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The transformation of the state financial control system in the context of the transition to technological sovereignty and the implementation of the national project «Digital Economy» is examined. The authors substantiate a paradigmatic shift from reactive methods of fixing violations to a model of predictive intelligent auditing based on machine learning technologies and deep semantic analysis. A comparative analysis of the experience of three leading jurisdictions (Brazil, Great Britain and China) was carried out, which made it possible to identify the effectiveness of intelligent scoring and interdepartmental data convergence. Based on the study of the fragmented architecture of domestic information systems – GIIS «Electronic Budget», EIS, ASK VAT-2 – the author’s four-stage concept of a single analytical forecasting platform is proposed. Special attention is paid to the mathematical justification of the risk vector based on data mining algorithms and the legal legitimization of AI conclusions through the introduction of principles of interpreted artificial intelligence.
state financial control, artificial intelligence, predictive analytics, Federal Treasury, digital transformation, economic security
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