Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.

Description: The rapid evolution of life insurance underwriting has created pricing and operational challenges and raised new questions about established approaches to assumption development, both of which demand a fresh perspective. As underwriting methods evolve, we find ourselves navigating uncharted territory. In this session, we delve into accelerated underwriting, focusing on two critical areas. First, we explore assumption setting in this new world, where numerous interaction effects can make it feel like we’re asked to consider everything, from every angle, all at once. Considerations for assumption setting must encompass early performance indicators—what signals inform our assumptions? Additionally, we address novel underwriting approaches and how to adapt assumptions for these paradigms. Furthermore, in the context of post-COVID claims experience, we discuss distinguishing meaningful insights from noise. Second, we examine declinable risks and their impact on mortality. In this new world ushered in by accelerated underwriting, previously excluded risks—low-frequency, high-severity declinable cases—are now part of the landscape. Quantifying their mortality impact challenges us, as historical data lacks systematic tracking. To quantify declinable risks, we draw upon research findings from analyzing 27 million life insurance applicants, providing valuable insights for attendees to navigate this dynamic landscape and make informed assumptions for pricing and risk management.

Description: We're introducing a new “cutting edge” wealth accumulation predictive framework, the predictive equity analytics (PEA) for life products (annuity, insurance, group employer benefits, retirement plan). PEA enables life insurers and policyholders to avoid market downturns and capture returns from equities (stocks, ETFs and mutual funds) predicted to increase in next one to three trade days via fund prediction advisory by insurers, additionally by individual policyholders. The capability does not exist in insurance markets nor in financial intermediary markets.

Description: The recent global pandemic, coupled with a rising interest rate environment, has emphasized the need for life insurers to be well-prepared for challenges on multiple fronts. Join industry experts in actuarial science and asset-liability management (ALM) as they discuss the significance of incorporating comprehensive pandemic modeling, mortality modeling, lapse modeling, liquidity analysis, and ALM strategies into the risk management framework of life insurance companies. Through case studies and interactive discussions, learn how to utilize systems and APIs from disparate risk models to integrate into an overall analysis to assess the short and long term impacts of the confluence of risk factors on your business, identify vulnerabilities, and implement proactive risk management strategies to enhance resilience and maintain long-term profitability.

Description: Gather with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, pension, investment, product strategy, and more.

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: Actuaries today have unique opportunities to analyze, understand and use data for strategic decision making. With nearly unlimited computing power and a broad spectrum of data sources at our fingertips, we are enabled to support our actuarial judgment with comprehensive findings backed up by deep data analyses.

Description: How can generative artificial intelligence (AI) be leveraged to transform and modernize life insurance? Gain an overview of AI and some of their current use cases in the industry, including the latest trends in the market. Next, you will learn about the current challenges companies face, including costly underwriting procedures, customer acquisition and retention, and complicated application processes. Finally, explore how generative AI can help address these challenges, improve customer experience and help streamline processes to free up more time for higher-level business insights and other company initiatives.

Description: Electronic Health Records are here to stay. Take a deep dive into the world of electronic health records and how the industry is poised to utilize this new form of digital medical data to transform the way policies are underwritten and ultimately, transforming the client experience. Listen to industry experts speak about what they are doing to use this data most effectively and how this ultimately develops into ground-breaking solutions for the industry.

Description: In this wide-ranging session, expect updates on the work of the Individual Life Experience Committee and delve into some interesting recent research. You'll gain an update on recent findings from the Individual Life Experience Committee regarding individual life mortality experience.