Features of modeling the financial activities of enterprises

Abstract

The development of economic and mathematical financial models enables the analysis of enterprises’ financial condition with sufficient accuracy and reliability, increases the efficiency of their activities, ensures financial equilibrium in the long term, and supports effective managerial decision-making.The purpose of this research is to conduct a comprehensive analysis of current methodological approaches to modeling the financial activities of enterprises while optimizing management processes in Ukraine’s business environment and to develop scientifically grounded recommendations for their implementation. The research methods include general scientific methods of abstraction, analysis, and synthesis. The results of the scientific research were obtained using both general and specialized research methods. The abstract-logical method of theoretical and factual generalizations was used to formulate conclusions and recommendations. The informational basis of the study consists of scientific works by Ukrainian scholars on the topic, as well as the authors’ own research results.The research results revealed that a financial model is a tool that helps manage the finances of an enterprise or project. With its help, one can understand how a business is developing, how to increase profits, and whether it is worth launching a new direction. The main advantage of a financial model was identified: it allows “testing” various scenarios without real risk. At the same time, the primary purpose of a financial model is to provide accurate analytical data on different situations that influence managerial decisions.The main categories of financial models and types of financial forecasting models were identified. A structure, key elements, and the main approaches and rules for building financial models were proposed. Conclusions.The use of financial models is an effective tool for enterprise development, as they contribute to the optimization of internal processes, improvement of decision-making, and cost reduction. The integration of automated financial modeling systems makes it possible to quickly process large volumes of data for more accurate forecasting and risk management in the face of modern challenges.