Description: This session will focus on what is new and coming at the Appointed Actuary (e.g., Actuarial Guideline ((AG)) 53, equity testing, etc.). We will provide highlights from the updated AAT Practice Note. A particular focus will be paid to asset classes that have received regulatory attention recently ((e.g., commercial mortgage loans, collatoralized loan oblications (CLOs), etc.)).

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

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

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: 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: 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: 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: 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: Dive into this review on Artificial Intelligence and Machine Learning (AIML) techniques for actuarial modeling for life & annuities. Presenters will showcase learnings from the recent SOA research paper "Predictive Analytics and Machine Learning – Practical Applications for Actuarial Modeling" (Nested Stochastic). The researchers will go over models and methodologies used to develop high-fidelity proxy models for various life & annuity applications.

Description: Learn from panelists from different companies as they come together to discuss their experiences.