Description: This literature review provides insights on emerging technologies that interact with the actuarial profession within the space of microinsurance for the purpose of establishing a frame of reference for actuaries to use in their work. Furthermore, it intends to spark readers’ interest in, and create a vision for, how microinsurance and its associated technologies may impact the actuarial industry in the future.

Description: A brief overview of recent AIT research papers in summarized format.

Description: This SOA e-course shows you how to use financial modeling to assess or mitigate risk. It covers derivatives pricing, range of outcomes and more.

Description: The 2023 Professionalism in Practice Course will study, discuss and explore the professionalism practice, code of conduct and application of the actuarial profession. Our speakers are seasoned presenters from mainland China. Experts will cover several issues encountered in daily actuarial working environments. Content will include business cases and interactive discussions, which aim to enrich the practical learning experience of attendees. Audience attendance will be limited in order to provide an interactive, collaborative learning experience. Early registration is highly recommended to secure a seat.

Description: Supplemental Health, DI & LTC Conference

Description: This session shows the fascinating world of Generative AI, focusing on the principles of Retrieval Augmented Generation and Agentic Workflows. Attendees will gain a comprehensive understanding of how these advanced AI techniques can revolutionize processes by integrating external data retrieval with generative models. Practical examples and expert insights will illustrate the transformative potential of this technology in various industry applications.

Description: This session will discuss essential theories and practical applications of deep learning for actuaries. Participants will gain insights on leveraging these cutting-edge techniques to enhance actuarial models and drive predictive accuracy.

Description: Review a recently completed research project for a multi-stakeholder data consortium on social determinants of health (SDOH). In this project, claims, external SDOH data, geospatial analysis, and machine learning models were used to examine several questions: How to identify SDOH vulnerabilities? How sensitive are the findings with respect to provider coding pattern variations? How much variability in cost can be explained by SDOH vs. morbidity? What are the key risk drivers revealed by machine learning models? The session will review the methodology and main findings from this project.

Description: This report provides a toolkit for actuaries and other interested parties to model and forecast mortality by cause and socioeconomic factors.

Description: Call for essays on how actuaries can apply their financial skills to support non-profit financial management and promote societal purpose.