Stress testing is an appealing risk-management tool because it provides the risk managers with additional information on possible portfolio losses arising from extreme, yet plausible events. In addition, stress scenarios can often become an effective communication tool within the bank and to the outside parties like the supervisor and depositors. It has assumed added significance in view of the ensuing implementation of BASEL II norms.

Risk management architecture in the financial sector has acquired paramount significance due to the increasing volumes and complexities of financial transactions. The banking sector, in particular, being highly leveraged and bearing fiduciary responsibility, is the most vulnerable to ever-expanding sources of potential risks. Surging volumes and a 360-degree integration in the financial sector have rendered the traditional methods of monitoring and managing risks useless. This has led to a global statistical revolution in risk management techniques over the past decade or so.

Increasingly, financial firms are relying on statistical models to measure and manage financial risks; ranging from market risks (such as, interest rate or exchange rate fluctuations), credit risks (such as, borrowers' default probabilities) to operational risks (such as, expected losses due to fraudulent transactions or system failures). Such models have gained credibility as they provide a coherent framework for identifying, analyzing and managing these risks.

However, most of such models are only stimulations of reality and cannot capture every aspect of these risks. Since, most fundamental basis of almost all quantitative models is `probability', such models constructed to monitor typical risk outcomes tend to focus on most probable events and do not capture the unlikely yet plausible events that could cause losses.

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