Description: The costly, time-consuming and complicated process of enterprise risk management (ERM) can be improved in many companies and made less tedious for managers by using reasonable data and templates obtained from peer group entities. The models used to calculate economic capital (EC) often underestimate its value because they do not consider decision-maker perception about risk. We assume here that managers, as the decision-makers, have appropriate business understanding and they can provide substantial information about risk characteristics regarding all business processes. Therefore we are focused, in this paper, on collecting data from managers across the different businesses to derive the appropriate knowledge about risky events, the importance of particular types of risk, the relationship between the risk outcomes and the level of risk control in a particular industry. We conclude that the collected data has a high potential for use as a benc hmarking reference and analysis for improving ERM models for individual businesses.

Description: 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.

Description: Description of considerations and perspectives to be taken into account by incentive compensation plans.

Description: Companies need to learn to plan for uncertainty by taking into consideration downturns, not just an environment of moderation and occasional booms.

Description: Target volatility, as an investment strategy, has been used by many funds not only as a way to smooth return but also as a way to manage risks of the VA guarantees. Contrary to existing research which favors volatility targeting over fixed allocation, this article shows that because of the existence of market jump risk, target volatility strategy does not necessarily offer an improved risk profile for VA writers. Further, target volatility coupled with leveraging can significantly increase tail risk for insurance companies.

Description: In summary, the goal of this report is to foster better industry-wide education, training and practice that decreases the future range and scope of what leading risk management professionals will henceforth label as being unpredictable as events now commonly thought to be so.

Description: State regulators' review of predominant LTC Risks after review of year-end AG51 reports.

Description: This paper demonstrates that extreme value theory (EVT) can be used as a tool to model policyholder behavior in the extreme tail. This paper applies EVT to the study of variable annuity dynamic lapse behavior in the extreme tail. It illustrates a process whereby a company can fully model policyholder behavior, including the extreme tail, with existing data. No judgment about the extremal behavior is necessary.

Description: Abstract: The U.K. Pension Protection Fund (PPF) was established in April 2005 to protect the pensions of members of U.K. private sector defined benefit pension schemes that have insufficient assets and whose corporate sponsor fails. The Fund takes over the pension scheme assets and assumes responsibility for the payment of compensation to the former members of the scheme. The PPF is funded by a levy on the population of eligible schemes. To improve its ERM framework, the PPF has undertaken a reverse stress testing exercise. This analysis provided the organization with new insights into its risk profile, the scenarios leading to the PPF’s potential “failure,” and interactions between these scenarios. This paper discusses the principles and objectives of reverse stress testing in the special case of the PPF and then illustrates the application of complex system science techniques for the purpose of reverse stress testing.

Description: Project portfolio risk management and risk analysis form one of the critical components of enterprise risk management. Organizations measure and analyze risks associated with projects, project portfolios, and programs. The important step of the process is quantitative risk analysis of project schedules using event chain methodology (ECM). ECM is a stochastic modeling technique for schedule risk analysis. All risks, including schedule and nonschedule-related risks, are assigned to a particular project and within this project to the particular activity or resource. Further, ECM allows one to model the relationship between project risks by defining risks that cause or trigger other risks. All risks and relationships between them will be presented on the project or portfolio Gantt charts using event chain diagrams. After risks are assigned to project and portfolio schedules, Monte Carlo simulation of the project schedule is performed. ECM simplifies complex risk analysis process.