Description: The SOA, with SCOR as the researcher, completed an experience study of post-level term (PLT) lapse and mortality. In the first part of this session, the presenters will cover the key findings of the traditional analysis regarding the shock lapse, the PLT lapse and mortality experience. The remainder of the session will focus on the results of the predictive modeling, which will provide further insights into policyholder behavior in the post-level term period.

Description: Are Accelerated Underwriting (AU) programs performing as expected? As mortality experience will (hopefully) be slow to emerge, it is pivotal that we look at alternative methods of monitoring early performance. From random hold outs, to post-issue APS's, and post-issue prescription profiles, explore popular monitoring techniques and lessons learned so far. Focus on confusion matrices that provide an early indication of mortality slippage relative to fluid-based underwriting decisions. Finally, explore statistical methods to determine what constitutes credibility and identify opportunities to think about mortality slippage more robustly.

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

Description: Focus on Accelerated Underwriting (AUW) in the life insurance industry, which is an expedited underwriting process that utilizes predictive models. Expect to address the challenges in designing the process, from modelling to performance monitoring. Additionally, you'll address risk management, particularly in mortality and proxy discrimination andhighlight the role an actuary can play in the AUW process, as well aswhat they should know to contribute effectively.

Description: The Individual Life Experience Committee has numerous research projects underway. Take a look at three current areas of research: the analysis of the interaction of lapse and mortality experience using data from mandatory submissions; a deep dive into old age mortality; and an update on the committee's work to establish a predictive analytics framework that will be open for all actuaries and data scientists to use. By attending the session, you will: - Better understand the research conducted by the Individual Life Experience Committee. - Better understand the link between lapse and mortality experience, appreciate some of the nuances of older age mortality, and gain knowledge about a predictive analytics framework that will be released in the future.

Description: Hear about modernized reporting capabilities and technical analysis, which is enabled through access to deep actuarial and financial planning data. The webcast will focus on a real post-Long Duration Targeted Improvements (LDTI) source of earnings analysis and on a high-level LDTI forecasting capability.

Description: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.

Description: Learn how modernization of data, models, and technology are influencing workflows. This webcast will address how workflows are changing in response to new regulatory requirements and the impacts the changes have on modeling and end-to-end future state operating models. Industry leading actuaries will discuss: How team collaboration can increase quality and speed of reporting to internal and external stakeholders How to strengthen controls and compliance frameworks across finance and actuarial departments How to modernize actuarial input/output for strategic analysis and insights How to attract and retain top talent by improving opportunities for actuaries There will also be dedicated time to ask questions of those who have made the transition.

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: The session will highlight trends in recent industry mortality and lapse studies that have been conducted, including areas where individual companies typically have limited data. The sources of data feature SOA studies as well as other industry studies conducted by consultants and/or reinsurers. Gain an understanding of current drivers of mortality and lapse experience for life insurance evidenced in industry studies, and an understanding of available data to supplement experience in areas where you may have limited internal experience.