Description: Introduces the concept of total risk analysis, a methodology used to answer questions like "what are the chances we will lose more than $1 million"

Description: New web page that describes the new e-learning FSA module Scenario Modeling. It replaces Financial Reporting Module in the QFI track.

Description: Analyze the market volatility behavior in context with historical extreme events during this webcast. There will be a focus on understanding volatility clustering and relationships, both contemporary and temporal, in addition to key economic and capital market variables. You'll also learn from a comprehensive attribution analysis, which uses economic data, asset data, retail investor data and event data as explanatory variables. Dive into investment-related Reddit comments used to capture features of retail investors and tree-based models, including Random Forests and Gradient Boosting Machines to justify changes in volatility modeling. Expect this webcast to end with an example of liability-driven investment optimization that illustrates the potential impact of increased volatility assumption, how to adopt stochastic volatility models, how to reflect volatility clustering and return jumps.

Description: Model design is an important part of being an actuary, and the SOA highlights the importance of the actuarial control cycle of model design, evaluation and monitoring. What tools are at our disposal for these steps? When should we be concerned or excited about model performance? Can we, and should we, use machine learning tools to assist with model improvement or development?

Description: The Student Research Case Study Challenge provides an opportunity for teams of students to apply their actuarial skills on a real-world problem in a business setting.

Description: Come dive into the Introduction to Modeling Summer Boot Camp series, which will provide an overview of modeling topics and techniques aimed at the beginner modeler. This interactive Zoom series will be comprised of five 90-minute sessions (August 24, 25, 30, 31 and September 1), with opportunities to discuss the topics in small break-out groups.

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: The surge in interest rates over the past few years presents opportunities for life insurers to enhance their Asset and Liability Management (ALM) positions through asset rebalancing to narrow the duration gap and secure higher risk-adjusted yields. This webcast introduces a robust, efficient and readily-executable, liability-driven strategic asset allocation (SAA) framework and implementation considerations. At the conclusion of the webcast, attendees will learn about the key objectives and practical considerations for a successful SAA.

Description: There is increasing industry interest in applying behavioral science to optimize product design decisions and improve outcomes for both insurers and their customers. With a growing set of options within product designs, predicting consumer behavior continues to get increasingly complex. Join this webcast for an overview of key behavioral economic concepts. Key insights will be shared from two SOA projects that explore how behavioral economic techniques can be used in various parts of the life insurance new business process and enforce management.

Description: The post COVID-19 period exhibited a fast-changing capital market with higher interest rates, uncertain monetary policies, and revaluation of asset classes. At the same time, regulators introduced changes to reward better risk management, such as the scenario-based approach for reserving under Bermuda regulatory framework. For life reinsurers, while new opportunities arising from these changes, challenges also exist to be able to adjust reinsurance portfolios and ALM strategies appropriately. A holistic modeling framework can assist companies better position themselves in front of these challenges and other potential future unknowns. In particular, a well-designed stochastic and dynamic modeling framework enables the quantifications of such probabilities and potential impacts.