Description: This paper employs a static-component projection methodology as a first step in a more complex research agenda focusing on developing detailed population projections in which mortality, disability, and disease are represented as linked phenomena with changes in any one impacting the other two. From Retirement Needs Framework, M-RS00-1.

Description: Article provides a market scan of recent state proposals for Medicaid work requirements as well as measures the impact to enrollment in different states.

Description: Results of survey, conducted recently by the Taxation Section of the Society of Actuaries, on how federal income tax is reflected in the projection work being performed.

Description: Summary of NAIC's Winter National Meeting

Description: Explores the open vs. closed systems debate with regards to actuarial modeling and exposes the over-simplification. Valuable for anyone who uses models.

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

Description: The article describes the key components of actuarial model, leading practices in designing them, and characteristics of well-built models.

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: 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: 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.