Description: Many risk management decisions involve the timing of implementing risk strategies. The cost of hedging, capital raising and securitization changes with the economic environment. The timing of de-risking and investment in new risk management functions affect the cost and benefit of these projects as well. Like investment timing, it is important to consider the timing in risk management decisions to maximize the gain of risk management projects. This paper discusses methods of determining the appropriate timing of implementing a risk management strategy or investing in risk management projects. It explains the human biases that may lead to inferior timing decisions. It also covers the costs and benefits of risk management projects and the impact of new information on the decision-making process. Timing considerations for financial risk hedging, insurance risk hedging and investment in new risk management projects are explained. Factors used for timing decisions include economic conditions, market volatility, credit rating, borrowing cost, capital adequacy and financial resources.

Description: People naturally observe risk in the form of the range of experienced gains and losses which is usually represented in statistical terms by standard deviation. In most cases, there are not enough observed values to reliably discern the true amount of losses that are possible in extreme situations. Statistical techniques that have long been applied to insurance company risks are being used to extrapolate from observed risk to extreme tails of the distribution of gains and losses. These processes are essentially an extrapolation from the “known” risk of volatility near the mean to “unknown” risk of extreme losses. “Fat tails” is a term often applied to risks where the likely losses in rare situations significantly exceeds the predictions of a Gaussian (“thin tailed”) distribution. This paper will look at the relationship between the observed risk and the extreme risk in statistical insurance r isk models and discuss how we might create a discussion among model users about the appropriateness of that relationship for specific types of risks.

Description: This paper examines the problem of a growing net benefit reduction for working women who are entitled to benefits in their own right, as well as to benefits as surviving spouses of covered workers.

Description: This paper uses the property-liability insurance companies as a research sample to investigate the relation between the enhancement of cost efficiency and the usage of reinsurance and financial derivatives as risk management tools. The stochastic frontier approach is applied to consider not only the mean of cost efficiency, but also its variance. The sample includes both organizational forms, namely, stock and mutual insurers.

Description: The author advocates trying to maximize the diversification of investment portfolios based on creating multiple sources of income, each taxed in its own way, based on the premise that taxation of retirement income in the future is no longer predictable. From the 2011 Enterprise Risk Management Symposium, March 2011.

Description: People naturally observe risk in the form of the range of experienced gains and losses which is usually represented in statistical terms by standard deviation. In most cases, there are not enough observed values to reliably discern the true amount of losses that are possible in extreme situations. Statistical techniques that have long been applied to insurance company risks are being used to extrapolate from observed risk to extreme tails of the distribution of gains and losses. These processes are essentially an extrapolation from the “known” risk of volatility near the mean to “unknown” risk of extreme losses. “Fat tails” is a term often applied to risks where the likely losses in rare situations significantly exceeds the predictions of a Gaussian (“thin tailed”) distribution. This paper will look at the relationship between the observed risk and the extreme risk in statistical insurance r isk models and discuss how we might create a discussion among model users about the appropriateness of that relationship for specific types of risks.

Description: Abstract for the 2008 ERM Monograph paper, “Effects of Integrated Risk Management on Mean and Variance of Cost Efficiency of Property/Liability Insurance Industry”

Description: This is the panel transcript for the 2017 LT100 Symposium Session 2C: Impact of Aging: What Can Individuals and the Private Sector Do to Address Challenges?

Description: 2011 Enterprise Risk Management Symposium, Chicago. This is the abstract of the entitled paper.