Description: In this paper the author presents an application of Bayesian forecasting methods to the estimation of reserves for outstanding claims. He assumes that the time number of periods it takes for the claims to be completely paid is fixed and known, that payments are made annually and that the development of partial payments follows a stable pay-off pattern. From Actuarial Research Clearing House, 2003, Vol 1.

Description: This abstract describes a paper that introduces an approach to sensitivity analysis for quantitative risk models such as those used in solvency calculations.

Description: A contingency table is a set of counts or frequencies obtained by classifying observations in two or more different ways. Log-linear analysis is applied to disability terminations, linking them to variables such as sex, age, region and maximum benefit period. Application to risk classification and underwriting are outlines.

Description: The author comments on the article Exposure Formulas Based on the Assumption of Uniform Distribution of Deaths written by T.N.E. Greville.

Description: Table of Contents

Description: This paper presents an additional view of estimating parameters of the force of mortality using Bayesian methods. Some examples are provided. From Actuarial Research Clearing House 1993 VOL. 1.

Description: This paper provides a method for estimating long-tailed unpaid losses from paid loss development using trended generalized bondy development. From Actuarial Research Clearing House 1993, VOL. 3.

Description: The method described in this paper is to allocate surplus to each category of business and reserves in proportion to its estimated effect on an insurer's surplus variation. Risk load for each category of business is then selected so that the return on allocated surplus for each category is equal to the overall return on surplus. From Actuarial Research Clearing House 1993, VOL. 3.

Description: In Gary Venter's paper on Credibility in Foundations Of Casualty Actuarial Science, he suggeted that estimating the variance of the estimated least squares credibility Z would help provide an understanding of the accuracy of the calculation. This paper examines this suggestion. From Actuarial Research Clearing House 1994, VOL. 1.

Description: In the paper, the authors implement the empirical version of a robust Kalman filter credibility estimator with a data set, and compare its sensitivity to large claims with that of other credibility estimators in the literature.