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: 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: 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: 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: This report looks at identifying drivers of systemic risk to China’s insurance industry and develops a measurement method for systemic risk as well as systemic risk dependence between the insurance industry and other industries.

Description: Early detection and assessment of insurer’s insolvency risk are critically important to regulators, insurers, policyholders, and investors for fiduciary assessment of insurer’s financial stability and for protection of potential financial loss associated with insurer’s insolvency. This proposed study aims to develop a market-based insolvency prediction model to detect financially distressed insurers at an early stage with the information content of higher moments from the market.

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.

Description: This project examines how companies perform deterministic scenario analysis, focusing on a worldwide IT disruption and its operational impacts. It highlights the use of table-top exercises to estimate direct and indirect effects, leveraging senior managers' experience.