Operational Risk

Operational Risk is the risk of loss resulting from inadequate or failed internal processes, people, and systems, or from external events, but is better viewed as the risk arising from the execution of an Organization’s business functions (Basel Committee on Banking Supervision, 2004). Operational risk exists in every organization, regardless of size or complexity.

Operational risk is intrinsic to financial institutions and thus should be an important component of their firm-wide risk management systems. However, operational risk is harder to quantify and model than market and credit risks. Over the past few years, improvements in management information systems and computing technology have opened the way for improved operational risk measurement and management. Over the coming few years, financial institutions and their regulators will continue to develop their approaches for operational risk management and capital budgeting.

Measuring Operational Risk
A key component of risk management is measuring the size and scope of the firm’s risk exposures. As yet, however, there is no clearly established, single way to measure operational risk on a firm-wide basis. Instead, several approaches have been developed. An example is the “matrix” approach in which losses are categorized according to the type of event and the business line in which the event occurred. In this way, a bank can hope to identify which events have the most impact across the entire firm and which business practices are most susceptible to operational risk.

Once potential loss events and actual losses are defined, a bank can hope to analyze and perhaps even model their occurrence. Doing so requires constructing databases for monitoring such losses and creating risk indicators that summarize these data. Examples of such indicators are the number of failed transactions over a period of time and the frequency of staff turnover within a division.

Potential losses can be categorized broadly as arising from “high frequency, low impact” (HFLI) events, such as minor accounting errors or bank teller mistakes, and “low frequency, high impact” (LFHI) events, such as terrorist attacks or major fraud. Data on losses arising from HFLI events are generally available from a bank’s internal auditing systems. Hence, modeling and budgeting these expected future losses due to operational risk potentially could be done very accurately. However, LFHI events are uncommon and thus limit a single bank from having sufficient data for modeling purposes. For such events, a bank may need to supplement its data with that from other firms. Several private-sector initiatives along these lines already have been formed, such as the Global Operational Loss Database managed by the British Bankers’ Association.

Although quantitative analysis of operational risk is an important input to bank risk management systems, these risks cannot be reduced to pure statistical analysis. Hence, qualitative assessments, such as scenario analysis, will be an integral part of measuring a bank’s operational risks.