Description: The SOA has developed a new “tool” using Microsoft Access/Excel for international actuaries to conduct mortality and persistency studies in conjunction with the SOA’s international experience study initiative. Professionally programmed, this new tool facilitates the work of international actuaries.

Description: Shows why predictive modeling should be a necessary tool for the life actuary, identifies examples of various limitations in traditional mortality experience analyses, and also posits various predictive modeling techniques as a means of avoiding these constraints.

Description: Medical management programs have traditionally addressed more acute and short-term issues with chronic disease. As LTC becomes an important product in the insurance industry, including disease management is likely to be valuable for reducing costs and prolonging the healthy, premium-paying portion of a claimant's life.

Description: Provides a summary of key points from the ERISA Advisory Council Report on Outsourcing (2014). The report provides interesting and important perspectives and the article encourages the reader to look at the report and consider the issues raised.

Description: This article explores the possibility of using machine learning to improve, or potentially rewrite, actuarial code within actuarial software.

Description: This article highlights business use cases where XTbML can define the tabled data in actuarial tables.

Description: The authors envision a data warehouse with information at the policy level or lower, and demonstrate how this data can be used to analyze the sources of earnings. The key to their analysis is the data warehouse, which links each policy, not only to valuation assumptions and results, but also to general ledger accounting amounts and to projections - model output that feeds the financial plan.