Description: This research report analyzes the risk associated with the use of models through the potential for model error.

Description: This research report, based on Ontario pension plan data, examines differences between going concern and solvency valuations.

Description: Health care cost trends are a key ingredient that health care actuaries use in their practice. In collaboration with the Health Care Cost Institute (HCCI), the Society of Actuaries has put together a data extract for practicing health actuaries to be able to better understand historical trends and cost disruptors.

Description: The study covers the extent of the use of big data or data analytics to enhance insurer operations, including sales, distribution, product development, underwriting and claims management within various markets within the Asia-Pacific region where the SOA has a strong and growing member population.

Description: This is the Phase I report of a two–phase effort. Phase I consists of defining relevant and actionable consumer segments among middle–income/mid–level net worth households. The Phase II report, defining a basic approach that could lead to a set of answers or 'solutions' that addresses the retirement risks faced by each segment, was released in September 2010.

Description: This report, part of the Society of Actuaries [SOA} ‘Research Projects – Finance/Investment,’ is sponsored by the SOA Committee on Finance Research. This research report examines modeling of cash flow associated within a pool of mortgages, specifically focusing on the effectiveness of infusing a limited amount of capital into the pool. The report was prepared by Michael Ekhaus of Gibraltar Analytical, LLC.

Description: This report analyzes the results of a survey of LTD carriers in the United States, focusing on how LTD carriers reflect benefit offsets in the valuation of their reserves.

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

Description: Underwriting has continually evolved throughout the history of insurance. Technology advancements over time have opened, and will continue to open, new underwriting possibilities from both process automation and content standpoints.

Description: This research paper is intended to be a primer on extreme event modeling and mitigation for practitioners. It covers the complete cycle of extreme event risk management, from identifying experience data sources, to extreme event detection, to modeling and dependence analysis, and finally to monitoring and mitigation. This paper explores extreme events from the perspective of a global insurance company, with an emphasis on market risk, credit risk, insurance risk, liquidity risk, and business risk. Extreme risk concepts and models are introduced from a practitioner’s perspective without unnecessary theoretical details. This report is not intended to be all-encompassing, but rather to focus on the key aspects of extreme risk analysis and its application. The input data and R programs underlying the numerical examples herein are available in the supporting files accompanying this report