Description: Level funded products often target the small group market (2-50) and can result in many manual and tedious processes for underwriting to perform risk assessment. Learn how a carrier used technology to help automate risk assessment without the need for paper medical questionnaires, and exposed a risk engine for broker quoting to enable near real-time of pricing for risk-based products. The approach reduced labor and allowed underwriting to focus solely on fallout cases while also improving pricing consistency. Discuss broader trends in the health market for risk assessment, including new machine learning cost predictions that can be used for automation and better predictions of future costs. Discussion topics will include underwriting guidelines, business rules, risk scores, and machine learning. By attending this session, you will have a better idea of new trends in risk assessment for small groups where no claims experience is available. And, better understand business rules that are common in underwriting for flags for review as well as how risk scores and machine learning can be used during the underwriting process.

Description: 1997 Valuation Actuary Symposium, Session 5 explores health cash-flow testing.

Description: This report outlines the current wellness environment, the objectives of the wellness study and provides a summary of the overall study findings. This report is supplemented by the Research Summary Report, Survey Results, and Interviews with Researchers. This document includes a summary of key findings from each of the three phases.

Description: The presenters will discuss predictive analytics as applied to recent group life and disability experience studies and other applications.

Description: Model design is an important part of being an actuary, and the SOA highlights the importance of the actuarial control cycle of model design, evaluation and monitoring. What tools are at our disposal for these steps? When should we be concerned or excited about model performance? Can we, and should we, use machine learning tools to assist with model improvement or development?

Description: Explore SOA-sponsored research on Social Determinants of Health (SDOH) during the How Does Where You Live Impact Your Health webcast. Dive into SDOH data and modeling that will focus on cluster analysis. This will help determine the overall impact of your area's affect on your health and life. This webcast also covers an overview of the existing SDOH-related programs that may affect or intersect with health plan or provider SDOH initiatives. Discover the importance of the place you live and future impact of your overall health.

Description: Much of the work performed by disability insurance actuaries depends on the availability of accurate and detailed data, which is not always as simple as it sounds. Explore a variety of data challenges faced by disability actuaries, along with potential solutions. Potential topics include finding relevant data, the impact of poor data on valuation work, the impact of new privacy rules, and the potential bias in the data used to develop predictive models.

Description: The American Academy of Actuaries Health Solvency Subcommittee and the NAIC Health Risk-Based Capital (E) Working Group are in the process of analyzing and reviewing the H2-Underwriting Risk component and the managed care credit calculation in the health risk-based capital (HRBC) formula. Come learn what changes are ahead! While RBC is designed for solvency issues, also come hear about other ways health insurers manage their capital and surplus levels. Are others doing something you should try?

Description: Discuss various analytics and use cases using payer published reimbursement contract data under federal mandate of Transparency in Coverage. These contract rates are publicly available in machine readable format (MRF) starting July 1, 2022, and refreshed monthly. By attending the session, you will have a better understanding of the state-of-art development and analytics using MRF data, including the technologies used to extract and analyze huge MRF files, validation and limitations of published rates, and their use cases.