Description: Discusses the market, demographic, and macroeconomic factors that affect actuaries' choices for the assumptions they use in the pricing and valuation of many insurance products.

Description: This study quantifies the range of intercompany variability in mortality. Mean actual-to-expected (A/E) ratios based on amount were calculated in each quintile for every combination of six key variables.

Description: The SOA Research Institute’s Mortality and Longevity Strategic Research Program is pleased to make available a research report that quantifies differences in mortality and disease prevalence by health status. Additionally, period life tables by health status, sex, and age are available in Appendix D.

Description: Every patient leaving the hospital has personal life-context circumstances that impact their chances of successful recovery and complications can be costly. Complex care management impacts over 50 percent of health care spend, with the admitted commercial population driving 37 percent of spend or $177M per 100,000 lives and the Medicare population driving 53 percent of spend or $600 million per 100,000 lives. The stakes are high, but existing care management solutions are mostly clinical and navigation call centers provide fragmented and outdated patient management systems, and do not address individual life-context. Discharged patients therefore remain underengaged and undercompliant, leading to costly complications. Innovative technology can help enable and integrate systems and existing infrastructure to leverage evidence-based contextualized care that will enhance care management, improve efficiency, and drive a better experience and outcomes for patients. This technology helps codifies life context, dynamically stratifying and engaging members digitally and telephonically helping virtual care teams to be more effective and efficient. In a recent randomized clinical trial, this technology and approach has shown a 50 percent reduction in the total cost of care, cutting the average and total cost of readmission, increasing virtual care team impact and member engagement and trust.

Description: Walk through real-life examples of how artificial intelligence (AI) can be used to drive insights and aide actuaries in improving the management of their company's inforce book of business. Hear a panel of experts go step-by-step through case studies, showing how practitioners leveraged predictive analytics for solutions to tap further into their data and draw improved insights.Leave the session with knowledge of how to partner advanced machine learning techniques with the actuarial skills and insights to better understand policyholders' behavior to more efficiently enable accelerating revenue and further profit realization.

Description: Amid macroeconomic uncertainty, proactive lapse management is becoming a growing strategic focus for Life and Annuity carriers. Interest rates have been increasing rapidly during the last eighteen months and insurers, especially annuity writers, have started to see higher lapses and withdrawals. After a prolonged low interest period, many insurers will have to (re)build capabilities to enable proactive lapse management.

Description: The SOA has conducted a mortality study covering deferred annuities, both fixed and variable. This is a brand new area of analysis for the SOA's Individual Annuity Experience Committee and should be of critical interest to the industry. Previous industry annuitant mortality studies have focused on payout annuities, as well as the specialized structured settlement annuity market. Traditionally, mortality had not been seen as a critical assumption for deferred annuities. As the products have evolved over time, especially with the popularity of enhanced death benefits for variable annuities and guaranteed living benefits for both variable and fixed annuities, mortality has taken on increased importance. The results of this study have recently taken on even greater significance, as regulators are seeking mortality assumptions for the standard projection scenario for VM-22 (fixed annuities), as well as a potential update to those assumptions in VM-21 (variable annuities). By attending the session, you will: - Understand how deferred annuitant mortality compares with established annuitant mortality tables. Note that annuitant mortality tables, including the most recent 2012 tables, were developed based on payout annuitant mortality experience. - Become aware of the differences in mortality experience between fixed and variable annuities. - Gain insights into the effect of various guaranteed benefits on anti-selection and subsequent annuitant mortality, both for death benefits and living benefits. - Understand the durational aspects of emerging mortality experience, particularly for deferred annuities with guaranteed benefits.

Description: Regression to the mean (RTTM) is inflating your health care intervention evaluations if you are not carefully managing it's omnipresent and significant impact RTTM is the statistical phenomenon which arises when comparing sequential data points when an initial observation is extreme or an outlier, and states that with no other intervention, future observations will be closer to the average. Members who had high costs last year will, on average, have lower costs this year, even in the absence of any intervention or clinical program, simply by 'regressing' to the mean. This means that if your clinical programs are simply targeting members who had adverse medical experience last year, you’re targeting the wrong people. And if your savings methodologies are simply last year’s costs minus this year’s costs, the savings are inflated. By attending this session, you will be able to identify situations where RTTM will be a significant factor, how to eliminate it's impact when performing retrospective evaluations, how to identify prospects for clinical intervention with RTTM in mind, and more.

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: Anti-obesity medications have been met with reluctance from payers and employee benefits consultants who often lack analogs or empirical data to estimate the cost impact of new therapies coverage. Health plans considering coverage of anti-obesity medications will need to assess and manage the potential costs of covering these new therapies in context of their overall obesity management strategy, including coverage of nutrition counseling, weight management, and bariatric surgery.