Operational risk is now among the three most significant types of risks in the financial services industry, and its management is mandated by Basel II regulation. This paper studies how bank operational risk event frequency (or error rate) and severity (potential losses) are affected by workload to inform better labor decisions. To achieve this goal, we use a unique operational risk event data set from a commercial bank in China that contains 1,441 operational risk events in two years. We find that workload has a U-shaped impact on operational risk frequency. More specifically, the error rate of operational risk events would decrease first as workload increases and then increase. In addition, we show that workload has an inverted-U shaped impact on bank profit. Based on the causal relationships between workload and operational risk events and profit, respectively, we discuss bank capital allocation impact of changing the staffing level among branches so as to reduce operational risk losses and improve profit. We compare our optimal staffing policy with bank’s original policy, and estimate that the new staffing policy would reduce the current number of employees by 7.56%, which would further decrease the number of risk events by 4.51%, cut the total losses by 4.58%, and increase profits by 1.24%.
|Name||SMU Cox School of Business Research Paper|
- Operational Risk
- Capital Allocation
- Optimal Staffing