Description: Appendices A, B, and C for the Factors That Affect Retirement Mortality FARM Phase II. These appendices provide the format for data submission by contributors to the Mortality and Turnover Study, the SOA & LIMRA Experience Studies, and the Structured Settlement Study.

Description: On October 30, 2015, the SOA Assumption Development and Governance Group, an informal discussion group consisting of nearly 200 interested actuaries with topics pertaining to actuarial assumption development and governance, organized an industry discussion call on end-to-end assumption documentation practices. The purpose of this call was to generate a large list of ideas for best-practice assumption documentation. More than thirty companies were represented in the call, including direct insurers, reinsurers and consulting firms. This article is the work product of the discussion written by Laurie Li and Alex Zaidlin.

Description: Author compares in-depth statistical review of baseball team to the actuarial profession, Issue No. 47.

Description: A summary of the 2001 Individual Life and Annuity Expense Study

Description: Data requirements for the Society of Actuaries cancer experience study, for those submitting exposure and claim information.

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

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: Using the Internet as a Pricing Tool clinical background information, defining the change in coverage, collecting data, data quality and data limitations. Issue No. 39.

Description: On October 30, 2015, the SOA Assumption Development and Governance Group, an informal discussion group consisting of nearly 200 interested actuaries with topics pertaining to actuarial assumption development and governance, organized an industry discussion call on end-to-end assumption documentation practices. The purpose of this call was to generate a large list of ideas for best-practice assumption documentation. More than thirty companies were represented in the call, including direct insurers, reinsurers and consulting firms. This article is the work product of the discussion written by Laurie Li and Alex Zaidlin.

Description: We highlight a new approach leveraging predictive analytics to identify high risk and rising risk opioid users for more effective screening and follow-up care.