Description: Development of relevant industry mortality experience for different market segments. Details about the 2017 CSGI Mortality Table for guaranteed issue products.

Description: The article is Part 1 of two articles that provide a case study for the development of a profitability and risk dashboard. The sample dashboard provides distilled information regarding actual to expected (A/E) ratios for key risks, agent quality scores and customer value scores. The dashboard would also provide the value of new business written, surplus strain, debit balances, and expected losses on debit balances at different levels, down to the agent level. A product mix index is provided, together with visual comparisons of key metrics to the company's business plan. The Part 2 article will add information to the dashboard regarding risk margins, target capital, and company value.

Description: Building on the Part 1 article, Introduction to the Representative Scenarios Method, this article describes testing the methodology with respect to four product types, fixed indexed annuities with GLIBs, level term life insurance, universal life with secondary guarantees, and variable annuities with GLWBs. This Part 2 article describes testing results, refinements to the RSM methodology, and next steps.

Description: Describes a process for identifying relevant industry experience to credibility-weight with relevant company experience to set modeling assumptions and margins.

Description: Describes a process for identifying relevant industry experience to credibility-weight with relevant company experience to set modeling assumptions and margins.

Description: Discusses Aug. 23, 2007, meetings in Salt Lake City, Utah, about principles-based approach for both reserves and risk-based capital, RBC.

Description: Examination of full surrender and benefit utilization industry experience for Variable Annuities with and without Guaranteed Lifetime Withdrawal Benefits. Part 1 of 3 articles focuses on full surrenders and building a dynamic surrender function using predictive modeling tools.

Description: Introducing the Respresentative Scenarios Method, the Motivation and Goals, how the methodology works, and what key information can be derived.

Description: Describes using the new multi-risk scenario generator to create sensitivity tests at moderately adverse probability levels, resulting in margins to use for PBR.

Description: Proposes an approach to develop dynamic assumptions for living benefits using a combination of available experience data and predictive modeling techniques.