Systemic-integrative approach to forming a bank's competitive strategy in conditions of market uncertainty

Abstract

Amidst global geopolitical turbulence and wartime challenges, the Ukrainian banking sector is facing an unprecedented level of uncertainty that requires fundamental changes to strategic management approaches. This study focuses on the processes involved in forming and implementing a commercial bank's competitive strategy. The key characteristics of this process are the dynamism of the external environment, aggressive competition and the volatility of the resource base.

Problem statement. The main issue examined is the inadequacy of traditional static planning models in the context of ongoing crisis phenomena. Banks require dynamic decision support systems that can adapt management parameters (specifically interest rates) in real time in response to structural market shifts and competitor actions.

Unresolved aspects of the problem. Despite existing research, the issue of creating a comprehensive model that directly integrates the dynamic clustering of the competitive environment with game-theoretic pricing decision optimisation remains unresolved. Existing approaches often ignore nonlinear feedback loops and time lags in customer reactions to rate changes.

Purpose of the article. The paper aims to develop and substantiate a scientific model for a commercial bank's competitive strategy, combining system dynamics, multidimensional statistical analysis and game theory to ensure financial stability and maximise profit.

Presentation of the main material. The article presents a conceptual model architecture that has been implemented in a simulation environment (Vensim/Simulink). This architecture includes blocks for monitoring the external environment, forming base volumes of assets and liabilities, and simulating competitor actions. Dynamic clustering methods are applied to identify the relevant competitor group. A dynamic modification of the Monti-Klein model is developed that takes into account demand inertia (time lags) and liquidity constraints. The guaranteed result principle (min-max saddle point search) is employed to determine optimal interest rates.

Conclusions. The simulation results prove that the proposed approach enables the bank to reach a dynamic equilibrium point, thereby ensuring the maximisation of net interest income, even in the face of aggressive competitor countermeasures. The practical value of this work lies in equipping management with the tools necessary for transitioning from a reactive to a proactive approach to market position management.