Description: Virtual - Session 4C: Price Transparency for Payer-Provider Negotiations

Description: The panel will discuss several product challenges including modeling hybrid/combo long-term care products, modeling benefit options that are difficult to model using deterministic methods, modeling current situs of care versus original situs of care, monitoring assumptions, streamlining experience studies within the Long-duration Targeted Improvements (LDTI) framework, and model decision making with limited credible data. The panel will then move into solutions observed to address some of the aforementioned challenges and the future of long-term care modelling

Description: En el seminario hablaremos sobre los nuevos flujos de tarificación, y nos enfocaremos en la inclusión del análisis geográfico en el proceso de modelado para optimizar la extracción del riesgo en modelos de Machine Learning.

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: This session will cover everything you've wanted to know about GLMs but were too afraid to ask. How do these generalized models relate to the plain linear regression, and how can we be sure that the models we implement are appropriate for the task at hand?

Description: Session 2F: Artificial Intelligence and Actuarial Modeling - Ask an Expert!

Description: Virtual - Session 2B: SOA Research Report - Incorporating SDOH in Risk Adjustment

Description: Best-in-class analytics allow companies to quickly understand results and dynamically manage their business. When enhancing analytics, we can learn from companies that have recently deployed new dashboards for Long Duration Targeted Improvements (LDTI), International Financial Reporting Standards 17 (IFRS17) and principle-based reserving (PBR). Data transformations and new software tools provide significant opportunities, but many companies are grappling with an actionable path forward to implementing new analytics.

Description: The Smaller Insurance Company/Chief Actuary Forum presents a unique format for focusing on issues faced by actuaries in leadership positions or actuaries supporting the Chief Actuary. By discussing critical issues with your peers, you will leave with ideas to incorporate in your business environment. The Forum will feature presentations to introduce several of the discussion topics, followed by an opportunity to break into smaller discussion groups and rotate among topics.

Description: A priori, one would expect In Home Assessments (IHA) and Telehealth (TH) Encounters to identify some conditions that lead to actions that keep a member or two out of the Emergency Room. Similarly, one would expect Care Management and Disease Management engagement to ultimately influence some improvement in documentation that leads to more accurate Risk Adjustment. The business cases for these activities are often siloed to only the primary activity. The relationship between risk adjustment and care management is often more recognized as competing interests - one generally relying on utilization and the other trying to reduce it. Business cases can change dramatically when profiling has a more complete picture. This session will explore some techniques and share some observations - positive and negative - of the interactions between CoC and Risk Adjustment.