Description: The Society of Actuaries (SOA) Research Institute received a grant from the U.S. National Science Foundation (NSF) to educate insurance actuaries on the use of wildfire risk datasets and models to be developed by researchers from academia and the U.S. National Aeronautics and Space Administration (NASA).

Description: PartnerRe Life and Health is rapidly growing its presence in global markets. This growth means that our medical underwriting team has to handle 25 percent more cases every year. To manage these additional cases without increasing headcount at the same pace, the team has to operate more and more efficiently. In a market where response time is a key differentiator, we improve efficiency by using machine learning to triage and prioritize the underwriting team's case work. In this talk, we describe the model pipeline end to end. That is, we cover the entire implementation chain from accessing data to the eventual evaluation of the added value. In particular, we discuss often neglected topics such as model risk mitigation, technical deployment of the model and integration into business processes.

Description: In year’s past, we presented the Practical Predictive Analytics Seminar (PPAS) as an add-on to the Life and Annuity Symposium or attached to the Predictive Analytics Seminar, this year it will take place as a stand-alone virtual Seminar.

Description: This newsletter provides a regulation outlook for the use of AI/ML in insurance industry, interpretations of regulatory expectations and what insurers should consider when managing risks associated with the development, implementation and use of AI/ML models/tools.

Description: Ever wanted to do a Kaggle data science competition, but didn't know where to start? This presentation meets the needs of actuaries interested in predictive analytics and competitive data science. The presentation will describe the nature of competitive data science, and provide insights into lessons learned by competing in the Airbus Ship Detection Challenge at Kaggle, as well as other Kaggle competitions. The presenters will provide an introduction to neural networks and describe the nature of the Airbus Ship Detection Challenge and other Kaggle competitions, plus a solution approaches that can be used to obtain top scores using Convolutional Neural networks (CNNs), random forests and boosted trees.

Description: View the Avoiding Unfair Bias in Insurance Applications of AI Models - Chinese

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

Description: How the speed of change is accelerating and how we could react to this as a profession.

Description: The purpose of this report is to demonstrate how artificial intelligence applications have grown since their infancy and invite the reader to consider the vast data at our disposal for the future.

Description: A literature review report that looks at research on how artificial intelligence is used in actuarial work.