Description: Regular update provided by the Chair of the Joint Risk Management Section on initiatives put forth by the section council for the current year.

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

Description: View the Data Challenges in Building a Facial Recognition Model and How to Mitigate Them

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

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: This Q&A article discusses the use of machine learning to analyze unstructured data. Supriya Ramachandra, a data scientist at SIKKA, explains how her team uses natural language processing techniques, technical aspects of neural networks, LSTM modeling, and natural language processing. Machine learning allows for the classification of large amounts of unorganized data, providing actionable information for actuaries.

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: Neural Networks are no longer limited to classification and regression solutions to numeric problems. CNNs add the ability to classify images, and GANs can create new images. Learn how these capabilities can provide competitive advantages to early adopters, how they work, and how to implement them.

Description: There is enormous interest by investors and business leaders in the potential for artificial intelligence technologies, often powered by predictive modeling and machine learning, to transform the way that companies do business.