Description: This chapter introduces a few probability distributions that play an important role in understanding and analyzing healthcare data. While theoretical in nature, these distributions model real life if appropriately chosen. Probability distributions are mathematical representations of how statistical data behave.

Description: This session will explore several critical elements in developing a sustainable and coherent framework to translate complex annuity (VA and FIA) policyholder behavior experience data to assumption models using company- and industry-level data, as well as inforce management techniques to handle related risks.

Description: There will be no easy resolution to the current trade friction between the U.S. and China. If anything, the motivations for increasing protectionism are set to intensify. What are these motivations? Where is this trade war headed? And what impact could this have on economies and financial markets?

Description: Life Insurers today are collecting huge volumes of text data though heterogeneous sources which if harnessed in a streamlined process can lead to enhanced decision making for pricing, product development, experience studies etc. This session would introduce the technical framework which can be used to derive insights from unstructured data like raw text.

Description: The author makes 10 predictions of how risk management will change over the next decade.

Description: This report explores AI bias in insurance and health data, highlighting the ethical role of actuaries and offering cross-disciplinary guidance for fairer decision-making systems.

Description: ACA risk adjustment has now been in play for years. The original intent of risk adjustment was to help stabilize the market through measuring risk levels of each issuer. However, the risk adjustment program may have introduced additional uncertainty due to annual market shifts and model changes, making risk adjustment estimation is a difficult task. This article analyzes the results over time, including impacts from market changes and model changes.

Description: In the evolving realm of healthcare actuarial practice, value-based contracts are reshaping the landscape. This article explores the pivotal role of AI-enhanced Electronic Medical Records (EMRs) in empowering actuaries to navigate this dynamic sector. Despite challenges in data standardization, AI-enhanced EMRs offer a solution by extracting and standardizing diverse medical records. The article delineates how AI-EMR integration benefits actuaries and provider organizations, enabling more accurate forecasting, earlier shared savings prepayments, and real-time quality metric aggregation. Moreover, it discusses how this fusion addresses historical data limitations, can help project catastrophic claims, and can help identify risk score capture opportunities. Ultimately, it indicates the transformative potential of AI-EMR synergy, positioning actuaries at the forefront of healthcare analytics with unprecedented precision and insight.

Description: Spark offers a way to get some dramatic speed and scalability advantages over the Map-reduce methodology whenever you are doing iterative data processing and particularly when you want interactive data analysis capability. Find out why “lazy execution” can be a desirable characteristic when dealing with big data.

Description: Book review of the latest edition (4th) of Life, Health, and Annuity Reinsurance by John Tiller, Jr and Denise Fagerberg Tiller