Description: This is a web page containing links to papers presented at the Retirement 20/20 conference held in Washington, D.C. on November 17 & 18, 2008.

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: Contemporary ERM has moved from an event-based view of risk to a hierarchical, systems-based approach. In order to operationalize such an approach, a methodology is proposed in this paper that draws on phylogenetic approaches that have been successfully developed for biological evolution. The technique and process provide an insight into the lineage, pace and impact of external conditions on the evolution of risks. They also provide a unique and rational classification of risk in an enterprise that can be used to optimize risk management resources. An example of a fictitious insurance company is used to illustrate the approach. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: This article is a summary of the authors’ two other articles where they discuss pension systems and whether they do in fact distort retirement decisions.

Description: We employ a framework for the classification of mortality evolution patterns to HMD data. We find both supra-regional patterns and outliers from global trends.

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: Global financial crises like the one recently experienced, affected both large and small institutions.Today, when there is heightened need for enhanced risk management tools, some entities are unable to employ sophisticated mechanisms due to limited data availability. Moreover, from the Basel Committee on Banking Supervision’s point of view via Basel II and Basel III, the internal ratings- based (IRB) approach requires that institutions have some reliable estimates of default probabilities of default for each rating grade. Taking the work of previous researches a step further, this paper intends to propose a new dynamic mechanism to for the risk management industry for to calculateing probabilities of default (PD). Through these estimates for the core model, we generate implied probability of default (PD) through actuarial estimation tools and different probability distributions. This mechanism is specialized to work best for low- defa ult portfolios (LDPs). Furthermore, scenario testing is adopted to validate the model against any model- specific bias

Description: This paper talks about the Swedish pension system reform.

Description: We apply grouped functional time series forecasting methods to produce point forecasts of mortality rates at older ages and price fixed-term annuities.

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.