Description: Feature article discussing the IASB’s and FASB’s introduction of the use of other comprehensive income (OCI) to report certain changes in the value of insurance contracts.

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

Description: The author recommends the use of "minimally destructive scenarios" as part of an ORSA process, in order to deal with cognitive bias that can occur in risk decision-making. Part of the essay collection "Risk Metrics for Decision Making and ORSA"

Description: In a very general setting this paper describes a straightforward, non-parametric approach to aggregate "stand-alone" or marginal distributions with desired correlations without imposing additional assumptions on those marginals. We then develop two optimizations for the enterprise, one based on maximizing return on economic capital and the other based on a mean -semivariance efficient frontier from the investor point of view.

Description: A sound enterprise risk management (ERM) framework functions as an ecosystem by balancing the interdependencies of its elements while constantly adapting to an ever‐changing, external environment. Each stakeholder has a unique role to play in forming a thriving ERM ecosystem by integrating risk‐conscientiousness in decision‐making. A resilient ERM framework has a single well‐ understood risk language and culture to promote healthy risk‐taking behaviors. The central focus of such a framework is concentrated around all stakeholders and everyone is held accountable. Every day, external forces can potentially disrupt how we operatively conduct business. Unforeseen changes in regulation, market trends, terrorist’s attacks and extreme natural disasters are often categorized as extremely adverse. How then will your ERM ecosystem survive the one‐in‐200 event and continue to flourish through dynamically changing environments?

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: Many top-performing businesses aren’t just risk aware, but rather risk intelligent. Such a posture helps prepare companies for a major event and can demonstrate to a regulator or auditor that an appropriately strong control framework is in place. Better still, companies gain real strategic value from a “risk adjusted” understanding not only of their threats and vulnerabilities, but also the upside opportunities associated with various risks. It starts with having both qualitative and quantitative information to identify, assess and manage risks. Strategic risk management, at its core, is about creating value by increasing transparency and accountability, and quality of information. More than a mere compliance exercise, effective risk management enables more informed strategic decision making, increased accountability and transparency, a greater likelihood of organizational success, and – ultimately – competitive advantage, as borne out by many studies that correlate risk management and financial results.

Description: The paper argues that Risks Evaluation at its core is a psychological process that can lead to the special type of chaos described in modern Chaos Theory. It will argue that quantification and scientific modeling does not exempt risk assessment from the potential for deep biases. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.