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

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

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.

Description: Presented at April 1986 Spring Meeting. This session discussion is about what analysis is effective in measuring recent medical care experience and are the projected cost-containment savings presented to plan sponsors being realized.

Description: Discusses cost-benefit decision-making for acquiring electronic data-processing equipment and installation issues, ability of small companies to compete in pension trust arena, effectiveness of various agency compensation programs in stimulating sales and improving persistency, success of sales to substandard risks and rating methods, and pricing, reinsurance and experience with individual hospital and medical policies.

Description: Presented at April 1985 Spring Meeting. This session focused on recent experience of programs designed to contain health care costs.

Description: Using Healthcare Claims Data to Create Actuarial Models.

Description: Read this report to learn more about interpretable machine learning techniques for health insurance fraud detection.

Description: Presented at October 2001 Annual Meeting. Explores current and projected Internet trends and how they may change the way the group health and non-medical business operate.