ADAPTIVE-PREDICTIVE MODEL OF FINANCIAL MANAGEMENT OF ENTERPRISES UNDER CONDITIONS OF A DYNAMIC ENVIRONMENT

Abstract

The article presents a scientific justification and structural development of an adaptive-predictive model of enterprise financial management that responds to the challenges of today's dynamic environment. Increasing macroeconomic instability, market fluctuations, technological shifts, and digitalization require a revision of traditional approaches to financial management, which no longer provide the necessary flexibility and responsiveness. In this context, it becomes essential to combine adaptation mechanisms with forecasting tools, enabling enterprises not only to respond to changes but also to anticipate them by building a proactive financial policy. The adaptive-predictive model proposed in the study comprises three interrelated functional blocks: the environmental monitoring block, the forecasting analytics block, and the adaptive management block. The first block ensures systematic collection and analysis of external (macroeconomic, market) and internal (operational, reporting) data. The second block generates multi-scenario forecasts of financial indicators using digital technologies such as Business Intelligence systems, artificial intelligence, and machine learning methods. The third block implements adaptive mechanisms—budget adjustments, resource reallocation, cost optimization—based on projected environmental changes and key financial risks. A central element of this model is a digital platform that integrates analytical and management processes into a unified information system. Implementation of this model allows enterprises to build a dynamic financial management system capable of rapid response to changes, improving planning accuracy, reducing risks, and enhancing the overall effectiveness of financial decision-making. The proposed concept has practical value for enterprises across various industries aiming to strengthen their financial resilience and competitiveness in an unstable economic environment. The study results may also be useful in managerial consulting, digital financial system design, and strategic planning.