Due to their position in the Middle East, which are oil-producing nations, civil war, and political unrest, the police face various rates of crime in the United Arab Emirates (UAE). Much effort has been made to decrease police exposure in the UAE to operational risks. Policies have developed up-to-date work facilities and security technologies, which are supported by the government. However, police in the UAE face dilemma regarding operational risk involves poor management of service delivery, lack of sufficient equipment, and insufficient response to problems and oversight functions. This study provides an overview of the methods and potential future directions for risk management and reduction in the UAE's police operations. The study aims to examine the effects of governance, leadership, information technology, risk perception, and compliance with the organisational risk management of the UAE police in Dubai. Data were collected from Dubai Police Sector employees, which collected 435 questionnaires representing 5236 Dubai Police Force total population, and obtained 412 valid questionnaires. After confirming the validity and reliability of the latent variables with confirmatory and exploratory factor analyses, structural equation modelling Analysis of Moment Structures (Smart PLS) was used to test the hypothesis in Structural Equation Modelling (SEM). This study has shown that different operational risk factors significantly affect difference performance outcomes. Results revealed that the compliance, governance and risk awareness showed significant positive relationships with effective operational risk management, while leadership, information technology were rejected. On the other hands, compliance, Governance and Information Technology showed significant relationship with mediating of training, while leadership and risk awareness found not important. The results would also provide a basis for enhancing policing functions in the UAE in an exceedingly dynamic and fast-changing environment through an objective understanding of operational risk management paradigms. Future research could employ a mixed method (quantitative and qualitative) approach to address any problem of knowledge.