Description: This paper introduces the modern concepts and definitions of the statistical subject of life testing, and ties them in with corresponding concepts of actuarial science. This paper additionally presents a justification of some common laws of mortality. Discussions of the paper are included.

Description: This abstract describes a paper that investigates how to apply a stochastic mortality model in the presence of missing data, using 'multiple imputation'.

Description: While many know that machine learning is a big deal and even have a general idea of what it is, many do not know what machine learning can do for them. As an alternative to citing achievements or explaining algorithms, this article outlines the challenges that occur in statistics and the solutions that machine learning offers. Some of those challenges include correlated predictors, missing data, data interaction, and prediction intervals. Corresponding solutions include regularization technics, missing value imputation with KNN, tree based models, and cluster analysis for backtesting.

Description: In Medicaid rate development, actuaries have not historically shared models that developed the margin (i.e., underwriting gain) assumption. This is unfortunate, given the margin assumption is one of the most critical components of the rate development in ensuring financial solvency of the Medicaid managed care organizations (MCOs). In this session, we will discuss the primary components of the this assumption and will share working models that help actuaries quantify these components—including the cost of capital and risk (or contingency) margin. We expect a lively discussion as we “open the black box” and discuss these actuarial assumptions in the public for the first time.

Description: According to the Actuarial Standards Board’s Actuarial Standard of Practice No. 49 (ASOP 49), actuarially sound Medicaid managed care capitation rates will include a provision for underwriting gain in order to provide compensation for the risks assumed by an MCO. However, there is no generally accepted method for quantifying underwriting gain in managed Medicaid capitation rates. This article discusses a new model developed to address this void and calculate underwriting gain. The model was developed by researching existing financial literature and performing a statistical analysis of industry data to build out a framework that can be leveraged to estimate underwriting gain.

Description: Presented at Living to 100 Symposium, January 2011. This study adapts the idea of regular discount sequence in the bandit problem, and uses it to interpret life expectancy, as well as to develop a model for survival probabilities. Data came from multiple countries.

Description: The financing for Social Security is a pay-as-you-go system, rather than the full-reserve system utilized in private insurance, and the financing conditions of the trust funds have more uncertainty than does the reserve in private insurance. Traditionally, the financing conditions have been decided by a deterministic approach using economic and demographic assumptions that rely upon negotiation among experts at various government agencies. This paper proposes an econometric approach, called the 'co-integrated multivariate time series model,' for forecasting the financing conditions of the trust funds. This stochastic approach not only establishes the interrelationships but also clarifies the co-movements among the economic assumptions. Furthermore, it helps analyze the original assumptions rather than the differences of the nonstationary assumption variables adopted by researchers in the past that are more difficult to interpret. Use of this approach permits the assessment of the probability distribution of the future balance of trust funds instead of assessing estimates from the three alternative deterministic assumptions. This distribution will provide policy-makers with a better assessment of stability of the trust funds.

Description: A summary of how the Forecasting and Futurism Section is networking with other SOA sections and with external organizations to collaborate on various projects. Also highlights new events and projects happening on the forecasting and futurism front.

Description: The author discusses the use of genetic algorithms as they apply to actuaries, specifically the application of characteristics and their potential to solve life insurance asset and liability management problems. He also highlights various ways genetic algorithms can be used to solve a variety of actuarial problems.

Description: This paper presents the fundamentals of creating and using projections. From Transactions of Society of Actuaries 1950, Vol. 2, No. 4.