Description: Article introducing a new department in the newsletter by the section's SOA staff partner.

Description: Feature article that defines strategic risk management (SRM) and discusses ways to design and optimize a company’s SRM process.

Description: We focus on those Strategic Risk Management (SRM) approaches which articulate challenges to strategic execution, prioritize risks to attaining objectives, drive key performance metrics, and improve the chance of success. By using these qualities as our guide, we drive SRM which resonates with the C-suite and creates risk management intelligence which drives success.

Description: Risk management techniques do not include system science. System science requires that the uncertainty of the world is incorporated into the results. The articles explains the difference between risk and uncertainty. Learn how risk practices create an overoptimistic view of future outcomes.

Description: While intended to assist health plan actuaries responsible for stress testing and ORSA filings, this session will also be informative for actuaries interested in communicating the impact of potential catastrophic events for health plans to their management and board. It will begin with a discussion of event thresholds for stress tests and their impact on capital and financial statements. Presenters will take a detailed look at several catastrophic event case studies (historical and hypothetical) in the following areas: healthcare specific (e.g. pandemic, specialty Rx), financial institution/credit market, operational/business, strategic and multi-event scenarios.</

Description: This paper introduces a re-rating formula which calculates proposed rates directly by means of fully developed and trended loss costs and current class differentials. From 2007 Enterprise Risk Management Symposium, M-AS07-1.

Description: This paper demonstrates the use of Quantile Regression in the development and understanding of conditional value at risk (VaR) models for enterprise risk management.

Description: Increasing uncertainties and volatility in financial as well as real goods markets increasingly reveal that controlling systems based on deterministic and pseudo-exact values are insufficiently eligible to manage the business activities. This raises the question how management systems can be modified to generate the adequate management impulses in volatile periods. Risk management deals from identifying, evaluating and aggregating chances and risks, which again determine the potential fluctuation range of relevant performance indicators. Everyday corporate life shows that risk management is considered important; but the corresponding processes to identify, evaluate and report chances and risks are seldom part of established decision criteria. This “paradox” lets assume that risks are managed in various differing and unsystematic ways. The combination of traditional controlling methods and risk management is not primarily a methodological challenge. The behavior of the whole organization, practiced over a long-year period, has to be transferred into a new corporate culture of transparent dealing with chances and risks. This paper describes the necessary change management process, which has to come along with necessary methodological modifications.

Description: Abstract: 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.

Description: For the purposes of risk management and stress testing, we characterize a spectrum of plausible extreme events, that we dub Grey Swans, by introducing a probabilistic method involving the concentration of measure phenomenon. As a result, stress tests can be triaged according to severity, probability and, now, information-based plausibility.