employee
Sibirskiy Federal'nyy Universitet (Kafedra Ekonomicheskaya i finansovaya bezopasnost', docent)
employee from 01.01.2020 until now
Krasnoyarsk, Russian Federation
UDC 338.242
UDC 339.1
As the financial sector transitions to the T+1 settlement standard by 2026 and regulators implement the concept of evidence-based oversight, traditional compliance control systems focused on formal process assessment are losing their effectiveness. The speed of transaction cycles necessitates a transformation of metrics toward productiveness and real-time monitoring. The aim of this article is to develop a conceptual model for the transformation of compliance metrics, ensuring the integration of assessment and data quality into a unified management framework. The research in this paper is based on a comprehensive interdisciplinary approach, combining general scientific methods of deduction, induction, and abstraction with the tools of functional modeling and management design. The applied nature of the work necessitated the use of a group of specialized methods structured by research stages, including content analysis of regulatory acts and a tabular systematization method. The empirical base utilized international standards (ISO 37301:2021), regulatory reports (Bank of Russia, SEC), and analytics from leading consulting groups. As a result, a hierarchical model was proposed, the key element of which is a matrix of the sensitivity of key performance indicators (KEIs) to data quality (DQ) parameters. Unlike existing approaches, the model formalizes the causal relationship between data integrity and the reliability of compliance results. For practical implementation, a practical implementation toolkit was proposed in the form of a "Roadmap," which includes a responsibility assignment algorithm (RACI) and methods for overcoming typical organizational barriers.The proposed toolkit provides a methodological foundation for the implementation of intelligent compliance control systems, which helps minimize regulatory risks and ensures a high degree of automation of procedures. This allows organizations to move from reactively recording violations to proactively designing the resilience of their compliance systems.
compliance metrics, model, sensitivity matrix, data quality, performance indicators, roadmap
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