Description: List of published materials on the topic of enterprise risk management.

Description: The author will show that risk management is more than combining several processes and methods it is much more a company wide approach that enables an open dealing with chances and risks, requiring a change in culture, governance and decision rules across the whole organizations.

Description: Business transformation initiatives are undertaken by enterprises to reduce the risk of misalignment and to build agility and adaptability to market changes. The predictability of desired outcomes needs to be managed by mitigating interdependent risks associated with changes in processes, systems, operating procedures, employee and customer base, etc. This paper is about a strong risk management approach needed for minimizing the unpredictability associated with transformation-related initiatives. This proposed approach details a comprehensive model to measure enterprise risk management maturity by measuring its ability to identify risk, measure impact and define mitigation strategy. The model is further enhanced by provisioning for feedback to measure the effectiveness of mitigation and to ensure that outcomes are within desired limits. The intended audience of the paper is senior executives, business partners, program managers, project/track leads working with program organization groups, project management organizations [PMOs] and steering committees.

Description: In the current environment of global competition, the question of how much, and in what way, the enterprise risk management (ERM) function contributes to the creation of shareholder value will only increase in importance and urgency.

Description: The paper discusses the arguments supporting the need for risk culture to transition into ERM culture to be embedded across financial organizations. Creating and maintaining strong ERM culture is paramount to a lasting and meaningful ERM program. It is essential for organizations to understand what ERM culture is, how it gets established and in what way affects the process of ERM implementation. Often, the implications of financial enterprises not focusing on the significance of ERM culture manifested in severely compromised ability to generate sustainable value and market competitive advantage. This paper calls for rethinking the role of ERM culture in the context of managing risks.

Description: Obsolescence of physical assets and processes is a major component of operational risk for some companies. A simulation experiment shows that managers, who consider the retirement and replacement of individual assets in isolation, have rational incentives, due to risk aversion and uncertainty, to defer the replacement of assets past a time that is optimal from the perspective of the shareholder who owns the entire portfolio of such assets. This results in measurable wealth destruction, —and a demonstrable opportunity to significantly enhance a company’s value. A practical decision model for the replacement timing of fixed, physical assets, which creates wealth by minimizing the long-term consumption of scarce resources, is provided.

Description: Empirical evidence of reported losses suggests that insurance firms are interconnected in a nontrivial way, making them prone to systemic risk. Systemic risk can be viewed as the result of a cascading process, as it unravels throughout a network structure. In response, this work presents a simple analytical model that can simulate this process. The model is subsequently tested upon an empirical dataset via the means of numerical simulations. This work makes three main contributions. First, it provides a novel methodology for quantitatively and objectively assessing the systemic role of individual firms within the insurance domain. Second, it exemplifies the inability of traditional, firm-based information in serving as proxies for mapping these systemic effects. Third, it provides a practical example where network-based information (e.g., Criticality IDX, Sensitivity IDX) can outperform firm-based information (e.g., admissible assets, excess c apital) resulting in increased efficiency in the decision-making process. These findings strengthen the need to account for the interconnected nature of the domain while showcasing some of the potential benefits that can be harvested by doing so.

Description: Empirical evidence of reported losses suggests that insurance firms are interconnected in a nontrivial way, making them prone to systemic risk. Systemic risk can be viewed as the result of a cascading process, as it unravels throughout a network structure. In response, this work presents a simple analytical model that can simulate this process. The model is subsequently tested upon an empirical dataset via the means of numerical simulations. This work makes three main contributions. First, it provides a novel methodology for quantitatively and objectively assessing the systemic role of individual firms within the insurance domain. Second, it exemplifies the inability of traditional, firm-based information in serving as proxies for mapping these systemic effects. Third, it provides a practical example where network-based information (e.g., Criticality IDX, Sensitivity IDX) can outperform firm-based information (e.g., admissible assets, excess c apital) resulting in increased efficiency in the decision-making process. These findings strengthen the need to account for the interconnected nature of the domain while showcasing some of the potential benefits that can be harvested by doing so.

Description: People naturally observe risk in the form of the range of experienced gains and losses which is usually represented in statistical terms by standard deviation. In most cases, there are not enough observed values to reliably discern the true amount of losses that are possible in extreme situations. Statistical techniques that have long been applied to insurance company risks are being used to extrapolate from observed risk to extreme tails of the distribution of gains and losses. These processes are essentially an extrapolation from the “known” risk of volatility near the mean to “unknown” risk of extreme losses. “Fat tails” is a term often applied to risks where the likely losses in rare situations significantly exceeds the predictions of a Gaussian (“thin tailed”) distribution. This paper will look at the relationship between the observed risk and the extreme risk in statistical insurance r isk models and discuss how we might create a discussion among model users about the appropriateness of that relationship for specific types of risks.

Description: This essay examines the root causes of the 2008 global financial crisis precipitated by the bursting of the housing bubble. The author suggests that if fraud is not addressed, future crises, perhaps even worse, will occur.