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: This paper presents a method involving re-sampling 'with replacement but without random numbers', numerical convolutions for sums and quotients, and estimation of confidence intervals for trend in average size claim. In this paper, this method is applied to major medical claims.

Description: Eric Friedman’s comments on ‘The Case for Stochastic Present Values,” by Dimitry Mindlin

Description: Chairperson talks about the activities of the section.

Description: This summary explains the techniques used and the results from the application of futurism techniques utilized to explore mortality improvement. From the 2008 SOA Spring Meeting, Quebec City.

Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

Description: This article proposes a framework for estimating mortality improvement models and analyzing the parameter uncertainty in such models.

Description: Part 2 of an article which presents simplified problem and and presented alternate models. Answers are presented in this article. The author's final question is: If traditional actuarial models stumble over these issues, can we get it right for real world funding pension plans and funding practices?

Description: Summary of all issue articles, with theme of recognizing limits of classical actuarial methods.

Description: The July 2013 issue of the SOA’s Forecasting & Futurism section’s newsletter, Forecasting & Futurism.