Description: Summary of recent SOA-sponsored research on Enterprise Risk Management practices as applied to health insurers, self-insured plans, and health finance professionals.

Description: At this time of economic distress, companies throughout the world are intensely focused on upgrading their risk management capabilities, as are their home country regulators. This article explores one example of how a part of this transformation was accomplished for several major Korean insurers.

Description: Highlights from the 8th Intercompany Long-Term Care Insurance Conference held in March 2008, consisting of 56 sessions covering a range of long-term care insurance LTCI topics each with a track-specific focus.

Description: Fact sheet that defines ERM, provides a brief history, discusses the role of the actuary in ERM and the importance of organizations implementing an ERM framework.

Description: Article discussing the benefits of the Chartered Enterprise Risk Analyst, CERA, credential.

Description: Joint Risk Management Section chairperson's corner, June 2023

Description: This article will examine four approaches under two different methods (eight in total) used to combat the non-additivity of key rates and will compare them under a number of rate environments.

Description: Introduces the concept of total risk analysis, a methodology used to answer questions like "what are the chances we will lose more than $1 million"

Description: Note from Editor introducing the articles in this issue.

Description: Economic risk analysis has two dimensions: time and frequency. Asset return varies by time because of economic cycles and economic structural changes. Risk is higher during economic recessions and smaller during economic expansions. In addition, different economic structures may exist at different time scales. Risk measures calculated based on daily, weekly, monthly and yearly historical data can be very different. The appropriate frequency depends on the time horizon of the analysis. Therefore, it is important to measure economic risk at both the time level and the frequency level. However, time series analysis and statistical analysis that have been widely adopted in economic risk analysis focus on only one of the two dimensions. In this paper, wavelet models are used to enhance both time‐invariant analysis and time‐variant analysis. Wavelet models can systematically analyze risk by time and frequency and provide richer information than time series models. Using wavelet models, risk measurement can easily be adjusted based on time horizon in a consistent way. Equity VaR estimation is selected to demonstrate the application of wavelet analysis in risk management.