Description: Dive into an integrative approach to Precision Medicine - how our modern capacity to interrogate a disease heterogeneity (from omics and phenotyping) and parallel advances in 'big data' together are driving to transform the practice of traditional medicine to precision medicine. After defining the relevant terminologies and the components of precision medicine, the speaker will walk through the spectrum in precision medicine and how it leads to personalized management of disease, which can impact underwriting approaches, product development and pricing. Diabetes will be used as a specific example.

Description: In this session a panel of industry experts from the life insurance industry will examine the modeling challenges created by increased investment in more esoteric assets.

Description: The purpose of this survey is to gather a high-level view of U.S. Group Term Life Insurance mortality results during the COVID-19 pandemic, as compared to prior period baseline mortality results. The datasets for this report encompass all Group Term Life claims reported to participating carriers as of August 31, 2020. The Committee is grateful that 20 of the top 21 U.S. Group Term Life insurers are participating in this survey, with market share representing roughly 90% of the industry.

Description: This document describes an effort to measure the deaths in the US population relative to pre-pandemic expectations. The actual deaths used are as reported by the US Center for Disease Control (CDC) and we consider several different methods for setting the expectations, adjusting for the estimated mix by age, sex, and time of the year (seasonality).

Description: This report explores the behavioral factors influencing insurance purchase among Gen Z and Millennials for forward-looking purposes, leveraging a rich dataset spanning 22 markets across six continents.

Description: Fixed Indexed Annuity Experience Study – Policy Years 2013-15

Description: Global trends in both technology and regulation are causing US insurers to reflect deeper on their model risk management frameworks. The world has seen a rapid proliferation of AI-based tools accompanied with an overall increased usage of machine learning models, exacerbating model risk and reducing transparency in an unprecedented manner. This rising tide of AI means that it is imperative for US-based insurers to address these emerging risks within their Model Risk Management (MRM) frameworks. Regulation also continues to evolve in this space: in Canada, the Office of the Superintendent of Financial Institutions (OSFI) revised Guideline E-23 to instill more detailed model risk management standards; in Bermuda, the Bermuda Monetary Authority (BMA) has published CP2 to add increased scrutiny on the data and models used by insurers. Insurers must react: MRM frameworks require prudent revisions to reflect these ever-changing landscapes of risk. Reassessing the core pillars of MRM frameworks - risk measurement, model development, validation, monitoring, and governance – is key to understanding the consequences of these evolving market changes on insurers’ risk profile. Overall, the inclusion of these new tools into the world of insurance necessitates a thorough examination of insurers’ MRM frameworks in order to align these new risks with core MRM principles. In this session we will: - Reflect on recent drivers of change and how they should be considered in the context of MRM - Explore best practices as it relates to MRM frameworks in the context of current global trends - Describe challenges, success stories, and lessons learned relating to recalibrating and embedding MRM frameworks

Description: In this session, we will explore the innovative use of artificial intelligence in developing narrative scenarios to enhance life insurance investment strategy discussions. Participants will discover how developing comprehensive and imaginative scenarios can help identify potential future risks and opportunities, leading to more informed investment strategy planning. The session will cover practical approaches to creating and utilizing narrative scenarios, emphasizing their role in improving decision-making processes. Join us to learn how to craft compelling scenarios that provide a broader understanding of drivers of emerging trends and uncertainties, ultimately transforming traditional investment strategies in the life insurance sector. Learning Outcomes: - Understanding the role of AI in Scenario Development - Enhancing Investment Strategy Decision-Making - Writing comprehensive scenarios and using them for specific investment strategy decisions

Description: Life insurance products have evolved over time from the early mutual aid societies paying benefits when members died to comprehensive products covering a range of financial needs over an individual’s lifecycle. While some life insurance benefit riders have been offered for decades and are well-established, recent years have seen a number of accelerated benefit riders being introduced by carriers for a growing range of covered triggers. Join us as we discuss these acceleration and extended benefit riders, trends and innovations in the space, and discuss challenges and actuarial considerations in designing, pricing, and modelling them. We will also explore issues carriers have experienced, how to consider the interactions between these benefits and the underlying mortality coverage, reinsurance considerations, and more!

Description: Value of new business (VNB) is being used by many companies for various purposes including: internal and external financial reporting, incentive compensation, pricing, capital management, and comparing products, distribution channels or regions on a consistent basis. Presenters will discuss how and why value of new business is used within their companies including: the various methodologies considered, some of the benefits and challenges related to implementing VNB, integrating VNB within their business as usual processes, and managing to VNB.