Description: The use of data to assess risk is not new to the life insurance industry, but has historically been limited to leveraging structured data. Join us as we discuss the next frontier: unstructured data.

Description: It's your first full day of productive learning! Start it off right with a delicious breakfast and warm welcome.

Description: Presenters will explore specific actuarial use cases, showcasing custom-built demonstrations and discussing a wider range of applications.

Description: The recent wave of innovation in GenAI has unlocked an entirely new category of AI applications. Whereas AI has traditionally focused on automation and predictions, LLM’s and Generative AI give us the opportunity to create AI applications that act as copilots. This emphasis on contelligence and empowering knowledge workers has already begun to change the way work is done. High expertise knowledge workers such as actuaries will be able to use this wave of AI Apps to make better decisions and dedicate more of their attention to the parts of the role that require domain expertise and judgement. Join Charles Morris, Microsoft’s Chief Data Scientist for Financial Services, as he talks about the latest advancements in this space and the opportunities it creates for expert knowledge workers. Charles Morris is the Chief Data Scientist for Financial Services at Microsoft. Charles has deep expertise in the financial services domain and works with many of the world’s leading asset managers, banks, insurance companies, and financial platforms to develop and execute their AI strategies.Currently, Charles is focused on applying Generative AI to financial services and advising many top financial institutions in building their own copilots and reimagining their businesses.Charles is a data scientist and machine learning engineer by profession and an expert in MLOps. Before joining Microsoft, Charles practiced data science, machine learning, and cloud engineering in the asset management industry. He has been a featured keynote speaker at several prestigious events and forums and is a highly sought after public speaker in the domain of AI and Innovation.

Description: Call for Practical Application Essays on NAAJ Articles

Description: Analyze financial risk and explore the foundation for pricing, valuation and other functions served by actuaries in the modeling profession during this webcast. Expect a focus on the importance of understanding and preventing bias. Observe the different types of bias, how it can enter into models, how to identify it in models and best avoidance practices. Join our presenter who is pursuing a Masters in Economic Analytics at Clemson University as he incorporates his recent economic research into the webcast material.

Description: In this SOA e-course, you'll learn how to develop an enterprise risk management (ERM) framework and help fulfill your SOA CPD requirement at the same time.

Description: 2014 marked a new beginning for small group(SG) health insurance market ushered in with adjusted community rated products priced from a single risk pool. It was anticipated that the mandated pooling of the risk would result in higher rates, especially for healthier groups. It is the aim of this article to show whether that view bears out in the actual market rates and if it is higher, then by how much. The article provides a point in time(1st quarter 2025) comparison of premium rates under two segments of the small group market, namely Qualified Health Plans(QHP) available under the small group ACA market versus self-insured Multiple Employer Welfare Arrangements(MEWA) plans.

Description: This article discusses the Halmstad prize, announces winners and asks for volunteers.

Description: Global trends in both technology and regulation are causing U.S. insurers to reflect more deeply on their model risk management frameworks. The world has seen a rapid proliferation of AI-based tools accompanied with an overall increased usage of machine learning models, exacerbating model risk and reducing transparency in an unprecedented manner.