Description: This article discusses the concept of Conservation of Mortality ("Conservation"). Conservation is the modeling principle that ensures consistency between assumptions of the total mortality of a population and mortality among population subsets. This article discusses the use cases for Conservation and the many ways that one could implement it in a model or an experience study. This article also discusses the potential issues that arise when using Conservation, and how one might solve or alleviate these issues.

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: CPT, NCCI, ICD, CCI, DRG, APC, PTP – understanding healthcare claims involve a dizzying array of code sets and payment methodologies, and yet the claim form is the intersection of health plan affordability, provider payment, and data analysis. This webcast will cover: • The code sets used in medical coding • Types of correct coding policies implemented by CMS and commercial payers • Payment integrity strategies to drive health plan affordability • Data analytics approaches leveraging medical coding knowledge

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: 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: In 2020 the Actuarial Innovation and Technology Steering Committee held a data visualization contest. Entries showed a variety of strengths including smart use of tools, user-friendly dashboards, and displays paired with actuarial analysis that can lead an end-user through a process of discovery. In this webcast a data visualization expert will review the winning entries with the contestants. We'll discuss how the different strengths of these entries can be combined to create a powerful tool for communication and understanding.

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.