A SYSTEM FOR AUTOMATING DOCUMENT FLOW AND MONITORING ECONOMIC SECURITY INCIDENTS BASED ON ARTIFICIAL INTELLIGENCE TECHNOLOGIES
Abstract
Automation of document flow is a key element of process optimization and efficiency improvement. Automation of document flow based on artificial intelligence improves the management of economic security incidents by optimizing work processes and reducing costs. The transition to automated document flow in Russia is associated with a complex regulatory framework and large-scale implementation costs at enterprises. Automation helps to comply with legal requirements and reduces the risks of legal and financial consequences. Integration of digital signatures increases the efficiency of document approval. The implementation of automation systems supports national digital transformation goals. Automation of document flow reduces dependence on paper processes and facilitates the creation of centralized digital repositories. The implementation of document automation systems requires a strategic approach and careful planning. Document automation provides time savings, reduced errors and increased compliance with regulatory standards. The article discusses the theoretical foundations of BPM, integration of digital technologies and regulatory aspects specific to Russia. The proposed system combines monitoring with AI and IoT, provides real-time data processing, automates the creation of legal documents and reports. The workflow automation system is based on data integration, artificial intelligence technologies and seamless solutions. The system combines monitoring technologies, facial recognition and behavior analysis algorithms, a centralized database and a communication module. The system generates reports and legal documents certified by QES and ensures interaction with law enforcement agencies and security services. Implementation results: a 30–40% reduction in operating costs and a 50% reduction in losses. The system complies with digital transformation standards and supports the modernization of the national economy.
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