THE DEVELOPMENT OF INTERNAL CONTROL IN TRADE: FROM CLASSICAL APPROACHES TO DIGITAL SOLUTIONS

Abstract

The article is devoted to a thorough study of the transformation of internal control systems in the context of digitalization of business processes, with a focus on the retail sector. The article argues that traditional control models, such as COSO and IIA standards, are not flexible enough and are not efficient enough to respond to the challenges of the digital age, in particular when processing large amounts of transactional data. In addition, modern technologies make it possible to move from fragmented control to continuous monitoring of operations in real time. In response to these challenges, the authors propose a conceptual model for integrating data flow analytics, anomaly detection algorithms, and robotic process automation (RPA) technologies to form a proactive internal control system capable of providing continuous monitoring and automated response in real time. Special attention is paid to the description of the mechanisms of flow analytics: from pattern identification to violation detection using statistical methods, machine learning, neural networks (including autoencoders and recurrent architectures) and complex event processing (CEP) algorithms. It is substantiated that the use of RPA significantly increases control productivity, providing automation of typical tasks - from evidence collection and data reconciliation to transaction blocking and reporting. The model proposed by the authors provides a five-level structure: data sources, analytical core, event dispatching, bot response and management dashboard. This approach allows real-time scanning of events, automatic response to typical risks and involving a human only in complex or atypical situations. Practical examples given in the article demonstrate that the integration of flow analytics and RPA can become not only a tool for fraud detection, but also an effective means of supporting operational efficiency in retail. The results obtained have practical significance for both internal audit practitioners and developers of digital solutions in the field of control and analytics.