Description: This is the full research report for the thirteenth Emerging Risk Survey which summarizes the results of the survey.

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: The research provides a modeling framework for assessing the inundation risk of properties and their expected flood damages, thereby laying a foundation for flood insurance pricing. The researchers studied over 50 years of claims data from the National Flood Insurance Program with 2.5 million records and identify property characteristics that predict flood damages for inundated properties. The development of a private flood insurance market benefits from insurers’ ability to better understand and price flood risk. This research takes a closer look at flood risk modeling and flood insurance pricing.

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: The Society of Actuaries announces the release of a new report that will provide a resource for the insurance industry to learn about image recognition technology. Authored by Kailan Shang, the report explores the current status of image recognition technology, models for image recognition, and various possible applications of image recognition to insurance.

Description: This paper discusses a theoretical framework for Enterprise Risk Management, risk dynamics within property-casualty insurance companies, empirical findings on widely used risk models, and examples of effective risk models.

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: 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: A research report that first defines ERM and provides the results of an applicable literature search with hyperlinks and then describes the current state of Enterprise Risk Management practices for health organizations. Areas covered: 1. Operational Risks. 2. Balance sheet risks. 3. Pricing discipline. 4. Asset risks. 5. Learnings. 6. Emerging risks.