Collaboration Methods and Tools for Operational Risk Management

Over the past years, various methods and tools have been used by financial institutions (FIs) to support operational risk management (ORM) (Brink, 2002). ORM supports decision-makers to make informed decisions based on a systematic assessment of operational risks (Brink, 2003; Cumming & Hirtle, 2001). By the end of the 1990s many FIs increasingly focused their effort on ORM. This was mainly motivated by the volatility of today’s marketplace, costly catastrophes (e.g., Metallgesellshaft, Barings, Daiwa, Sumitomo, Enron, Worldcom) and regulatory-driven reforms such as the new Basel accord (Grinsven, Ale, & Leipoldt, 2006). The main benefits of ORM are improving performance, reducing operational losses, enabling a more efficient use and allocation of resources, preventing major business disasters, optimizing the allocation of capital, increasing the chance of success, improving decision-making and creating a shared understanding for Operational Risk (OR) (Brink, 2002). FIs often use loss data and expert judgment to estimate their exposure to operational risk (Brink, 2002; Cruz, 2002). Utilizing expert judgment is usually completed with more than one expert individually (often referred to as individual or self-assessments) or group-wise with more than one expert (often referred to as group-facilitated self-assessments). While individual self-assessments are currently the leading practice, the trend is more toward group-facilitated self-assessments. As a result, there is a need to support these group-facilitated assessments using e-collaboration methods and tools. However, there are a number of difficulties that financial institutions face which result in research issues that need to be bridged. The major difficulties are closely related to an effective, efficient and satisfying identification and estimation of the level of exposure to OR (Young et al., 1999). In this article, collaboration methods and tools are discussed for supporting multiple expert judgement utilized in ORM. We also present the main research issues. First, an overview of ORM will be provided by discussing the main phases of ORM. Second collaboration methods and tools are presented that can be used to support the multiple experts’ judgment and elicitation process and the role of experts is discussed. Finally research issues are discussed that need to be solved to leverage the full advantages of collaboration methods and tools as well as future developments.