Description: Actuaries today have unique opportunities to analyze, understand and use data for strategic decision making. With nearly unlimited computing power and a broad spectrum of data sources at our fingertips, we are enabled to support our actuarial judgment with comprehensive findings backed up by deep data analyses.

Description: Learn about the latest developments in hospital and payer price transparency data. Hear experiences working with the data and attempts to gain meaningful insights for actuarial and other purposes. Discover challenges and workarounds associated with this data, including file size, comparability of prices, duplication of prices, aggregating provider NPIs into meaningful groupings, and missing payer information.

Description: Keynote Speaker: J.D. Kleinke, Author and Medical Economist J.D. Kleinke has been instrumental in the creation of four health care information organizations; has served on the Boards of several health care companies; and spent many years advising both sides of the political aisle on non-partisan, practical approaches to health policy and legislation.

Description: Study, discuss and explore the professionalism practice, code of conduct and application of the actuarial profession. Hear from seasoned presenters from mainland China as they cover several issues encountered in daily actuarial working environments through business cases and interactive discussions.

Description: In this SOA e-course, you'll learn how to develop an enterprise risk management (ERM) framework and help fulfill your SOA CPD requirement at the same time.

Description: Improve your financial reporting knowledge with this SOA e-course. It will help you understand financial statements and regulatory capital requirements.

Description: Dive into this review on Artificial Intelligence and Machine Learning (AIML) techniques for actuarial modeling for life & annuities. Presenters will showcase learnings from the recent SOA research paper "Predictive Analytics and Machine Learning – Practical Applications for Actuarial Modeling" (Nested Stochastic). The researchers will go over models and methodologies used to develop high-fidelity proxy models for various life & annuity applications.

Description: The use of data to assess risk is not new to the life insurance industry, but has historically been limited to leveraging structured data. Join us as we discuss the next frontier: unstructured data.

Description: It's your first full day of productive learning! Start it off right with a delicious breakfast and warm welcome.