Operational Risk Management : Team-Based Effort and Incentive Bonus

In this paper, we propose a general continuous-time stochastic-modeling framework where a financial firm offers incentive bonuses to a team of employees, who would thus exert effort to reduce operational risk losses. We characterize employees' Nash equilibrium efforts and the firm's optimal incentive bonus under this general framework. We find that employee effort may not always increase in the expected operational risk losses or incentive-bonus rate, and the effort decision is more complicated when risk-reduction efficiency increases in effort. Furthermore, given any incentive-bonus level, we characterize the region where the equilibrium effort leads to complete free riding (i.e., only the most efficient employee exerts effort), and thus the firm manager must carefully design the incentive bonus so as to reduce the free-rider effect. We then characterize the optimal incentive bonus to help reduce the free-rider effect. Finally, we conduct numerical experiments with an operational-risk dataset from our bank collaborator, and discuss the nonlinear incentive contract. We find the nonlinear contract is another way to reduce free-rider effect while motivating more employees to exert effort. In addition, when the risk is high, employees' efforts could be more divergent under the nonlinear contract. On a broader note, our work illustrates a general modeling framework to capture team-based effort and an incentive bonus toward risk mitigation