Description: The chairperson of the section council issues call to members asking them to volunteer. He indicates that in particular, with the emergence of complexity science and other underutilized tools, there is plenty of room for volunteers, especially open spaces for new thought leaders.

Description: Specifies 6 rules which help shape not only good crime-scene analysis, but good futures practice, as well. These rules address project management and control.

Description: A summary of the activities of the Forecasting & Futurism Section, including research initiatives, participation in Delphi studies and sponsoring of seminars.

Description: The purpose of this article is to provide a refresher on regression and times series models so that actuaries will feel more comfortable building forecasting models.

Description: The Future Ain't What it Used to Be...

Description: This article shows how to use a RBF Neural network to predict if a breast tumor is malignant. The network is trained using a genetic algorithm that uses C# multi-threading.

Description: Uncertainty of a predictive model is a fact of life that many insurers could be overlooking at their peril without a framework for assessing it. The article provides a framework to understand the prediction uncertainty, which can be critical for the insurance operations using predictive models. Coin toss example explains model uncertainty and randomness inherent in making predictions to the number of heads expected. A mortality analysis case study illustrates how the Bayesian methodology can be used to develop the prediction uncertainty. In particular, the article shows that the Bayesian framework is a way to combine historical data and actuarial judgment, and directly address the model uncertainty through its posterior distribution.

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: Discusses the duality of the market-consistent and traditional actuarial approaches to pricing and valuations, and the need to exercise flexibility of thought to reconcile the opposing viewpoints.