Description: Description * Coinsurance has not been widely offered as a benefit reduction option to offset long-term care premium rate increases. This article uses an illustrative example to evaluate the potential impact coinsurance could have on an insurance carrier's future claim liabilities and a policyholder's premium rates. It also explores various considerations insurance carriers, regulators, and policyholders should think about when evaluating whether coinsurance is the right option.

Description: Millions of aging Americans are challenged to prepare for uncertain health and financial setbacks in addition to cognitive impairment that impacts one-third of adults over age 85. Advanced planning can reduce the negative impact of impairment on personal finances, including financial exploitation, scams and fraud, and care and spending decisions that are not aligned with retirement goals. To address these issues, the SOA’s Aging and Retirement Strategic Research Program co-sponsored work on the Thinking Ahead Roadmap which was created by a team from the University of Minnesota and Stanford Center on Longevity. In this webinar, members of the research team will preview the Thinking Ahead Roadmap and the steps that people can take to help ensure their financial wishes are honored as they age. The presenters will discuss: 1. Advice on choosing the right financial advocate 2. Organizing financial information to pave the way for a smooth transition 3. Starting open and honest conversations about future money management 4. The importance of a financial power of attorney and how to obtain one 5. Shifting money management responsibilities when the time is right

Description: Mortality Model Selection and Combination in RAlternative approaches for selecting mortality models and forecasting mortality have been proposed. The usual practice is to base mortality forecasts on a single mortality model selected using in-sample goodness-of-fit measures. However, cross-validation and other alternative out-of-sample measures are increasingly being used in model selection, and model combination methods are becoming a common alternative to using a single mortality model. Such methods combine predictions from multiple mortality models to reduce model choice uncertainty and improve forecast accuracy. Explore techniques to select and combine mortality models using the freely available open source R package CoMoMo (https://github.com/kessysalvatory/CoMoMo), which extends the widely used R package StMoMo (https://CRAN.R-project.org/package=StMoMo). We will use data for the USA and other countries to discuss and demonstrate four different model combination approaches including simple model averaging, Bayesian model averaging, model confidence set, and stacked regression ensembles.

Description: In this session, the following essays from the Society of Actuaries Living to 100 Call for Essays are presented. Essays: Potential for Mortality Improvement from Cognitive and Psychological Factors – Gordon Woo, – Ph. D. How Growing Inequality in the United States Makes Long-Term Care Financing Reform A Lot Harder – Karl Polzer – MPA Alcohol and Mortality, Sam Gutterman, FSA, CERA, FCA, FCA, HONFIA, MAAA

Description: Description of Long Term Care programs in various European countries.

Description: Table constructed from lifetime long-term care cost studies conducted by P.J. Eric Stallard, ASA, FCA, MAAA, Center for Demographic Studies, Duke University.

Description: The Aging and Retirement Strategic Research Program is pleased to make available a report describing the results of analysis into how the supply of neurology specialists for diagnosis and care of dementia relates to historical LTCI cognitive claims.

Description: This is the second Intercompany Study of Long–Term Care Insurance. For this report, the committee gathered and refined data that dates back to 1984. This report combines and analyzes data received from 14 insurers that agreed to provide information to further the knowledge of long–term care insurance.

Description: This is the second Intercompany Study of Long–Term Care Insurance. For this report, the committee gathered and refined data that dates back to 1984. This report combines and analyzes data received from 14 insurers that agreed to provide information to further the knowledge of long–term care insurance.

Description: "On the decomposition of mortality models into causes of death – Andrés M Villegas Ph.D – UNSW Australia, Madhavi Bajekal, Ph.D.,HONFIA, University of London, UK, Steven Haberman, Ph.D. – Bayes Business School, University of London, UK Forecasting cause-specific mortality rates using the insights from the cointegration analysis, Séverine Arnold, PhD, Viktoriya Glushko, Department of Actuarial Science, Faculty of Business and Economics (HEC Lausanne), University of Lausanne, Switzerland"