Forecasting and Rating Financial Control in the Automotive Sector: A Data-Driven Evaluation Model

Abstract

The digitalization of the economy and the results achieved through artificial intelligence require the application of new approaches and tools by managers of commercial organizations within the overall financial management system. These are reflected in research expenditures. Auto manufacturing organizations are also free from such problems. The article aims to propose an integrated approach to the control of current financial requirements in automobile manufacturing companies listed on international stock exchanges within the context of artificial intelligence solutions. This is intended to serve as a new pathway for enhancing financial management through optimizing capital structure. This article presents an interrelated assessment of inventories, accounts receivable, and accounts payable in leading automobile manufacturing companies listed and studied in the global stock market by capitalization. Practical solutions for improving the control of current financial requirements have been proposed through structural changes in capital. The scientific novelty of this research lies in the development of control boundary intervals using a predictive model for the turnover (in days) of current financial requirements.