A system dynamics approach to operational risk loss reporting policy in banks

The purpose of the study is to understand the interrelationships between operational risk management (ORM) activities and evaluate the impact of the operational risk loss reporting policy on the behavior and performance of ORM in banks. The study employed case study research to investigate the real-life context of ORM in banks. Five Thai commercial banks with different sizes, capital adequacy levels, and ownership structures were purposively selected to reflect the diverse characteristics found in the Thai banking market.System dynamics (SD) was used in developing the ORM models that capture the real-life structure and dynamics within the ORM system. The simulation model facilitated the assessment of ORM behavior and performance across banks. The robustness of the models was enhanced through the validation process of the model structure, behavior, and policy implications under both normal and extreme conditions.Empirical evidence from the study indicates that the operational risk loss reporting policy contribute to the data problem in the field of ORM in banks. Specifically, an increase in the levels of the loss reporting threshold causes a decrease in the frequency of loss reports. The study also found that the settings on operational risk loss report policy affect the ORM behaviors and performances of banks, regardless of their sizes, levels of capital adequacy, and types of ownership structures.While a majority of ORM studies within the banking discipline predominantly concentrate on developing measurement models to address capital adequacy requirements, this study adopted a systems perspective, an interdisciplinary approach, to investigate the complex and dynamic ORM system. The SD ORM models are among the first models that represent the real ORM system. They potentially serve as foundational models of future studies, particularly those focusing on dynamic performance measurement systems. They also serve as a managerial tool for bank management to evaluate real-life ORM behavior and effectiveness. Furthermore, the findings of the study contribute to discussions on a data issue and factors influencing ORM behaviors in banks. The empirical evidence of the study supports the bank management in promoting a culture of transparency in reporting operational risk losses. This transparency facilitates the transition from “unknown” to “known” operational risk.