Description: Final installment of a series on the evolution of risk management with a close look at high profile failed corporations.

Description: This article describes how insurers can expand the reach of their efforts with regard to Economic Capital EC into the broader enterprise risk management process. Some experts contend that can be done by shifting the focus towards value. EC has the potential to shed new light on valuable opportunities for insurers.

Description: The author makes 10 predictions of how risk management will change over the next decade.

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.

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.

Description: The management of The Guardian Life Insurance Company of America Guardian decided during 2006 to perform an economic capital EC analysis, with results to be delivered in the spring of 2007. A second generation EC analysis EC 2.0 was conducted from fall 2007 through spring 2008. This article describes EC 2.0.

Description: Enterprise Risk Management incorporates integrated risk management due to the fact that the majority of company failures result from multiple correlated causes. Sites findings from Mercer study

Description: Feature article discussing the four main perspectives of ERM.

Description: To provide high level information on a book selected and discussed during the December book club session, The Ten Commandments of Risk Leadership. In addition, this article serves as a promotion of the SOA book club as well as the upcoming sessions.

Description: Feature article that discusses how insurance and banking business models have continued to grow in complexity over the past 50 years—from simple and local risk exposures to the current environment of complex and global exposures