Description: An application of GLM trees to mortality modeling using the Individual Life Experience Committee 2009-2015 dataset. GLM trees are a hybrid of GLMs and decision trees which are analogous to the way actuaries have analyzed data. The major benefits include speeding up actuarial analytic workflows, improving data understanding, and improving data visualization.

Description: Methods and assumptions used in the valuation of savings by external care vendors

Description: This article will highlight the issue that the sum of key-rate metrics does not add to metrics derived by parallel shift to the entire curve, even at very low shift size. Additionally, in the article I will outline how to define a single rate change to be applied to a key rate (or the entire curve) since the rate changes are generally not level or parallel.

Description: An introductory article describing how Bayesian statistics has evolved over the past 20 years and why it offers the actuarial discipline powerful tools to better understand and manage risk. Compared with traditional (frequentist) and black-box (machine learning) approaches, Bayesian analysis provides explainable models focused on distributions of estimates instad of simply point estimates.

Description: With coinsurance of an existing block of long-duration insurance contracts, there may be existing reinsurance that remains in force. The new coinsurance is typically net of such “inuring reinsurance.” In this article, we look at approaches that the new reinsurer might apply to account for the effects of inuring reinsurance.

Description: The momentum in value-based care has produced an opportunity for actuaries to become pioneers in health care

Description: Regression to the mean is a phenomenon that arises when comparing sequential data points. It states that when an initial observation is extreme or an outlier, future observations will be closer to the average. Health care actuaries need to understand and be able to mitigate the effects of regression to the mean to avoid misapplying predictive models or misstating measurements of historical effects.

Description: James Dunseth's MBA journey at Yale’s School of Management and his startup internship taught him invaluable entrepreneurial lessons. Key takeaways include the importance of customer feedback, flexibility, technical skills, effective metrics, and achieving product-market fit. These insights emphasize customer-centric approaches, agile methodologies, technical understanding, and strategic metric use to guide business decisions and foster innovation.

Description: Artificial intelligence (AI) at the heart of new digital tools allows actuaries to extract structured data useful for creating more precise risk assessment models. This technology sits best alongside the expertise of insurance professionals who have years of experience in the industry. RGA’s partnership with DigitalOwl is an example of how AI combines with human knowledge for the best outcomes.

Description: Most industry professionals acknowledge that funding retirement needs will almost always require disciplined savings over a period of decades. Today, we are less than 30 years from the second half of the 21st Century. However, a majority of the Millennial and Gen Z generations are either not eligible for or are not using today's tax-preferred options for funding retiree medical and Long Term Care (LTC).