Description: Explore insights to non-traditional actuarial roles from a panelist with experiences in data science, finance and entertainment. The panelist will be sharing their perspectives on their non-traditional actuarial role in relation to the actuarial profession.

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: Practical Analytics 4.0 Virtual Event recordings

Description: Explore insights to non-traditional actuarial roles from a panelist with experiences in data science, finance and entertainment. The panelist will be sharing their perspectives on their non-traditional actuarial role in relation to the actuarial profession.

Description: Data needed to run the Hack-a-Thon that was held at the 2019 PAS.

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: 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: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

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: This practical session would provide a technical overview about Generalized Linear Model (GLM) and describe how GLM can be applied as a business tool in life insurance. The session would also focus on case-studies sharing across different functional areas such as pricing, fraud detection, underwriting, product development and other real-world applications.