Description: Internal modernization initiatives and external changes of the financial reporting regulations (e.g., LDTI, IFRS 17) increase the amount of validation activities for actuarial models. In addition, the use of predictive analytics in actuarial modeling requires a different set of validation skillsets/techniques in model validation. These internal and external forces call for a structured, streamlined and robust model validation practice.

Description: Reunite with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, IFRS 17, product strategy, cross-border communication and discussion, and more. Advance your career through learning and networking opportunities, and share your experiences in the finance and insurance industries, as well as other fields related to actuarial science.

Description: Analyzing large quantities of raw complex data is often a challenge in the health care industry. During this webcast, there will be a demonstration of how unsupervised machine learning techniques can be applied to such data to help bring useful insights. This will include examples that use unsupervised learning techniques spanning dimensionality reduction, clustering and anomaly detection.

Description: "Risk adjustment (RA) is a key component for CMS Medicare Advantage program and California Medicaid Managed Care program. While both RA programs follow generally accepted basic principles at a high level, their underlying methodologies and assumptions are also quite different. Due to recent events such as COVID-19 Public Health Emergency and Medicaid redetermination delay and restart, it adds complexity to Risk Adjustment. This is a hot topic in the industry and has significant impact to health plans. Keeping current with risk adjustment program changes and understanding the commonalities and differences of these two government risk adjustment programs is important to our health actuaries. Compare these two risk adjustment programs so you can learn key elements of a risk adjustment program, similarities and differences in methodology and assumptions , as well as special considerations due to serving different populations."

Description: "Explore a general introduction to the opportunity of applying a relatively newer area in machine learning called uplift modeling, which has been successfully used in retail (Wayfair etc). The concepts are parallel to the intervention programs in health care, where we are interested in measuring the treatment effects and ultimately directing the right members to the most effective programs, driving the highest value for the programs both from a financial and health outcomes perspective. Uplift modeling can also be viewed in context of causal modeling where we are interested in assigning cause to a treatment relative to a member not receiving the treatment. Check out an introduction on the concept, seehow it relates and builds on existing work, and use a demo to showcase the potential of integrating this ML approach to current work."

Description: Lincoln Financial Group announced the beginning of a two-year data and analytics talent upskilling program with the Society of Actuaries, a global professional organization for actuaries. The SOA will facilitate training for Lincoln employees through a customized multi-phase educational program focusing on big data and predictive analytics.

Description: Technology has streamlined countless processes in our daily lives, and insurance is no stranger to this transformation. Technology can make insurance simpler and more personal for consumers, and can enable actuaries to better analyze unstructured data, make good decisions, create new products, and find channels to enhance profitability, provided they can tame the flood of information pouring in from across the digital ecosystem.