Description: This paper presents a method involving re-sampling 'with replacement but without random numbers', numerical convolutions for sums and quotients, and estimation of confidence intervals for trend in average size claim. In this paper, this method is applied to major medical claims.

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: This paper provides a method for estimating long-tailed unpaid losses from paid loss development using trended generalized bondy development. From Actuarial Research Clearing House 1993, VOL. 3.

Description: Presenter offers ways in which actuaries might set credibility levels to be used by underwriters to set group health insurance expected benefits. From the Record of the Society of Actuaries, Vol. 24, No. 2.

Description: This article describes a method that can be useful when re-fitting a risk score model to a population of only moderate size. Learn how to use concepts like ridge regression to train a model with partial credibility.

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

Description: Exploration of sources of volatility in retiree health valuations, noting how volatility arises and might be mitigated, with discussion of valuation parameters more problematic for retiree health benefits than for pensions. Three significant influences on retiree health valuation volatility are covered-- changes in benefit level, fluctuations in cost level, and alterations in eligibility for, or duration of, benefit – and attention focused on the last two. Specific conclusions result in recommendations, which are supported by practical examples contrasting volatile measurement results with those likely from the recommended practices. Theoretical discussion includes health claim variation, health trend usage, financial economics, option pricing, discount rates, and deterministic vs. stochastic modeling.

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.