Description: Research report describing an analysis of experience transition rates between Long Term Care insurance claim settings over the course of a claim. Examples of such transitions are from an assisted care facility to home health care or from home health care to a nursing home.

Description: The 2009 Estonia experience study includes both mortality and persistency studies of policies in force any time during the 2006-2008 study period. The study applies to the entire portfolios of the contributing companies and these companies represent the vast majority of the Estonia individual life insurance market. Separate studies were performed based upon policy counts and insurance in force. Actual mortality was compared to expected mortality based upon the SOA 1975-80 select and ultimate mortality table.

Description: This article provides a very high level overview of accelerated underwriting programs and their history in the US marketplace. It then discusses setting up an actuarial control cycle for such products and some items related to risk management that are helpful in this setting. Pros and cons of retrospective studies, random holdouts, targeted holdouts and post issue analysis are discussed. A mathematical example of how to estimate the mortality impact of such programs from early emerging experience is provided.

Description: Expanding channels and datasets to understand our policyholders

Description: The Mortality Improvement subgroup of the American Academy of Actuaries’ Work Group and the Society of Actuaries’ Mortality and Longevity Oversight Advisory Council released a recommendation for a set of improvement factors that vary by gender and attained age to be used in conjunction with the 2008 Valuation Basic table or the 2015 Valuation Basic table for AG-38 purposes. This recommendation has been adopted by the NAIC’s Life Actuarial Task Force.

Description: Hear about some applications using quantile regression-derived individual and group claim distributions and how they may be used in various traditional health care modeling situations. The session will not focus on the technical use of quantile regression to obtain estimates of claim distributions, but more so is intended to focus on the uses of the distributions in actuarial modeling and the additive framework in assessing claims distributions. Presenters will show how actuaries can better assess risks by focusing on the individual- and group-specific claims distributions as opposed to traditional point-estimate-centric models.

Description: CMS has required hospitals to publish their chargemaster rates, cash discounts and negotiated rates as of January 1, 2021. Our panel is comprised of a data strategist, an executive from a large hospital system and an actuary.

Description: One common barrier to employing GLM modeling is the lack of sufficient data. This limitation often comes from the combination of the considerations in ASOP No. 25 “Credibility Procedures” and the fact that GLMs assign full credibility to the data. Explore the possibilities of credibility-based regression by expanding the intended purpose of modeling analysis from producing a single model as output to producing data insights, credible differences, and a range of reasonable models.

Description: Have you ever struggled to make business decisions because your internal mortality studies lack credibility? Have you ever launched a new product or initiative and wanted to understand mortality risk before claims experience emerged? This session will discuss how predictive models can help actuaries enhance their traditional mortality studies with leading mortality leading indicators to be more nimble to market demands.

Description: This session will introduce attendees to a variety of powerful tools in Excel designed for manipulating and analyzing large datasets, including seriatim data with millions of rows. Alternatively, the attendee with learn equivalent strategies using R. Both approaches can validate each other.