Description: Essay suggests reforms of the U.S. health care system to promote financial soundness, broader access, and efficient operations. These reforms require that each participant in the system – individuals, employers, providers, insurers, and government – give a little.

Description: A central problem for regulators and risk managers concerns the risk assessment of an aggregate portfolio defined as the sum of d individual dependent risks Xi. This problem is mainly a numerical issue once the joint distribution of (X1,X2, . . . ,Xd) is fully specified. Unfortunately, while the marginal distributions of the risks Xi are often known, their interaction (dependence) is usually either unknown or only partially known, implying that any computed risk measure of the portfolio is subject to model uncertainty. Previous academic research has focused on the maximum and minimum possible values of a given risk measure of the portfolio, in the case in which only the marginal distributions are known. This approach leads to wide bounds, as all information on the dependence is ignored. In this paper, we integrate in a natural way available information on the multivariate dependence and provide easy-to-compute bounds for the risk measure at hand. We observe that incorporating the information of a well-fitted multivariate model may, or may not, lead to much tighter bounds, a feature that also depends on the risk measure used. We illustrate this point by showing that the Value-at-Risk at a very high confidence level (as used in Basel II) is typically prone to very high model risk, even if one knows the multivariate distribution almost completely. Our results make it possible to determine which risk measures can benefit from adding dependence information (i.e., leading to narrower bounds when used to assess portfolio risk), and, hence, to identify those models for which it would be meaningful to develop accurate multivariate models.

Description: Introduction to Actuarial Considerations in Insurance Mergers and Acquisitions, M-FI03-1.

Description: New tools for managing insurance risk have particularly emerged in the 1980s and 1990s, usually with roots in the financial markets. A strong motivating factor has been the record number of natural catastrophes and their impact in insured losses. New organization or joint ventures have been created to meet this demand. From Securitization of Insurance Risk: The 1995 Bowles Symposium, M-FI97-1.

Description: The concept of crosshedging gives us the key to the actuarial understanding of most new tools arising in the area of alternative risk transfer mechanisms. Securitization of insurance, which is the theme of this symposium can, as I see it, almost always be seen as an exercise in crosshedging. The 1995 Bowles Symposium, M-FI97-1.

Description: There is no right price for a piece of insurance. There is simply the transacted market price, which is high enough to bring forth sellers and low enough to induce buyers. From Securitization of Insurance Risk: The 1995 Bowles Symposium, M-FI97-1.

Description: Successful healthcare reform: First, it must help that must keep healthy people healthy. Second, it must help people mitigate or eliminate the health-risks associated with unhealthy lifestyle behavior choices, and Third, it must ensure the provision of evidence-based care to those who are ill.

Description: By establishing insurance risk as an asset class, participants will provide the insurance industry with vast pools of capital to mitigate catastrophic risk through the use of new nontraditional reinsurance products. From Securitization of Insurance Risk: The 1995 Bowles Symposium, M-FI97-1.

Description: Catastrophic insurance futures are being traded, albeit thinly, at the Chicago Board of Trade. This paper examines the broad context for trading insurance risk. The motivation for trading insurance risks, specifically to increase the capacity to cover risk, is discussed. From Securitization of Insurance Risk: The 1995 Bowles Symposium, M-FI97-1.

Description: This paper gives two explicit formulae that estimate the yield of a portfolio of fixed income securities that are not interest-sensitive. The yield is explicitly estimated in terms of the discounting interest rates of the securities that comprise the portfolio. From 2006 Enterprise Risk Management Symposium, M-AS06-1.