Description: Our firm has developed the first publicly available insured lives mortality table for Cambodia using data science methods. This essay provides a brief background, our approach and the impact of our work.

Description: Emerging technologies like GenAI will be more disruptive than past technological developments, such as spreadsheets, low-code data and dashboarding tools, and cloud computing. This article will explore how how we can lead ourselves, our teams, and our organizations to thrive within a defined modern value proposition, using one of two archetype roles: actuaries as business partners or actuaries as developers.

Description: Python has become the fastest-growing major programming language in the world. It has surged in popularity over the last decade, following the development of its industry-leading capabilities in data science, machine learning and artificial intelligence, and it is now one of the most globally popular and widely used languages. In this article, I discuss some of the reasons for its popularity and explain why many actuaries and insurers have started using Python.

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: A look at the near future and far future of various elements of Actuarial Models as defined through ASOP 51. What is driving the complexity for inputs, calculations, and outputs. Howe will actuaries handle these challenge?

Description: Predictive modeling is a powerful toolset for assumption setting (mortality, lapse, etc.). The multivariate approach has its advantages in handling high-dimensional data, address correlations, and statistical significance. However, building insurance assumptions is far more than a simple modeling practice. One must take care to address how the model is applied and its business implications. This session will share the learnings from multiple projects.

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

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

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: Hardly a day goes by without a feature story about the latest reverberation from the expanding use of Artificial Intelligence/Large Language Models (tools) in a variety of settings. The pace of use (and misuse) of these tools, such as ChatGPT and Bard, has been explosive and shows no sign of abating. Many experts would argue we are on the cusp of a permanent paradigm shift in teaching/academics and overall application of technology. With these issues in mind, the Society of Actuaries (SOA) Research Institute’s Aging and Retirement program is interested in an exploration of this topic from a variety of perspectives. The result of this effort is intended to provide a useful resource for readers to become well-grounded on the issues surrounding the impact of these tools in a retirement context and set the stage for future research.