Description: CMS provides ACOs with monthly claims data for members, including their medical visits and ACO program eligibility. This data can be divided into Membership and Claims tables through the ETL process. However, when calculating PMPY at specific levels of detail using these tables, issues arise due to unrelated dimensions, leading to inaccurate and understated results. This article presents a solution to this problem by utilizing Tableau's data blending capabilities.

Description: This newsletter provides a regulation outlook for the use of AI/ML in insurance industry, interpretations of regulatory expectations and what insurers should consider when managing risks associated with the development, implementation and use of AI/ML models/tools.

Description: This article summarizes the new research paper of "InsurTech: A Guide for the Actuarial Community" by Carrie Kelley and Kiki Wang. It serves as a quick read for our members to learn the latest development in the InsurTech space and explore the opportunities for actuarial practitioners

Description: Actuarial Process Optimization is a framework for using technology to support the actuary of the future. In this article, we discuss the capabilities of new technologies and explore examples where they can be used to aid with providing strategic business direction, optimizing skillsets and use of technology, and maintaining governance, control, and risk frameworks.

Description: In this article, we talk to Lei Rao-Knight, FSA, Vice President and Actuary at Prudential Financial. Lei discusses her model development experience in the Modeling Center of Excellence.

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 winner of the “most unique use of technology” prize of the 14th Speculative (and Inspiring) Fiction Contest.

Description: An overview of the basic tooling and packages available for the Julia programming language, with a focus on why this is of interest to the actuarial profession. It covers some of the built-in language features as well parts of the Julia package ecosystem that make Julia ideal for modeling and data analysis. This is the second installment in a series of article aimed at actuaries. The first installment, Julia for Actuaries, was published in the October 2020 edition of Actuarial Technology Today, and covered the base language itself, its high-level, math-friendly syntax, and why the actuary of the future should consider its adoption.

Description: A discussion of techniques that can help manage model risk and complexity.