shows how to compute the variance and standard deviation of the stop-loss claim and suggests how the method can be extended to group insurance benefits where the claim amount per certificate is not fixed. Paper is followed by discussions from several people

Description: This note describes a mortality investigation procedure in which the expected mortality applicable to each new policy for a period of about three years after issue is estimated by use of persistency factors. Discussions of this paper are included.

Description: This paper will investigate the problem in estimating mortality rates using data obtained from insurance company records.

Description: It is well accepted that, for ages 30 and above, human mortality rates increase with age, yet no established graduation method makes direct use of this knowledge. Such a method is offered in this paper.

Description: This paper presents simple Bayesian graduation models that substantially ease the prior elicitation burden, and also describes a Monte Carlo integration approach that greatly reduces the computational load.

Description: In this paper, methods are presented that allow the systematic graduation of multidimensional data subject to linear constraints. With these constraints the practitioner can impose limitations on the graduation that agree with prior knowledge. Discussions of this paper are included.