Description: This paper provides an overview of deductible ratemaking , and the pros and cons of various approaches under different parametric models are compared

Description: The report examines various benchmarks for analyzing option adjusted spreads of the major fixed income asset classes of life insurance companies.

Description: Compilation of the answers gathered through the survey, Will Retirement Assets Last a Lifetime?

Description: The purpose of the SOA project Modeling Long Term Healthcare Cost Trends for Valuation is to provide a benchmark projection of medical cost increases and provide a user-firendly model for making alternative projections. This paper presents sample output from the model, technical documentation of the model, FAQs, and a review of the literature and references.

Description: The SOA’s research objective is to provide guidance to state exchange officials and administrators, federal officials and administrators, and actuaries assisting states and health plans. The goal of the project is to estimate the morbidity and/or cost for newly insured individuals in the individual market (and to some degree, the small group exchange) relative to the morbidity and/or cost for the current commercially insured population. This analysis will primarily focus on the individual, non-group market. In order to plan for the impact that these currently uninsured individuals will have on the health insurance markets, it will be important to understand their costs relative to the costs for people already enrolled, for whom many health insurers have experience and data.

Description: The project goals are: • Illustrate an analytical framework using stochastic forecasts and efficient frontiers for hypothetical retirees, for determining retirement income generators (RIGs) that could be offered in a DC retirement plan. • Determine the RIGS or combination of RIGs that could be considered optimal according to specified criteria. • Encourage plan participants, plan sponsors, and advisors to adopt a portfolio approach to developing retirement income strategies.

Description: With the decline in traditional defined benefit plans, cutbacks in Social Security already legislated, and further ones possibly needed to maintain solvency, retirees increasingly must rely on their own ability to manage their retirement income. Relatively few retirees purchase annuities, leaving them with investment and distribution decisions concerning their accumulated savings. Increasing life expectancy and improved health at older ages raise the issue of whether people should consider postponing retirement as a way of assuring adequate resources during retirement. During retirement, they face complex issues concerning how to manage various risks. Increasingly, people planning for retirement have access to financial planning software, much of it available over the internet for free. This study, sponsored by the Society of Actuaries and the Actuarial Foundation, assesses the extent to which the retirement planning programs analyzed help users understand post-retirement risks.

Description: Compares discount rates for computing pension plan liabilities for funding purposes across single employer, multiemployer and public pension plans in the U.S.

Description: In this article, the authors discuss the Experience Study Working Group surveys of published embedded value EV financial assumptions they have been conducting.

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.