Description: November 2017 issue of The Modeling Platform by the Modeling Section. Practical information for actuaries, trends that impact section, section activities.

Description: Results of 2019 survey to their subgroup members.

Description: Table of Contents

Description: Authored by a MIB Solutions team of Tom Rhodes, Stuart Klugman, Marianne Purushotham and Stacy Gill, the report summarizes the results of a study on the application and adoption of credibility theory within the life insurance and annuity industry. In addition to the report, numerical examples related to the application of credibility to company mortality and lapse data are provided in the four Excel files. This excel spreadsheet is a numerical example relating to the application of Credibility for mortality - Limited Fluctuation Method. Please see the SOA website research section for the full report on Credibity Theory Practices.

Description: It has been a little over a year since the release of the Society of Actuaries (SOA) Research Institute's Mortality Improvement Model, MIM-2021. Since then, waves of COVID-19 have continued to occur in the U.S. The uncertainty around the COVID-19 pandemic and the slowing of U.S. general population mortality improvement prior to the pandemic are just a few of the reasons that make developing MI projection scales difficult. Uncoverthe results from intercompany surveys on mortality improvement, including one that addresses COVID-19, discover insights from a mortality expert panel on COVID-19 and future mortality, and discuss enhancements to MIM-2021. By attending the session, you will: - Understand MIM-2021 and 2022 enhancements. - Understand SOA Research Institute activities around COVID-19 and impact on mortality improvement. - Apply research results and insights presented to daily work.

Description: This chapter focuses on creating practical models that aid in the prediction of the risk of readmission to a specific hospital within 30 days of discharge for Medicare patients, to aid in the identification and stratification of at-risk patients for hospitals considering building an intervention program in a cost-effective manner. For readers who wish to develop their own predictive model, a dataset is provided on the Actexmadriver.com website, and R code is provided in the appendix to this chapter.

Description: The Johns Hopkins ACG Team's comments regarding their participation in the Comparative Analysis of Claims-Based Tools for Health Risk Assessment.

Description: Appendix E is round 2 on comments on application of judgmental methods from the Delphi study. See the SOA Website Research section for the full Delphi Study of Economic Variables Report along with all the variables.

Description: Almost half of recent FDA approvals have been for orphan drugs. This trend is expected to continue in 2023. Orphan drugs are priced more than 30 times higher than non-orphan drugs, therefore their cost burden in aggregate has the potential to overwhelm the budgets of payers, especially that of smaller health plans. Hear how the cost impact analysis for smaller health plans require different considerations than for a larger health plan when modeling the impact of rare diseases.

Description: The frequent use and complexity of today's actuarial projection models has increased the importance of having efficient models. Model optimization can reduce both cloud costs and overall end-to-end clock times, thereby allowing companies to do more with less such as reducing close times, increasing controls, enhancing analysis, doing more complicated calculations, and/or improving employee workloads during the close. From design and data to execution and audit, come explore techniques that can be applied throughout the actuarial modeling process to optimize actuarial models for improved run-time, accuracy, and reliability. There will be a focus on techniques that don't rely on model compression. Topics covered include model design pitfalls, data handling, improving convergence on asset-liability projections, strategies for interacting with the cloud, and other tips for optimizing actuarial models.