Methods of automating financial planning in the public sector

Vollständiger Abstract

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Subject. Transition of the public sector to results‑oriented budgeting and integration of intelligent financial planning systems. Objectives. To study modern methods of automating financial planning in the Russian public sector, to assess the effectiveness of technology platforms, and to identify systemic barriers to their full‑scale implementation. Methods. General scientific methods were applied: literature analysis, systematization, comparative analysis, and logical‑system analysis. Results. A paradox has been identified: despite a significant increase in operational efficiency (for example, the acceleration of contract payments to two days) and a tangible financial return from the use of AI (revenue exceeding 400 billion rubles from liquidity management in 2023), the systems operate with low data reliability. Audit data confirm widespread systemic inconsistencies in key information resources (for example, the GIIS “Electronic Budget”). This discrepancy leads to the faster execution of potentially erroneous decisions. The barriers include a legal vacuum regarding AI, a critical shortage of skilled personnel, and unresolved cybersecurity issues. Conclusions and Relevance. The implementation of automation methods requires measures to enhance the consistency of data aggregated in various budget accounting systems. Eliminating regulatory uncertainties and systemic contradictions will ensure an improvement in the quality of budget accounting and the reliability of financial planning. The results are advisable for use by public‑sector financial authorities to improve data consistency in budget accounting systems and to optimize control procedures.