The Adaptive Money Flow Management of Banks in the Era of Uncertainty and Risk
Kochorba V. Y., Kolomiiets Y. Y.

Kochorba, Valeriia Yu., and Kolomiiets, Yuliia Yu. (2025) “The Adaptive Money Flow Management of Banks in the Era of Uncertainty and Risk.” The Problems of Economy 4:362–372.
https://doi.org/10.32983/2222-0712-2025-4-362-372

Section: Finance and banking

UDC 336.71:004.8

Abstract:
The study focuses on the development of adaptive money flow management scenarios for a commercial bank, integrated into the risk management system. The need to transition from reactive to proactive and adaptive money flow management is substantiated by sharp liquidity fluctuations, an increase in non-performing assets, and stricter requirements from the NBU for stress-testing and recovery planning. The aim of the article is to develop theoretical and methodological foundations and practical recommendations for creating flexible, multi-level money flow management scenarios capable of dynamically responding to changes in the risk environment. To achieve this aim, the article proposes a conceptual three-dimensional model of adaptive money flow management, which integrates the following components: key scenarios, dynamic models, and risk minimization strategies. As part of the study, a multi-level classification of risk events was developed across three main directions with clearly defined triggers for activating the corresponding management level; a simulation model of the bank’s money flows was created based on the system dynamics methodology, which quantitatively describes the interactions between key indicators and financial outcomes, allowing for the assessment of the impact of endogenous and exogenous factors. The simulation results demonstrated the bank’s profit is critically sensitive to increases in deposit interest rates, emphasizing the importance of finely tuning the passive policy. It was also found that proactive management of lending rates is an efficient tool for restoring financial balance. Detailed, scenario-based risk mitigation strategies were developed. They include recommendations on diversifying liabilities, implementing AI/ML models for proactive scoring and customer monitoring, and optimizing the maturity of assets and liabilities to reduce the structural liquidity gap. Implementing the proposed scenarios will enable the bank to operate proactively and sustainably, improve the accuracy of liquidity forecasts, and enhance capital efficiency under conditions of systemic uncertainty.

Keywords: money flows, risk management, adaptive scenarios, simulation modeling, system dynamics, financial stability, liquidity.

Fig.: 11. Tabl.: 5. Bibl.: 9.

Kochorba Valeriia Yu. – Candidate of Sciences (Economics), Associate Professor, Deputy Director, Educational and Scientific Institute «Karazin Banking Institute» of V. N. Karazin Kharkiv National University (55 Peremohy Ave., Kharkiv, 61174, Ukraine)
Email: V.y.kochorba@karazin.ua
Kolomiiets Yuliia Yu. – Applicant, Department of Finance, Banking and Insurance, V. N. Karazin Kharkiv National University (4 Svobody Square, Kharkіv, 61022, Ukraine)
Email: yuliya.kolomiiets@student.karazin.ua

List of references in article

Ali R. (2025, February 19). The 8 top data challenges in financial services with solutions. NetSuite. https://www.netsuite.com/portal/resource/articles/financial-management/data-challenges-financial-services.shtml
Borysova L. Ye. & Volkova M. S. (2024). Upravlinnia bankivskymy ryzykamy v umovakh voiennoho stanu v Ukraini [Banking risk management under martial law in Ukraine]. Ekonomika ta suspilstvo, 67. https://doi.org/10.32782/2524-0072/2024-67-113
Farion V., Homotiuk A. & Turchyn S. (2024). Vykorystannia shtuchnoho intelektu dlia prohnozuvannia finansovykh pokaznykiv [Using artificial intelligence to forecast financial indicators]. Ekonomichnyi analiz, 34 (2). https://doi.org/10.32782/2524-0072/2025-72-35
Peshko M. I. & Melnyk O. H. (2025). Upravlinnia ryzykamy v IT-haluzi v umovakh tsyfrovizatsii ekonomichnykh system [Risk management in the IT industry in the conditions of digitalization of economic systems]. Problemy ekonomiky, 1 (63). https://doi.org/10.32983/2222-0712-2025-1-193-198
Romanieiev O. (2025). Upravlinnia likvidnistiu [Liquidity management]. Fondexx. https://fondexx.com.ua/blog/upravlinnya-likvidnistyu
Sliusarenko Ye. R. (2024). Upravlinnia problemnymy aktyvamy bankiv u konteksti nadzvychainykh vyklykiv ta zahroz v Ukraini [Management of non-performing assets of banks in the context of extraordinary challenges and threats in Ukraine]. Investytsii praktyka ta dosvid, 14. https://doi.org/10.32702/2306-6814.2024.14.177
Sterman Dzh. (2000). Business Dynamics Systems Thinking and Modeling for a Complex World Int’l Ed. McGraw Hill. https://www.researchgate.net/publication/44827001_Business_Dynamics_System_Thinking_and_Modeling_for_a_Complex_World
Vit D., Stelmashenko Ya. V. & Faryna O. I. (2013). Systemno-dynamichni modeli osnovni etapy pobudovy modelei systemnoi dynamiky z vykorystanniam prohramnoho paketa Think 10 : praktychnyi posibnyk dlia roboty z systemnoiu dynamikoiu v kompiuternomu klasi [System-dynamic models main stages of building system dynamics models using the Think 10 software package: a practical guide for working with system dynamics in a computer class]. Kyiv. https://ekmair.ukma.edu.ua/handle/123456789/9078
Yaroshevska O. V. & Orlov M. S. (2023). Systemnyi pidkhid do stres testuvannia bankivskykh ryzykiv [System approach to stress testing of banking risks]. Problemy systemnoho pidkhodu v ekonomitsi, 3 (92). https://doi.org/10.32782/2520-2200/2023-3-18