Description: In this paper we shall present our results in terms of the estimation of human mortality rates, but the results carry over to other applications. We shall discuss a Bayesian model that encompasses both graduation [smoothing] and prediction.

Description: After reading the Panjer-Bellhouse paper in the Proceedings of the Ball State University Conference, I wondered whether their technique could be used when a realistic investment process was assumed. I believe that such an extension is necessary if the theory is to have any practical application I have had little success in trying to do this. I have decided to present some thoughts and to invite others with different perspectives to bring them to fruition.

Description: All claim reserve systems endeavor to derive estimates of the unpaid portion of claims which have been incurred over a given period of time, making use of information on numbers of claims and amounts paid on claims as of the valuation date. In this paper, a claim reserve system is described. While the system does produce the traditional type of single-point estimates of claim reserves, it also provides the user with frequency distributions of claim reserves

Description: This presentation suggests a possible flexible solution to the time and resource problems of running a large number of stochastic interest rate scenarios, by selecting a representative subset. Each interest rate scenario consists of 30 future spot yield curves, where a reasonable number of points are specified on each curve such as 12. The distribution of the scenarios is approximated by the subset and each scenario in the subset has equal weight. The method is independent of the inter rate generator used.

Description: By the use of resampling and extreme value statistics we will develop a method to reduce the time and costs of testing insurance company insolvency. Most ruin models require assumptions about the surplus distribution and/or assumptions about the claims count and severity distributions. The actuary may not be comfortable in making these ruin assumptions. Instead, he or she may generate such distributions by running extensive computer simulations of corporate models, I introduce a method to reduce the number of simulations necessary' to estimate the 1 and 0.1 percentiles of the surplus distribution. This approach 'cuts off' the tail at approximately the tenth percentile of the sample distribution and generates new tails for the distribution by resampling. Averages of the new order statistics approximate the I and 0.1 percentiles.

Description: This work describes a study undertaken to determine whether the Federal Housing Administration FHA should modify or discontinue its single-family home mortgage insurance program for investor i.e., non-occupant loans.

Description: Sooner or later a casualty actuary is confronted by the question, Given a history of paid loss amounts by calendar year, what should reserves be? Often, it is not possible to accurately gather and analyze additional data within the time constraints for the reserving decision. The algebraic reserving method presented in this paper offers one approach to rapidly addressing this problem.

Description: This is the abstract of the paper Risk Classification by Fuzzy Cluster. In this paper an algorithm for risk classification is proposed. This algorithm is based on the concepts of fuzzy cluster. We test our algorithm with two examples, the results are very promising.

Description: In Volume LXXV of the Proceedings there appeared a paper entitled Risk Loads for Insurers by Feldblum. Confidence intervals for the betas in TABLE 4 [Profit Margins and Their Standard Deviations by Line of Business] of this paper can be generated using the assumption of underlying normal distributions. However, bootstrapping operational or not for interval estimates does not require the normality assumption. The method of operational bootstrapping does not use random numbers. The method for the 4-dimensional case, used to generate the interval estimates in the current paper, is a natural generalization of the bivariate case. I use operational bootstrapping to generate interval estimates for Betas shown in the TABLE 5.

Description: The initial risk reserves in collective risk models vary according to the underlying claim distribution, and a suitable level of ruin probability. A thorough analysis of the needed initial surplus for various ruin probability levels is provided in eight meaningful examples. The claim distributions are drawn from various fields of insurance, including property damage and liability insurance.