Description: Results of the PBITT Working Group annual Variable Annuity Survey.

Description: The monograph walks the reader through the hindsight, insight and foresight building process while discussing theoretical and practical issues supporting the building of valid forecasts with provenance for each of these schema examples. That is, the analyst can document the iterative ‘profiling change processes’ mindscape and landscape elements by which and through which the successful forecast is built. This kind of forecast construction ameliorates the ‘black box’ problem of generating pattern output without an understanding of the pattern’s creation or contextual meaning that is often seen when using other methods, particularly machine learning and artificial intelligence. This issue is discussed, referencing appropriate thought leaders.

Description: The Casualty Actuarial Society, Canadian Institute of Actuaries, and the Society of Actuaries Research Institute are pleased to make available results from the 2021 Emerging Risks Survey, the fifteenth in the series. Conducted by Max J. Rudolph of Rudolph Financial Consulting LLC, the survey incorporated a set of Emerging Risks defined by the World Economic Forum as the basis for several of the questions. The survey also included questions related to current risk management topics.

Description: Enterprise risk management (ERM) is an orderly or guided conduct of an enterprise to deal with risks. For insurers, ERM requires full support and commitment of the senior management. ERM in the U.S. and Canada has evolved over the years into a complex ecosystem.

Description: Discover the latest insights on emerging risks in the Indian market with our comprehensive survey report. Uncover key findings on financial volatility, disruptive technology, and climate change, and learn how AI is reshaping risk management. Compare these results with North American trends and explore the optimistic economic outlook for the India market in 2025.

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

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: Canadian Institute of Actuaries (CIA) and Casualty Actuarial Society (CAS), has annually conducted a Survey of Emerging Risks. As the researcher for this project, I have asked open-ended questions thought to be useful to risk managers. In this article, I will summarize one of those questions from the 2015 and 2016 surveys and provide some perspectives for Canadian actuaries: Are there lessons learned that you would like to share with risk managers developing an enterprise risk management (ERM) framework (e.g., what worked, what did not)?

Description: This paper provides a summary of the Dec. 2012 summit of the Natural Resource Sustainability Group and invited experts.

Description: The SOA’s Artificial Intelligence Working Group explored the role of AI in actuarial practice, focusing on risk management, regulatory compliance, and ethical considerations. The discussion highlighted the importance of the NIST AI Risk Management Framework and Generative AI Profile in ensuring responsible AI development and deployment in insurance and healthcare.