MODELING THE RESILIENCE OF EXPORT-IMPORT FLOWS IN THE ECONOMIC SECURITY SYSTEM OF THE REGIONS OF THE RUSSIAN FEDERATION

Amid geoeconomic risks and increasing external market volatility, there is a growing need to establish an adaptive monitoring system for the stability of exportimport flows across the regions of the Russian Federation, based on the use of digital and intelligent tools. The study substantiates the integration of economic and mathematical modeling methods and analytical platforms to enhance the system of economic security at the regional level. The models were adapted to account for regional heterogeneity, including demographic parameters, natural resource constraints, institutional conditions, and the level of infrastructure accessibility. The application of machine learning algorithms, regression analysis, and clustering enabled the identification of significant factors affecting key indicators of foreign economic activity (import, export, trade balance, and total turnover) and the construction of typologies of regional vulnerability and resilience. The developed digital analytics architecture reflects a transformation in the paradigm of managing exportimport risks and serves as a foundation for the development of intelligent decisionsupport systems in the field of economic security and strategic regional development planning.