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: Virtual - Session 5A: Leveraging Gamification and Personalized Wellness to Grow the Business

Description: Session 7B: Health AI in Practice - Lessons From Top U.S. Health Systems

Description: In this session, we will explore the opportunities and challenges of leveraging AI tools to support valuation actuaries in their work. We will begin by introducing the concept of large language models (LLMs), discussing their capabilities, limitations, and potential errors. We will then delve into case studies that demonstrate how LLMs can be effectively utilized to reference actuarial documents.

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

Description: Hardly a day goes by without a feature story about the latest reverberation from the expanding use of Artificial Intelligence/Large Language Models (tools) in a variety of settings. The pace of use (and misuse) of these tools, such as ChatGPT and Bard, has been explosive and shows no sign of abating. Many experts would argue we are on the cusp of a permanent paradigm shift in teaching/academics and overall application of technology. With these issues in mind, the Society of Actuaries (SOA) Research Institute’s Aging and Retirement program is interested in an exploration of this topic from a variety of perspectives. The result of this effort is intended to provide a useful resource for readers to become well-grounded on the issues surrounding the impact of these tools in a retirement context and set the stage for future research.

Description: The document is a research call for proposals seeking researchers to produce a report on the uses of synthetic medical claims data for actuaries. It outlines the background, purpose, research objectives, proposal requirements, selection process, and conditions for submission.

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: Zero-Knowledge Proofs (ZKPs) represent an innovative suite of cryptographic algorithms that empower the insurance community to validate the accuracy of sensitive information without revealing the actual information itself. Mutation with the use of non-traditional data entering the insurance processes of customer acquisition and in-force management is currently taking place. A shift toward using non-traditional data in insurance customer acquisition and in-force management processes is currently taking place. This evolution is captured in the Australian market through surveys and interviews. Come and join us to learn about these two new research studies that open up the possibilities for the insurance industry to be more efficient in delivering its value to the society.