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

Description: The Canadian Institute of Actuaries and Society of Actuaries Committee on Life Insurance Research, the Product Development Section and the Financial Reporting Section, sponsored this study investigating how the Canadian life insurance industry is utilizing predictive modelling.

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: There is value in a framework that allows a smooth transition from a qualitative assessment to a quantitative analysis as entities mature in their understanding of climate risk. In this report, a case study on climate change impact on home prices is used to illustrate a Bayesian network iterative approach to building a model for scenario analysis.

Description: With the growing threat of cyber incidents, organizations and governments are rightfully concerned. In recent years, cyber incidents have caused significant losses to entities and insurers across the world. Therefore, there is a need to understand and provide greater context around the topic of catastrophic cyber risk, which has implications for insurance companies, reinsurers, regulators, consumers, and society. Taking a multi-disciplinary, holistic approach, an expert panel study was conducted on catastrophic cyber risk in this four-part series of discussions and subsequent reports.

Description: This report explores how artificial intelligence can be applied to investment and retirement planning, highlighting real-world applications, risks, and recommendations.

Description: This report captures expert insights from a March 2025 roundtable on how generative AI is shaping actuarial work and insurance industry practices.

Description: Our panelists will explore fixed income topics from an actuarial perspective. We'll start with the basics of bonds, including sensitivity measures like duration and higher moments. Then, we'll discuss bond ALM characteristics, highlighting the advantages and disadvantages of incorporating various bonds into a portfolio. Finally, we'll cover actuarial modeling considerations, such as reinvestments, defaults, expenses, and other assumptions. We encourage the audience to ask questions throughout the presentation and we hope you can join us for an engaging discussion!

Description: This three-part series provides an overview of the rapidly evolving and dynamic gene and cellular therapy landscape, from the clinical, historical, and risk transfer perspectives. It covers the actuarial considerations in pricing cell and gene insurance and reinsurance, the value assessment of the therapies, manufacturer pricing, and reinsurance cost.

Description: Artificial intelligence is rapidly transforming the investment landscape. From natural language processing and large language models to physical AI applications like robotics, autonomous vehicles, and drones, the evolution of AI is reshaping both how we analyze data and where we find opportunity. We’ll begin by exploring the evolution of AI, which is already driving disruption across industries such as coding, customer service, and marketing. However, the future of AI is physical AI (drones, AVs, robotics). With valuations already stretched, and growing concerns about the “circular economy” and bubble risks, investors should focus on high-quality tech companies that generate free cash flow and deliver strong returns on invested capital. We'll explore examples of interesting companies across the globe: Meta, Alphabet, and Uber in the US; ASML in Europe; Tokyo Electron in Japan; TSMC in Taiwan; and BYD in China. The session will also examine how natural language processing and large language models are reshaping the way quantitative and fundamental managers extract insights from raw data. We’ll highlight how these tools are being deployed to enhance understanding of risk and return, and how they’re increasingly supporting collaboration between quant and fundamental teams.