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: In this article, we discuss the future of wearable technology in life insurance. Evidence from recent research shows that low levels of physical activity, as measured by steps per day indicate much higher mortality risk while higher levels of activity correspond with lower risk. The article shares insights of how insurers can use wearables to innovate by improving the customer journey, expanding insurability, engaging customers, promoting healthy lifestyles and improving risk assessment. Lastly, we discuss the challenges and considerations when using new data and technology to ensure success.

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 chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.