Description: In this article, the author discusses the capital shortfall an insurer faces because of the longevity risk on immediate annuities.

Description: Current risk management approaches for variable annuity business are not working very well in today's market turmoil.

Description: There will be inflection points in the value of an instrument when interest rates change. These inflection points could materially impact the approximation of value change using ALM metrics. In this part of the seven-part series, I will highlight: • How to identify the inflection points; • the range of rate changes where ALM metrics may be relied upon i.e., the “validity” range, outside of which recalculation of the ALM metrics is required and the potential that one needs to rebalance the portfolio; • a technique to improve on the approximation of value change beyond the validity range; and • a technique to convert non-linear change on the yield curve to be used with duration and convexity.

Description: This article departs from the usual GMWB pricing approach by assuming that the policyholder is always smart enough to act in his/her own best interest.

Description: This article provides background and key results of the Risk Premium Project of the Committee on Theory of Risk [DOTOR] of the Casualty Actuarial Society [CAS]. The project is intended to gather research on risk issues and encourage further development.

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: This article examines the emphasis that is currently being placed on assessing, monitoring and managing credit concentration risks.

Description: As sponsored by the Canadian Institute of Actuaries (CIA), Casualty Actuarial Society (CAS), and Society of Actuaries (SOA), the study looks at causes of insolvency and decisions made by management, regulators, and policyholders over the life cycle of the insolvency. Further, this study considers ways the profession can be equipped to prevent or mitigate future insolvencies. In addition to directly benefitting the profession, the work is also intended to assist other insurance industry practitioners in understanding the complexities of insurance company solvency and the benefit of keeping the actuarial profession in the forefront of company management, operations, and regulatory communication

Description: This paper evaluates the current practice of operational risk management in the insurance sector. Operational risk is nothing new in insurance, but, because of regulatory requirements, companies have initiated computation of risk capital for their operational losses. The current effort to manage operational risk is not a naturally evolving phenomenon, and operational risk, in the Basel Committee on Banking Supervision’s Basel II definition, is unlikely to be a significant cause of insurers’ failure. In addition, the current Basel II definition of operational risk is not suitable for the insurance sector. Consequently, the invention of models and tools based on the definition is incomplete and illusionary. My findings are based on the analysis of dozens of interviews with insurance industry professionals. I demonstrate the way operational risk is quantified in practice, show that the result obtained from this computation is of littl e use in managerial decision making and propose a set of policy recommendations illustrating the characteristics of operational risk in insurance. This study can be used as a platform for launching dialogues to initiate fresh thinking about operational risk in insurance beyond the current artificial and narrow boundaries.

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.