Description: Introducing Random Effects into Risk Score Models

Description: Come discuss the benefits and challenges of collaboration between academic institutions and industry stakeholders in shaping actuarial education and research agendas. Register for this event now.

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.

Description: Understanding Asian Capital Regimes

Description: In this presentation, actuaries and data scientists from Cleveland Clinic and Milliman discuss the development of a sepsis prediction model using machine learning. Presented with a unique challenge of handling massive amounts of data for near real-time risk scoring, the team took their model development to the cloud and delivered a product in less than a week through a unique virtual engagement.

Description: Learn more about the predictive modeling that was applied to industry data for the lapse and mortality experience in the post-level term period. Novel approaches were taken to model the shock lapse, subsequent lapse, and mortality experience. Observe a demonstration of the Tableau tool, which was built to allow users to analyze data on their own.

Description: This session will delve into the valuable lessons learned from recent accounting change implementation, covering both model and process optimization. Attendees will gain industry knowledge as we explore optimization decisions made by others, highlighting both successful strategies and areas for improvement. We will discuss key decision points throughout the entire actuarial process, including data manipulation, actuarial calculation engine, and post-model reporting.

Description: The Product Development Section, the Financial Reporting Section, the Modeling Section and the Committee on Life Insurance Research are pleased to present new research on modeling and forecasting cause-of-death mortality. Authored by a Milliman team led by Alexandre Boumezoued, the report develops a framework for forecasting cause specific death rates. Included also is a Cause of Deaths Forecasting Tool and a user guide for the tool.

Description: Cluster modeling is emerging as a powerful technique to manage cloud costs and run time. It also enables quick responses to "what if" scenarios, and aids in attributing results between reporting cycles. In this webcast, we provide insight into cluster modeling, present case studies that focus on various key performance indicators and discuss the benefits and challenges to cluster modeling from an insurer’s perspective. We also discuss the considerations associated with moving from an on-prem based computing solution to a cloud-based approach.