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 provides an overview of those cognitive biases most often responsible for flawed risk assessments and provides practical techniques to mitigate them. Through a combination of mathematical rigor, case study, metaphor, and logic, the author highlights systematic errors in our thinking about risk and provides ways to avoid them.

Description: The objective of this report is to provide benchmarking information that will help companies address the needs of internal stakeholders in cost-effectively conducting and implementing an ORSA process. In order to obtain this benchmarking information, a cross-disciplinary survey was conducted to find out what insurance companies understand and expect from an ORSA, the effort required to complete an ORSA, and the benefits from doing so. This survey was undertaken on a global basis, with participants that included life, property and casualty (P&C), often referred to as "non-life" or "general" insurers in territories such as Europe, and health insurance companies in North America (the United States and Canada), Europe, and Asia.

Description: A discussion of the need to connect the interrelated requirements of reserve requirements, capital requirements, risk management, IASB requirements and so forth.

Description: This paper discusses various types of risks within an Enterprise Risk Management framework, responses to risk, and the implementation of an ERM framework.

Description: In this article, the author explains what a CAT model is.

Description: Metadata for entire issue

Description: The article is devoted to risk management in the business process of materials supply for industrial enterprises. The goals of the business process are considered, and the risks of the failure to achieve goals are identified. Probabilities and influence of negative events are estimated. The risk treatment is considered on critical risks, including forming of insurance supplies of materials. The calculations of insurance supplies of materials, taking into account risks, are conducted on the basis of statistical information.

Description: We demonstrate an integrated enterprise risk management (ERM) solution to optimize the risk portfolio, identify natural hedges, create an optimal risk treatment plan, enhance risk culture, and facilitate risk reporting throughout the organization.

Description: Abstract: An introduction to the Goals-Progress-Strategy (GPS) strategic risk management framework: an original synthesis of scenario based ERM, the Logical Framework Approach, and new metrics and methods. GPS improves strategic planning and execution and enables practical management of the risks a company faces in pursuit of its business goals. The framework provides a portfolio view of a company’s strategic objectives, a return on risk-adjusted capital measure, risk-intelligent decision making, and risk-adjusted performance measurement/compensation.