Description: Machine learning algorithms fit models based on patterns identified in data and can be very complex. In this report, we describe and illustrate a range of methods for interpreting machine learning models from the growing field of Interpretable Machine Learning (IML).

Description: Big data and predictive models have disrupted the life insurance new business and underwriting processes over the past few years. How did we get here? What does the future hold? This session will review the lessons learned from the evolutionary process and discuss what the potential next steps are in this journey. Are real time fully underwritten decisions an achievable goal?

Description: Telehealth enables the delivery of health care services to patients that are not in the same location as providers. Over the past decade, telehealth has been used increasingly to complement face-to-face patient encounters, and is particularly important to addressing health care needs in rural areas. Recent regulatory catalysts, particularly in the Medicare Advantage program, have served to elevate the visibility and importance of telehealth in the overall health care delivery system. Starting in 2020, Medicare Advantage plans can offer any clinically appropriate physician services through telehealth as part of the standard Medicare benefit. Network adequacy standards can also be met via telehealth providers under certain programs. This presentation will cover the basics of what constitutes telehealth, and provide tangible demonstrations of telehealth technology (simulating variations mediums through which services are delivered). We will cover the what, the why, and the where (anywhere) of telehealth in 2020.

Description: This article addresses the risks associated with poor data quality and the importance of establishing effective data governance.

Description: This article discusses the emergence of multi-processor computers and the importance of acquiring parallel computing skills.

Description: The predictive analytics application growth in the Asia-Pacific region has been gaining momentum.

Description: File for 2020 DATA VISUALIZATION CONTEST.

Description: This session will discuss basic and advanced hedge modeling concepts. It will explain common hedge strategies used to support guarantees and options embedded within life and annuity products and the materiality of these products within the US. Attendees will learn how Machine Learning acts to reduce the computer processing needed to simulate the dynamic hedging of product liabilities projected in the future across many stochastic scenarios. Actuaries working in consulting, software development, and a large life insurance company will provide a wide range of hedging viewpoints ranging from a broad industry perspective to a hedging practitioner. Attendees will obtain a comprehensive understanding of a novel ML approach to modeling dynamic hedges and the hedge optimization opportunity it presents.

Description: This newsletter provides a regulation outlook for the use of AI/ML in insurance industry, interpretations of regulatory expectations and what insurers should consider when managing risks associated with the development, implementation and use of AI/ML models/tools.

Description: Chairperson's newsletter outlining section strategy for 2023.