Description: This paper is intended to acquaint actuaries with a simple and practical application of the ruin function technique in the determination of the C-2 mortality risk reserve needed for individual life insurance business. Followed by 2 discussion papers submitted

Description: From the 1985 Valuation Actuary Symposium Discussion of the practical application of cash flow testing in the valuation process.

Description: This paper uses contingent claims analysis to evaluate portfolios of vulnerable private loan guarantees and investigate their risk diversification properties.

Description: This paper explores the principles upon which experience-rated group insurance currently is based and discusses the question of whether or not these principles are sound. Followed by discussion papers submitted by several authors

Description: Regime switching models have become a popular tool in econometric time series modeling since their introduction in Hamilton [1989].These models have been widely applied for equity-returns for investment guarantees. A prominent risk management challenge is hedging these guarantees, given the equity regime switching process. This presentation develops some methodologies for regime-switching portfolio replication and use real world data to demonstrate and evaluate their effects. A Bayesian approach for regime switching model fitting is used, which allows for the examination of the robustness of each of the optimization methods when parameter uncertainty is present.

Description: A new health insurance pricing model takes external market prices into account, as well as regulatory rate restrictions and other traditional pricing factors. Rather than being assumed at the outset, lapse rates emerge from the model, along with assessment spiral & loss ratio projections. Under the model optimal pricing strategy depends on whether the class being rated has a healthier than average mix of risks.

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.