Description: A description of the operation of an R package for experience studies. Premium patterns, lapse rates, and mortality rates can be calculated.

Description: Using the Cox proportional Hazards Model to improve underwriting debits and credits.

Description: First article in a series that walks through the progression from developing LTC assumptions using traditional methods to doing so using predictive analytics.

Description: The presenters will explore policyholder experience data for long-term products, risks of over-fitting data in developing behavioral models, and ways to mitigate these risks and develop a sustainable and coherent framework to translate complex policyholder behavior experience data to behavioral models using company- and industry-level data. At the conclusion of the session, attendees will be able to: - Identify key drivers of policyholder behavior for long-term product - Understand the risks of over-fitting data and a false sense of precision in developing behavioral mode - Understand techniques that can be used to mitigate these risk

Description: Third article in a series on how to use predictive analytics to improve the development of long-term care projection assumptions.

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

Description: Hot topics and emerging trends in assumption development in US life insurance companies

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: Description of methods for extracting and reformatting the existing mortality tables using R. Methods and formats for storage are discussed in the second article. Intent is to generate discussion regarding the format of our stored mortality tables. Value is in the demonstration of task automation in R and in the reduction of duplicate work across companies related to reformatting tables.

Description: The article explores the possibility of using the emerging technology for life insurers to build a monitor system for better risk and profitability management.