Description: Outline of modifications to formulas in previously released FORTRAN program to compute two-life annuities, including those designated 'qualified joint and survivor annuities' in the ERISA Act of 1974.

Description: When setting reserves, multiple methods are often used in the creation of the reserve estimate. Judgment is warranted to combine these different estimates into a final recommendation. This paper describes two techniques that can be used to combine these estimates that may result in better accuracy and lower variance.

Description: This paper documents the R language and its applications.

Description: Presented at May 2005 Spring Meeting. Panelists discuss currently available data standards, forecasts about the future uses of data standards, and standards being adopted by Information Technology departments.

Description: Many executives are talking about predictive analytics uses in health insurance.

Description: The purpose of this paper was to describe some of the actuarial aspects of one company's electronic system and to discuss the underlying analyses and comparison of alternatives that led to the selection of particular electronic procedures to solve certain actuarial problems. Followed by several discussion papers submitted

Description: Members of the American Academy of Actuaries’ Solvency Committee have put together an acronym reference chart. This handy guide can be folded up to fit in your wallet and quickly reviewed so you can fearlessly enter an elevator.

Description: Health Watch, Issue 79, December 2015, Health Watch

Description: The April 2016 Issue of The Modeling Platform

Description: Insurance regulations are undergoing a paradigm shift in determining capital and reserves. With Solvency II in Europe and principle-based reserving in the United States, the old formula-based static approach is being replaced or supplemented by a principle-based dynamic method. This change requires enhanced modeling, stochastic simulation and sensitivity analysis, which pose challenges to insurers whose infrastructure has not been built for big computation. This paper introduces a method of building complicated models with small reusable modules and running them on a many-task computing platform to achieve high performance with simplicity. The paper presents an example of a term life insurance model built to take advantage of computer hardware for parallel computing at the task level.