Description: This session will cover the current and potential use of artificial intelligence (AI) in the health care space. Participate in this interactive session and learn how AI is being used today and discuss its potential to reshape and revolutionize health care. You will get an opportunity to learn how AI can influence patient experience in every phase of healthcare delivery and talk about the challenges and limitations that arise with the use of this technology.

Description: Volatile interest rates, repositioned investment portfolios, and stress in the banking sector are driving insurers to manage market risk and counterparty credit risk. Our experts in investments, derivatives, and hedge accounting will discuss this new market environment and its impact on hedging. The conversation will include practical case studies, including hedging future bond purchases, hedging floating-rate CLOs, and counterparty credit risk management.

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: Walk through real-life examples of how artificial intelligence can be used to drive insights and aide actuaries in improving the management of their company’s inforce book of business. A panel of experts will walk through case studies of how, as practitioners, predictive analytics provided solutions to tap further into their data and draw improved insights.

Description: This session will present the results of a case study investigating the impact of genetic testing on the reduction of health care costs. This will present both actuarial and clinical analysis of genetic testing in addition to researchers who are applying this approach.

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

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: 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.