Description: The results obtained during the last one-third of the research project and the project at whole are presented. The report only contains brief descriptions of the results which are placed in addendums and which are in reality copies of papers and a chapter of a book submitted for publication. Some theoretical and applied problems induced by the research are discussed.

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: In this paper, we propose measures of the risk that the value of the liabilities becomes larger than the value of the assets, and this especially for insurance companies. We study probabilities of mismatching and a degree of mismatching in unsegmented and multidimensional models of the balance, in which we stress the influence of interest rates on the active and passive side of the balance.

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: This paper's objectives are to reduce the variation of life expectancy due to changes in the closing out method and give more homogeneous old age mortality surface for the Algerian population. The paper will also provide readers with a general methodology to extend mortality to old ages for the Algerian population starting from adult mortality data.

Description: This presentation compares continuous-time multi-factor affine cohort mortality models and presents estimation results for an affine multi-factor, multi-cohort mortality model.

Description: This abstract describes a paper that proposes a multi-population Global Vector Autoregression (GVAR) mortality model, in which the joint mortality dynamics of all populations are formulated in a large vector autoregression model with a set of contemporaneous global mortality factors.

Description: In December 1997, the Society of Actuaries held a conference whose focus was actuarial and financial modeling. During the course of that conference, one of the speakers mentioned a number of technologies his firm was using for modeling, which were either unfamiliar or only vaguely familiar to some of the audience. The purpose of this paper is to define each of the technologies mentioned during that presentation and to briefly describe their distinguishing characteristics. The technologies discussed in this paper are statistical pattern recognition [SPR], neural networks [NNs], genetic algorithms [GAs], simulated annealing, fractal analysis, chaos theory, rule induction, data fusion algorithms [DFAs], data compression, fuzzy logic, case-based reasoning, and expert systems.