Description: Modern Actuarial work, being quite data intensive, provides many opportunities for actuaries to use the statistical skills that are part of their basic training. Furthermore, modern computing allows us to analyze vast quantities of data intensively, and each package will provide statistical 'answers' to any questions the actuary might ask of it. However, in this particular field, it is often worth taking a step back, and ensuring that we recall and consider the warnings that come with each of the statistical procedures we might attempt to use. This will allow us to ensure that we guard ourselves against drawing inappropriate conclusions, which could come back to haunt us later.At the conclusion of the session, attendees will be able to avoid drawing inappropriate statistical conclusions, while doing their work. They will leave informed about the types of pitfalls that exist, and where those might come into play in actuarial work.

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 report describes two methods, an observation-based analysis and an actual to model analysis, to analyze long-term care insurance experience to determine if calendar year trends exist.

Description: The presenters will highlight differences in mortality that result from socioeconomic issues. Topics will include the differences in cause-specific mortality among different socioeconomic classes, trends in these gaps over time, and recommendations for reducing inequalities in life expectancy in the future.

Description: The session offers high-level initial steps to get started using R, as well as a list of helpful resources for both general data science and actuarial science with R. Attendees will learn about popular R packages to perform practical tasks such as importing, transforming and visualizing data, as well as packages commonly used by actuaries. You will also be introduced to the markdown package for creating reproducible and reusable analyses and workflows. By the end of the session, you will be familiar enough with using R and RStudio to begin incorporating these tools in your day-to-day work as an actuary

Description: SOA and LIMRA request mortality data for deferred annuities issued 2015–2024 to support an updated industry experience study.

Description: How do Professionalism and the Actuarial Standards of Practice apply as the way we work and tools we use continue to change? Business is conducted via social media and messaging and Generative AI allows for additional scenarios, analysis and oversight. Join us for an interactive session to go deeper into these topics including case studies, polls and a panel discussion.

Description: This suite of projects analyze four decades of U.S. mortality disparities across socioeconomic groups, providing data-driven insights using life tables and demographic techniques.

Description: Learn about the latest developments in hospital and payer price transparency data. Hear experiences working with the data and attempts to gain meaningful insights for actuarial and other purposes. Discover challenges and workarounds associated with this data, including file size, comparability of prices, duplication of prices, aggregating provider NPIs into meaningful groupings, and missing payer information.

Description: This report covers the latest emerging trends in U.S. population mortality. The SOA relied upon data furnished by the Centers for Disease Control and Prevention (CDC). Observations are based on the CDC’s recent release of 2021 mortality experience, along with prior mortality experience data from 1999 through 2020.