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onal risk means giving an account of occurrences of loss experienced in the course of the business operations over a specific time-band (Parsley 2006). The reporting frequency and structure for reporting varies from organization to organization depending on their size and complexity of operations as also on the past trends.

In banking, the functional units such as branches are widely spread, especially in Indian Public Sector banking. On the top of this, there may be various layers in the bank such as Regional Authorities/Zonal Authorities, besides the Head Quarters (Luhmann 2002). Often major incidents such as frauds are also required to be reported to regulatory authorities immediately on occurrence/detection of any event of loss/potential loss.

Therefore, reporting of operational risk in banking needs to be compact and the reporting machinery is required to be so organized that reliability, accuracy, coupled with speed and consistently, is maintained on an ongoing basis. Technology is to be the key driver in the entire reporting system.

In this research, I have discussed the concepts of risk mapping and KRIs in operational risk management. I have examined the main objectives of these tools and proposed a general methodology to map operational risks to business activities and to select KRIs. I have shown how to apply the methodology to two specific, albeit rather stylized, business cases.

As automation and complexity in banking operations reach new heights, risk mapping is bound to take a central role both in business and in risk management. With the recent increase in scrutiny and pressure for tightening controls coming from regulators and legislators alike, the need for understanding, documenting and monitoring banking activities is becoming a major concern at top management level and is not anymore an exclusive endeavour for auditors and operations managers. Amongst all the control tools available to managers, KRIs have one clear advantage, if properly selected and interpreted: they are forward looking. They ideally complement statistical models, with their sophisticated analysis of past information, through a snapshot, imperfect and error-prone as it may be, of what might happen in the immediate future.

In activities where timing is always tight, consequences are swift and unforgiving, and where complexity often clouds the real mechanics of events, monitoring a set of well-identified KRIs can substantially enhance the effectiveness of risk management and substantially reduce operational exposures. A systematic, factor-driven analysis of processes, going from risk factors through failure and consequences of failures can help identify the most important indicators almost as a by-product of risk mapping.

Furthermore, a more holistic view of processes and risks can be achieved by considering a structured set of indicators as a means of drawing an overall picture of operational risk exposures. This bank-wide analysis can be implemented through the construction of an operational risk scorecard, summarizing, aggregating and reporting KRIs by business activity and risk category.

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