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.

Description: Initiated by the Financial Reporting Section, this paper explores rising interest rates. Following this path, the paper will look at implications of interest rate changes for the life insurance industry, current stress testing practices, and how a risk manager can proactively prepare for an uncertain future. A paper published in 2014 focused on why rates could stay low, and some aspects of this paper are similar (e.g., description of insurance products). This paper also uses a sample model office to help practitioners look at their own exposures. It includes typical interest-sensitive insurance products and how they might perform across various scenarios, as well as a survey to establish current practices for how insurers are testing interest rate risk currently.

Description: Research report describing the results of an Emerging Risks Survey conducted in 2015. The report includes comparisons to the previous surveys.

Description: The Society of Actuaries released research in 2007 that develops a model for a U.S. individual life insurance company to consider its potential liability exposure as a result of a pandemic. Sponsored by the Mortality and Longevity Strategic Research Program Steering Committee, this paper updates several model assumptions including mortality in light of COVID-19.

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

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

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.