Description: This session will explore governance considerations for insurance carriers leveraging machine learning models. During the session, panelists will share insights on the evolving predictive model and AI regulatory landscape, as well as techniques for developing or enhancing AI governance frameworks that comply with emerging regulatory guidance.

Description: What role do retirement accounts and insurance products play in wealth inequality pre- and post-bankruptcy in Washington, DC, in 2011?

Description: In today’s business world, many financial decisions undergo considerable analysis before the decision is made and the decision-maker is often held accountable for the outcomes. The purpose of this research is to introduce the concept of total risk analysis (TRA), which is designed to help the decision-maker answer key questions at the time the decision is made. This paper will focus on a specific example of a typical healthcare decision: setting a budget for claims in the upcoming year. In addition to explaining TRA and providing a case study, this paper presents quantitative research regarding cost distributions for health care costs.

Description: The Society of Actuaries released research in 2007, performed by Jim Toole, that develops a model for a U.S. individual life insurance company to consider its potential liability exposure as a result of a pandemic. Sponsored by the Mortality and Longevity Strategic Research Program Steering Committee, this paper updates several model assumptions including mortality in light of COVID-19.

Description: Actuaries historically modeled new launches in pharmaceuticals by anticipating the expected change to the market basket. This became more complicated with the recent launches of gene and cell therapies as they address rare diseases. Rare conditions have low total member volume to study and some do not currently have a diagnosis code to identify them within claims data. Addressing this modeling challenge has been growing more important in the recent years with the number of therapies launching. What has the health care industry, and more specifically health care, done to enhance modeling and how should this be altered for the future? Additionally, historic modeling has sometimes incorporated a level of direct medical treatment cost offsets where studies have shown lower treatment costs are achievable. Can gene and cell financial modeling include cost offsets as well? And if so, what are suggested precautions or limitations to this effort?

Description: Renal disease is a very heterogenous medical condition whose end state is dialysis, a recurring cost intensive medical condition. Dialysis cost is one of the major medical cost drivers in USA. Insufficient and improper care management in the early stages of CKD (chronic kidney disease) leads to early incidence of end stage renal disease (ESRD) among CKD patients which not only leads to high medical costs, but also reflects poor health quality.

Description: Lincoln Financial Group announced the beginning of a two-year data and analytics talent upskilling program with the Society of Actuaries, a global professional organization for actuaries. The SOA will facilitate training for Lincoln employees through a customized multi-phase educational program focusing on big data and predictive analytics.

Description: The article discusses the recent final and proposed regulations published by the IRS and Treasury on the required minimum distribution rules for qualified plans, which implement changes made by SECURE 1.0 and SECURE 2.0. The article is intended to identify the important rules in the final regulations, provide a framework for determining how the rules apply to beneficiaries of qualified plans and IRAs, describe the key differences between the earlier 2022 proposed regulations and the final regulations, and it summarizes the SECURE 2.0 provisions contained in the new proposed regulations.

Description: This report explores AI bias in insurance and health data, highlighting the ethical role of actuaries and offering cross-disciplinary guidance for fairer decision-making systems.

Description: Cover a variety of topics centered around the unsupervised learning technique called 'clustering'. The presenters will take you through a wide array of topics that range from 'What is Clustering?' to 'How can I use this technique to solve problems I didn't even know existed?' In the health care industry, everyone is looking for an edge in reducing total spend-cluster analysis finds the unambiguous in an ambiguous framework of results.