ECONOMIC SECURITY AT THE STATE LEVEL: PREVENTING FINANCIAL CRISES

Abstract

In the context of increasing global instability, high volatility of world markets and increased competition in the field of technology, the problem of ensuring the economic security of the state naturally comes to the fore as one of the key strategic tasks of the 21st century. The article analyzes the mechanisms for preventing financial crises, which are considered not as a separate management unit, but as an integral part of the national security system architecture. Special attention is paid to the analysis of the vulnerabilities of the Russian economy in 2023-2024. The key risks include continued high dependence on commodity exports, sustained inflationary pressures, deepening demographic imbalances, and technological isolation caused by limited access to critical import solutions. Based on up–to-date statistical data, an attempt is being made not only to record the current state, but also to assess the potential of the Russian economic system to adapt to external economic shocks, from sanctions pressure to disruptions in global logistics and financial chains. The focus is on the key technological and institutional components of the modern digital architecture of economic security. These include the creation of national platforms for interdepartmental monitoring that ensure the rapid collection and processing of economically significant information; the development and implementation of digital counterparts of the economy that function as virtual testing grounds for modeling development scenarios in the face of various internal and external shocks; the formation of cyber resilience systems designed to protect critical infrastructure from digital threats.; as well as the deployment of early warning analytical modules capable of detecting weak instability signals before they enter the crisis phase. Special attention is paid to the use of artificial intelligence algorithms and big data analysis tools that allow not only to assess risks, but also to build multi-level predictive models covering a wide range of macro- and microeconomic processes.