Description: Many executives are talking about predictive analytics uses in health insurance.

Description: This article goes through some basic data exploration techniques to show how different approaches look.

Description: Update on Health Section research projects and topics, including new vision and mission statements for the Health Section Council, research and communications projects, and information about the Health Actuarial Research Initiative.

Description: Chairperson's column for the July 2016 issue of Predictive Analytics & Futurism.

Description: This paper examines a differential equation model, whose solutions have yield curve shapes. The paper also examines the relevance of the model with historical monthly U. S. Treasury nominal rates. From the Actuarial Research Clearing House 1992 Vol. 1 .

Description: A look at the near future and far future of various elements of Actuarial Models as defined through ASOP 51. What is driving the complexity for inputs, calculations, and outputs. Howe will actuaries handle these challenge?

Description: Python has become the fastest-growing major programming language in the world. It has surged in popularity over the last decade, following the development of its industry-leading capabilities in data science, machine learning and artificial intelligence, and it is now one of the most globally popular and widely used languages. In this article, I discuss some of the reasons for its popularity and explain why many actuaries and insurers have started using Python.

Description: The author recounts his experience as a keynote speaker at the Actuarial Research Conference and provides advice to young actuaries to present complex subjects in an understandable manner.

Description: Overview on current trends in medical practice impacting the LTC insurance business with a focus on dementia, risk stratification, and predictive modeling.