Regulatory whitelist mechanisms in financial monitoring and state financial security

Abstract

This article develops a regulatory model for implementing whitelist mechanisms in financial monitoring as an instrument of state financial security under conditions of digitalization and algorithmic transaction control. The study focuses on false-positive blocking of legitimate and legally mandatory transactions, especially public-law payments whose recipient, purpose, and legal basis can be verified through authoritative data. The methodology combines systemic, comparative, structural-functional, institutional, and conceptual modelling approaches. The article defines false-positive blocking as an automated or semi-automated high-risk classification or suspension of a financial transaction that is subsequently confirmed as legitimate on the basis of its legal nature, verified recipient status, payment purpose, customer due diligence data, or post-audit review. The study identifies the principal mechanism of such errors as a mismatch between behavioral risk indicators and the legal classification of transactions. It argues that large amounts, unusual frequency, atypical geography, new recipients, or customer- profile mismatches are not causes of illegitimacy in themselves, but risk indicators that may generate false-positive decisions when legal-context validation is absent. Based on this mechanism, the article proposes a three-level regulatory model consisting of institutional, informational, and algorithmic components: a centralized registry of verified public-law payment recipients, dual validation of risk and legal classification, real-time pre-blocking validation, low-risk eligibility testing, audit logging, human-in-the-loop review, and post-audit safeguards. The whitelist mechanism is not treated as an exemption from AML/CFT monitoring; rather, it functions as a validated processing regime for transactions that meet independent eligibility criteria and contain no critical risk flags. The proposed model is designed to reduce unjustified automatic blocking, preserve the continuity of state financial flows, and strengthen the explainability, proportionality, and accountability of algorithmic financial monitoring.