Description: This article addresses the concern that while risk assessment models are supposed to help identify and reduce risk, they can be a source of risk themselves. A new report released by the Canadian Institute of Actuaries in August 2008 helps address that potential problem by providing useful guidance to actuaries who are charged with designing, implementing and using advanced models.

Description: This article discussed modeling the P&C reinsurance market using an Agent Based Model to provide insights into the market. The characteristics of this marketplace provide credibility to this type of modeling. Specifically, the P&C reinsurance market has few major players, very little product differentiation, and low barriers to entry. In addition established competitors are volume-constrained due to prior business and capacity decisions made based on estimated product costs and prices.

Description: This article talks about the role that models played in the subprime meltdown and the subsequent crisis in the financial markets in general. The models failed to provide information about the magnitude of potential 'black swans'. Extreme Value Theory [EVT] is described as a potential solution to this error.

Description: This article describes the financial modelers’ manifesto. Focus is on how difficult it is to model financial instruments when there is a human element involved.

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.