Description: In this session, we will do a deep dive into the potential of large language models; we will explore how new AI tools can be combined with traditional modeling to automate aspects of risk assessment. Industry experts focused on operationalizing this technology will talk through their approaches, lessons learned and demo use cases. We will also share insights around creating a robust AI strategy based on business objectives and regulatory considerations. Learning Outcomes: • Applications of large language models in risk assessment use cases • Regulatory considerations around the use of generative AI

Description: In this session, actuaries and data scientists will describe how the Cleveland Clinic has utilized large language models to support caregivers with difficult end of life conversations with patients and their loved ones. While artificial intelligence is often prefaced with words of caution, it can also be harnessed for good.

Description: Session 3A: State-Specific Enrollment Modeling - Understanding Disenrollment Trends and Population Dynamics

Description: Exhibits for Predictive Analytics Framework

Description: This report is a technical paper on a Predictive Analytics Framework and Reusable Workflow for Experience Analysis in actuarial studies. It covers data analysis, machine learning models, methodologies, and model interpretation techniques.

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: 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: 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: Session 10F: Debating AI - Valuable Tool or Overhyped Trend?