A Systemic Approach Framework for Operational Risk : – SAFOR –
This thesis attempts to describe the essential systems features of a complex real-world domain of operational risk (OR) in banking, by employing general systems theory (GST) as the guiding method. An implementational framework (SAFOR) is presented for operational risk management (ORM), the target of which is to manage and mitigate the risk-around-loss causes. Since reasoning about OR is often scenario based, the framework also includes methods for decision making in addition to Value at Risk (VaR) and Conditional Value at Risk (CVaR). Other computational models that yield prediction intervals are discussed as well. Because the banking industry is one of the most mature sectors when it comes to OR, and contains the most data points, the discussion in this thesis evolves around such institutions. The present state-of-the-art in OR management for banking is surveyed using a systemic-holistic approach and the model framework is presented against this discussion. Tools and concepts from systems theory and systems thinking are employed for assessing systems properties and gaining insights into the interaction of various components. This brings about a number of advantages. This is not in disagreement with current suggestions such as those of the Basle Committee (Basel II), which is doing an excellent job in proving the state-of-the-art in best practice for banking institutions. Rather, this thesis offers a complementary perspective, looking at essentially the same problems but in a broader context and with a differing view.OR data has been hard to come by in banking. Confidentiality and difficulties in quantifying OR as well as the short time data has been gathered in a consistent way are some of the reasons for this. Therefore, no case study has been done. Instead, we have chosen to look into a published bank application of an advanced OR model. The application shows that the technique holds as validation of the SAFOR modules.
Source Type:Doctoral Dissertation
Keywords:SOCIAL SCIENCES; Statistics, computer and systems science; Informatics, computer and systems science; Computer and systems science; operational risk; systems thinking; decision analysis; interval forecasts; data- och systemvetenskap; Computer and Systems Sciences
Date of Publication:01/01/2007