Description: Python is the leading programming language for data science. Python programming is one skill that actuaries should acquire. It facilitates analytic work, and the available visualization tools help to communicate ideas. In this article, I use a traditional actuarial problem, mortality modeling, as an example.

Description: Discusses results of author's recent survey of professionals in the viatical and life settlement, a.k.a. secondary insurance industry, to discover how actuaries could best serve this particular business.

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: An overview of bias and fairness in machine learning models, as they apply to use cases in life insurance.

Description: This article focuses on the recent surge of digital medicine data being seen in the healthcare industry. While an increase in data can generally be perceived as good, it is important to remember that current privacy practices need to be maintained, if not strengthened, to continually protect healthcare members. The COVID-19 pandemic helped fuel digital medicine data, but it also created new avenues for privacy to potentially be compromised (i.e. healthcare employees using personal devices while working from home). Digital medicine data is a very powerful asset, but it is also a massive responsibility. If mishandled, this data can cause more harm than good.

Description: Actuaries pride themselves on innovation and advancements; but no professional field has pushed to set the bar higher than medical Radiology. Over the course of the last few decades, medicine has begun to rely more on artificial intelligence to aid in the process of patient care; and the results have been outstanding! This article looks to show how high the bar has been set, how it will impact the current state of the world of the actuary and the future impacts

Description: A list of the lessons the author learned through his own failure(s). The intent is to help readers avoid making the same mistakes and reflect on how far they've come.

Description: This article proposes that using common techniques employed by actuaries to manage risk like economic capital could be effective in mitigating financial losses that face the airline industry during COVID-19.

Description: This article explores the challenges of writing exams during the COVID-19 pandemic and lessons learned.

Description: Feature article discussing image recognition and how it may affect actuaries in the future.