Description: Discuss policyholder behaviors that evolve throughout the life cycle of a typical VA annuitant, with supporting data from industry-level experience studies during this interaction session. The following behavior assumptions and their implication under accounting/regulatory requirements will be covered: - Separate account/fixed account allocation and transfers - Deposits - Surrenders - Withdrawals - Income utilization - Mortality By attending the session, you will: - Identify policyholder behaviors that would transform at different stages of life cycle. - Understand key aspects of industry-level policyholder behavior experience. - Form a dynamic view in the assumption setting.

Description: SARS-CoV2 will impact our post-pandemic future. Morbidity more than mortality will impact the life and health business in the mid-term. But how does this temporary disruption in health care elicit long-tail implications on other common diseases and changes in lifestyles? Find out how mid-term pricing could be affected using one case scenario and also show how mental health will particularly shape the post-pandemic future (individually and societal), not only due to long COVID. Review the experience of the insured policies and discuss future ideas for COVID-19 research at the Society of Actuaries Research Institute. Consider recent causes of death studies, as well as reported claims analyses to help expedite the analysis of recent experience. Join us where experts from both the medical and actuarial disciplines join forces to discuss this important topic.

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: 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: Last year, the COVID pandemic significantly increased the pace of change in the life insurance industry, particularly in Accelerated Underwriting (AU). In the past, underwriting process changes occurred relatively infrequently and over a matter of years. Now, with new data sources and predictive models constantly evolving, the frequency of underwriting enhancements and decisioning changes, particularly in AU programs, is occurring every few months. With so much change occurring quickly, how can a company effectively monitor and understand the effects of these changes to make continuous adjustments with confidence and agility? Well-designed data visualizations allow a reviewer to navigate and comprehend detailed results quickly because our brains can process data in a picture format more than 15 times faster than text. Today’s advanced BI tools can make AU program monitoring more efficient and help companies adjust quickly to the results from program changes.

Description: Term products exhibit a wide range of behavior as policyholders can elect different term periods and conversion options. While term products have been around for decades, it's only recently that longer level term products are reaching the end of the level term period. Term conversions have historically been an afterthought and are rarely modeled. Discuss the use of predictive modeling techniques such as LASSO regression and cross-validation to build models for level term lapses and post-level term shock lapses, as well as the extrapolation of experience for shorter term products to longer term products (e.g., extrapolating 20-year term experience and applying to 30-year term). Explore the use of traditional techniques to develop term conversion rates and a framework for modeling the assumption. Challenges and limitations of setting lapse and conversion rates will be discussed. By attending the session, you will: - Understand the complexities of term policyholder behavior. - Understand the challenges in developing and implementing assumptions for lapses and conversions. - Understand the application of traditional and predictive modeling techniques for term policyholder behavior.

Description: Health care has changed rapidly over the past couple of years. The pandemic has shifted consumer behavior in how and where they receive health care as well as consumer attitudes toward health care. Payers continue to design innovative solutions in responses to their patient’s needs and expectations. These changes in consumer behaviors and the responses by payers are expected to impact both health care cost and utilization. Discuss changes in health care that have emerged due to the pandemic and how they are expected to influence actuarial assumptions. Explore epidemiological models commonly used in the industry, the considerations when using these models, as well as the challenges with regards to gathering and interpreting relevant experience data. By attending this session, you will be able to: Identify shifts in consumer behavior that have emerged from the pandemic and describe how payers are responding to new patient expectations. Discuss how these post-pandemic changes by consumers and payers influence medical spending. Determine which actuarial assumptions are impacted and how and if the impact is expected to be temporary or permanent. Discuss considerations taken by actuaries and challenges faced when modelling actuarial assumptions post pandemic.

Description: The time has arrived for ASU 2018-12, otherwise known as Long-Duration Targeted Improvements (LDTI). For health insurance products, the ASU will require considerable efforts to make the necessary changes to valuation systems, procedures, assumptions, and/or methodologies in order to be in compliance. This session is designed to cover LDTI implications specific to carriers of long-term care and supplemental health products, including changes to how attained age rated products will be approached, allocating and discounting the claim liability (IBNR), and how the treatment of Profits Followed by Losses (PFBL) will evolve under LDTI. By attending this session, you will be able to: • Understand LDTI’s key impacts on long-duration health insurance products. • Recognize the treatment of attained age rated products under LDTI. • Comprehend the requirements of allocating the claim liability to cohorts. • Grasp the requirements pertaining to the discounting of the claim liability. • Understand how PFBL will evolve under the new standard.