Description: Describes what a Delphi study is and why actuaries might want to use one.

Description: Identifies current trends and considerations when setting the mortality improvement assumption for individual life insurance in the US.

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: An introduction to Hidden Markov Models, which are used extensively in speech and facial recognition technology. They are a useful tool in forecasting time series and in developing categorizations of data based on the values of the data themselves.

Description: A general introduction about predictive modeling in insurance applications. Some basic models are discussed, such as Generalized Linear Model(GLM), Calssification and Regression Tree Model. Other models are also briefly introduced, including data clustering, neural networks and support vector machine.

Description: On October 30, 2006, the UK government's Stern Review on the Economics of Climate Change made startling claims about the present value today of climate change effects predicted to emerge primarily 150 years or more in the future. The ensuing debate included challenges to and defenses of the particular methodology used and parameter values selected to perform the discounting of future values. Noticing an overlooked faux pas in the Stern Review, this presentation uncovers the likely motivation for choosing the most mystifying of the parameters values, and provides a lesson on the underpinnings of the basic tool of actuarial science.

Description: The comments of DxCG about their participation in the SOA study A Comparative Analysis of Claims-Based Tools for Health Risk Assessment.

Description: Research report sponsored by SOA to model and compare projected costs of different proposals for a Medicare prescription drug coverage plan. 3 types of costs are studied: net benefit cost estimates per member per month, continuance table data, and projected annual costs to the government over 10 years for two selected plan designs.

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.