Description: Virtual - Session 1A: From Actuary to Data Scientist - Career Journeys into AI

Description: Human longevity is one of the great success stories of the past century, and there is growing consensus that there are further gains to come. What will these future gains look like, where will they come from and how likely are they to happen. Furthermore, how do we as actuaries deal with the uncertainty when trying to predict future long-term mortality improvements more than 20 years into the future. This is one of the most important assumptions on the balance sheet that insurers and reinsurers make, so it is important to have a strong perspective on it. Our presentation will give attendees a view into some of the core components of how to assess long-term mortality improvements by looking at the cyclical nature across different countries of life expectancy. It will also deep dive into the different drivers of life expectancy over the past cycle driven largely by improved diagnosis and treatment of cardiovascular disease (CVD) and cessation of smoking, which ended in about 2010. It will then discuss how population mortality improvement has slowed and plateaued in many major countries.

Description: Expect to learn how recent advances in AI and Generative text technology can help unlock data from medical records to solve many key underwriting and actuarial challenges. Specific topics include the following: - What is NLP/AI/machine learning and how is it currently being used in underwriting? - What technological advancements have Insure Techs made in the use of AI and GPT, and how are carriers/reinsurers utilizing these enhancements? - How can you avoid some of the challenges with GPT such as Hallucinations and 'black box' outputs? - How can extraction of data from medical records assist actuaries with various pricing and analysis challenges? - What legal/compliance challenges should users be aware of and how to manage those risks?

Description: You’ve written the position papers, updated the models, and designed the required disclosures, but you may be wondering how to explain the results during interim financial reporting periods to company management as well as other stakeholders. This session will explore ways to adapt existing management reporting and offer ideas for new metrics. We will explore various methods for analyzing DAC amortization patterns, market risk benefit reserve patterns, and Liability for Future Benefits (LFPB) movements. In addition, this session will explore ways to integrate changes in LDTI with business planning and other broader business issues such as product pricing considerations and reinsurance strategy.

Description: This session will discuss essential theories and practical applications of deep learning for actuaries. Participants will gain insights on leveraging these cutting-edge techniques to enhance actuarial models and drive predictive accuracy.

Description: View 2017 Kaggle Involvement Program Results.

Description: Early in his career, Ehren Nagel, FSA, MAAA, scoured through podcasts and articles about predictive analytics, long suspecting this was a field with potential for him.

Description: The Predictive Analytics Seminar is a unique event that allows experts in the practice areas of life, health, and P&C to come together and explore the vast world of predictive analytics.

Description: "A crucial importance in forecasting is to be able to distinguish cases when temporary slowdowns in health care utilization are followed by a “rebound” period of higher utilization. Come explore an analysis of a new mathematical model describing the return-of-care process. By means of simulation and case studies using the R programming language, the relationship between the visibility of these effects and the endogenous variance of the utilization time series is explored. After attending this session, you will be able to: Describe the parameters and mathematical form of the model Apply the model to real-world utilization data"

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."