Description: Prepared for the Society of Actuaries by STATLAB at the University of Western Ontario, this report contains the results of a cash flow testing, ‘CFT,’ software survey performed in 2004. The results were based on the responses of 110 life insurance companies in the U.S. and Canada. The goal of the survey was to produce a report that will serve as a reference for comparing the available CFT packages and lead to better software and modeling techniques. CFT refers to analysis which is used to support both the Asset Adequacy Analysis for the Actuarial Opinion for U.S. companies, and the ALM Provision for Adverse Deviations in applying the Canadian Asset Liability Method to determine reserves for Canadian companies.

Description: Panelists at this session of the SOA 1998 Annual Meeting discuss the results of two SOA research projects. One study looks at mortality rates as a function of lapse rates. The other study develops a model for relating mortality and lapse rates.

Description: This paper presents a statistical analysis of advanced age mortality data, using extreme value models to quantify the upper tail of the distribution of human life spans. From 2005 Living to 100 and Beyond Monograph, M-LI05-1.

Description: This paper examines the following three questions by reviewing literature that identifies and evaluates the tradeoffs among annuitization and self-managed drawdown strategies: 1. How DO Retirees Draw Down their Financial Savings? 2. How COULD Retirees Draw Down their Financial Savings? 3. How SHOULD Retirees Draw Down their Financial Savings?

Description: This paper develops a general approach to actuarial calculations in applications that can be modeled as multi-state processes. Such situations arise when benefits are payable upon a change in the status of the insured or while the insured maintains a given status. From the Transactions of Society of Actuaries 1994, Vol. 46.

Description: This paper presents a model for analyzing the impact of underwriting cycles on an insurer’s surplus. The model allows the insurer to vary its security loading in response to the cycles, with a strategy parameter that indicates the extent to which the insurer follows the loading which prevails in the market. The insurer’s claim rate is also allowed to vary to reflect exposure changes that result from the insurer’s strategy. The paper analyzes ruin probabilities using both simulation and a Lundberg-type upper bound which is developed in the paper. It finds that the latter is suitable and convenient for comparing ruin probabilities under the different insurer strategies.

Description: The abstract for the paper An Extreme Value Analysis of Advanced Age Mortality Data.

Description: This paper presents an analysis of mortality in a sample of 441adults aged 55 to 85 at baseline, who were observed for eight years. The study was initiated for the purpose of analyzing age-related changes in a variety of physical variables and their impact on functional independence. The modeling approach is discussed and the factors which were most significantly related to mortality.

Description: In this paper, the authors show how probabilities and actuarial values may be calculated using a time-homogeneous Markov model. Piecewise constant transition intensities are suggested as a way to extend the approach to the inhomogeneous case. From Actuarial Research Clearing House 1993, VOL. 1.

Description: This is the abstract of a paper that presents a model for examining the effect of various relationships between mortality rates and lapse rates on the mortality experience of a cohort of insured lives. It takes an individual approach rather than the aggregate approach used in traditional methods of analyzing selective lapsation. The model assumes that insured lives are healthy at policy issue, but may later move to an impaired state from which the lapse rate is zero. Associated with each insured is an unobservable 'risk level' random variable, which reflects the heterogeneity of the insured group. Individual mortality and lapse rates are functions of the risk level. A numerical illustration provides some interesting results obtained using this model.