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: 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: This session is an in-depth interview of two actuaries turned Artificial Intelligence (AI) experts. We aim to have a conversation that gleans into each of their journeys and what led them to the path they are now on. We will open up the last ten minutes for audience questions. At the conclusion of this session, attendees will know Eric and Joe much better, have an understanding of what AI/machine learning/data scientist work is like for actuaries, and, for those who are curious to get more involved with AI, some encouragement to pursue their interests.

Description: This session will cover everything you've wanted to know about GLMs but were too afraid to ask. How do these generalized models relate to the plain linear regression, and how can we be sure that the models we implement are appropriate for the task at hand?

Description: Session 7B: Health AI in Practice - Lessons From Top U.S. Health Systems

Description: Session 10F: Debating AI - Valuable Tool or Overhyped Trend?

Description: Session 2F: Artificial Intelligence and Actuarial Modeling - Ask an Expert!

Description: As data continues to become more robust and readily available, there has been a push in the actuarial field to transition away from Excel to SQL and Python native cloud-based platforms. While these platforms are widely used and powerful, they present their own challenges for the actuarial industry, requiring processes to be production-ready from the onset, technical expertise for integration, and robust requirements documentation. Low-code tools provide a unique alternative solution, which works well when the organizations operating model allows for actuarial and IT to work together, giving actuaries the flexibility they need while maintaining a level of control followed by the organization. Make use of demonstrations to showcase low-code tools (such as Alteryx and Dataiku) and their use case in the actuarial space. Learn how these low barrier-to-entry tools can be leveraged to create robust and controlled processes. Discuss how low-code tools can integrate with coding languages such as Python as well as efficiently prepare data for downstream visualization platforms such as Tableau and PowerBI.

Description: Reference Based Pricing (RBP) efforts have increased in popularity as tools to reduce the cost of care. Now with the ability to use CMS health plan transparency information, organizations can estimate the impact of savings from the use of RBP. This session will share the results of an analysis of this in the form of a case study.