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: Even the best algorithms are only effective if they are trained on appropriate data. This article discusses common pitfalls in creating a training data set.

Description: This article discusses challenges that short-term predictions have on actuaries' reputations, both as individuals and as a profession, and discusses strategies to improve our professionalism and better manage this risk.

Description: Presented at June 2002 Spring Meeting. A noted expert with a degree from the graduate program in Studies of the Future at the University of Houston-Clear Lake discusses long-term forecasting and planning, the future of information technology and technology transfer, strategic planning and the development of future scenarios.