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: 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: Insurers can leverage information from their required Own Risk Solvency Assessment (ORSA) and use it internally to improve the likelihood of solvency and gain a competitive advantage.