Many advanced statistical techniques are available for use in modeling health benefits. A few examples
are generalized additive models, generalized linear models and non-parametric models. These methods
are well known to most statisticians but not most actuaries. The presenters will show how these methods
can improve health insurance analyses in applications such as projecting health insurance claims and
pricing health benefits. At the conclusion of this session, you'll have an understanding of how stochastic
modeling can get more accurate results or even some new results for your employer and/or clients.
Case studies will be provided to help you gain a basic understanding of how to perform the techniques in
product strategy, pricing, underwriting and enterprise risk management.
Literature/reference will be shared with you for more thorough understanding.