Managing Available Balances of the Single Treasury Account: The Need for Universal Service

Introduction. In the context of budget constraints and a highly volatile economic environment, managing balances in the Single Treasury Account (STA) is becoming not just a source of additional revenue but also a critical factor in the state’s financial stability. The existing state cash management system, having proven its effectiveness, faces institutional and technological barriers that hinder its further development. The main goal of this article is to explore the architecture of the “universal service” concept as an evolutionary development of the Single Treasury Window model, aimed at overcoming these barriers. Materials and Methods. The study is based on a systems approach. Critical and comparative analysis, a generalization of liquidity management practices, and elements of economic and mathematical modeling were used to substantiate the proposed solutions. The theoretical basis was an adapted Baumol-Tobin model, supplemented by principles of the Federal Treasury, the Russian Ministry of Finance, and an analysis of regional practices. Results. The architecture of the universal service concept proposed in the study was a logical continuation of the authors’ earlier publications, which proposed a Single Treasury Window model aimed at solving key problems that limit the effectiveness of state cash management. The architecture of the universal service includes four main modules: a single data portal, a forecast module for CEN balances based on AI, a placement optimization module and a digital risk audit module. Unlike existing models — such as the Miller-Orr model used to optimize cash balances or traditional treasury budget execution models — the proposed service involves adaptive customization for users with different levels of digital maturity. Conclusions. The proposed universal service architecture makes it possible to move from reactive liquidity management to proactive, based on predictive analytics and automated risk management. The implementation of the service will help reduce cash gaps, increase the transparency of management and generate additional income from the placement of temporarily free funds due to more accurate forecasting of CEN and the effective use of available financial instruments. Further research will be aimed at developing algorithms for the forecast module and assessing the economic effect of the service implementation.