Description: We will share the latest research from the Actuarial Innovation and Technology (AIT) Strategic Research Program, with a focus on research relevant to health actuaries. Attendees will learn about leading-edge technology that has impacts on actuarial functions, both broad and specific innovations and breakthrough technology, and the resulting impacts.

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

Description: Learn how insurers provide new opportunities for efficiency and value creation from product design and underwriting through customer engagement and claims. Glimpse some industry use cases for Gen AI and its outcomes as observed by the first movers.

Description: Every patient leaving the hospital has personal life-context circumstances that impact their chances of successful recovery and complications can be costly. Complex care management impacts over 50 percent of health care spend, with the admitted commercial population driving 37 percent of spend or $177M per 100,000 lives and the Medicare population driving 53 percent of spend or $600 million per 100,000 lives. The stakes are high, but existing care management solutions are mostly clinical and navigation call centers provide fragmented and outdated patient management systems, and do not address individual life-context. Discharged patients therefore remain underengaged and undercompliant, leading to costly complications. Innovative technology can help enable and integrate systems and existing infrastructure to leverage evidence-based contextualized care that will enhance care management, improve efficiency, and drive a better experience and outcomes for patients. This technology helps codifies life context, dynamically stratifying and engaging members digitally and telephonically helping virtual care teams to be more effective and efficient. In a recent randomized clinical trial, this technology and approach has shown a 50 percent reduction in the total cost of care, cutting the average and total cost of readmission, increasing virtual care team impact and member engagement and trust.

Description: This document is a Request for Proposal (RFP) issued by the SOA Research Institute, seeking researchers to assess the impact of artificial intelligence on the insurance and healthcare industries in Asia, with specific research objectives, proposal requirements, selection process, submission guidelines, and appendix providing cost estimates.

Description: Read this report to learn more about interpretable machine learning techniques for health insurance fraud detection.

Description: This report explores the adoption and impact of artificial intelligence and large language models in the Greater China insurance industry, drawing from surveys and case studies.

Description: CMS has required hospitals to publish their chargemaster rates, cash discounts and negotiated rates as of January 1, 2021. Our panel is comprised of a data strategist, an executive from a large hospital system and an actuary.