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