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

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: 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: The article talks through my personal journey of passing actuarial exams during the pandemic. The purpose of the article is to provide readers a different perspective on how to successfully navigate and balance work-study commitments. The article provides 6 tips that helped me overcome exam challenges.

Description: The article contains a description of the Emerging Topics Community. The focus of the article is what is a community, what makes the Emerging Topics Community special, and benefits of the Community. Included after the discussion on the community are ways to get involved and be a part of the community.

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

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

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: Overview about the information covered in the Predictive Analytics Certificate and how that is useful for actuaries.