Description: 2021 Life Meeting - Session 7D: Emerging Trends in Lapse and Mortality for Life Products 9.1.21 Recording

Description: This is a study to perform a mortality analysis of the 1898-1902 birth cohort.

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: The Society of Actuaries Individual Disability Experience Committee has completed their study of incidence experience for the period 2006-2014 comparing trends to the 2013 IDI Valuation Table (2013 IDIVT) base incidence rates. Included is the report and pivot table.

Description: The COVID-19 pandemic has had an impact on all aspects of daily life and its impact extends to how disability incidence may play out in the future. Product profitability will be shaped by how morbidity patterns, interest rate levels and other key drivers will play out into the future. In this session, our panel will discuss COVID’s impact on IDI morbidity experience as observed over the past 18 months, offer comparisons and insights in light of other insurance lines of business, and share emerging information on the on-going effects of Long COVID. Highlights will also include how regional differences and implications for insurers as the industry moves further into the COVID vaccine era.

Description: Learn about the latest developments in hospital and payer price transparency data. Hear experiences working with the data and attempts to gain meaningful insights for actuarial and other purposes. Discover challenges and workarounds associated with this data, including file size, comparability of prices, duplication of prices, aggregating provider NPIs into meaningful groupings, and missing payer information.

Description: This report describes two methods, an observation-based analysis and an actual to model analysis, to analyze long-term care insurance experience to determine if calendar year trends exist.

Description: After a sustained period of mortality improvement, U.S. population mortality improvement has stagnated in recent years. The presenters will discuss mortality improvement trends in the U.S. population and the causes of death contributing to these trends. U.S. population cause of death trends will be analyzed and compared to trends in the insured population. Mortality rates for major causes of death will be compared between the U.S. population and the insured population. In addition, assumption setting for both older age and later duration mortality as well as mortality improvement will be covered.

Description: The famous 80/20 rule in data science states that only 20% of your time working with data is spent driving insightful business analytics. The rest of your time is spent trying to query, clean and organize your data. Even with this knowledge, the majority of actuarial training/focus is on the 20 percent. This session takes a different approach, focusing solely on speeding up your work on the other 80 percent. Practical examples will be part of a code walkthrough in R.

Description: Data science, predictive analytics and AI are certainly the buzzwords these days. They are heavily used and developed in underwriting and marketing but for most actuaries, they might/may as well be science fiction. The presenters will demonstrate how a normal actuary can utilize data science techniques in their daily job function without forming an official data science team within a company. It can be done in a gradual fashion so that normal business is not disrupted and improvements are made over time. The usage of data science techniques will include demonstrations of the following areas: - Regression analysis - Economic scenario generator - Experience study - Data quality checks - Inforce compression for explicit hedging