Description: Bias Awareness in Model Governance

Description: This Q&A article discusses the use of machine learning to analyze unstructured data. Supriya Ramachandra, a data scientist at SIKKA, explains how her team uses natural language processing techniques, technical aspects of neural networks, LSTM modeling, and natural language processing. Machine learning allows for the classification of large amounts of unorganized data, providing actionable information for actuaries.

Description: This note presents a review of calculator financial functions for the Texas Instruments BA-35 calculator. A number of the examples used as illustrations are from the 3rd edition of the book Mathematics of Investment and Credit, by S. Broverman.

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: Machine learning models have many practical applications in the world of insurance. These applications are well documented and most actuaries, at least at a high level, are familiar with these concepts. The presenters will take this one step further and provide an introduction to the theoretical formulas and real-world considerations that make machine learning models possible.

Description: To remain relevant, insurers need to understand and adapt to changing consumer behaviors. There is no doubt about it, millennials have different expectations around searching, buying and servicing, and insurance is no exception! Come hear from four different insurance startups who are designing solutions for this future generation of insurance buyers, followed by a panel discussion with the opportunity to ask questions. You'll learn and perhaps even be inspired to propose solutions in your own company. You may even start calling yourself a Millenial Maven too!

Description: An overview of how the actuary's role will evolve as technology improves.

Description: The future holds many changes. We've already dealt with major changes over the last few decades. This article goes through tips to embrace change effectively.

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