The Role of Intelligent Data Processing in Optimizing Companies’ Financial Efficiency

The relevance of the research lies in the increasing need for the use of intelligent data processing (IDP) to increase the financial efficiency of a business in conditions of economic instability. The development of artificial intelligence and machine learning allows organizations to effectively manage risks, optimize internal processes, and improve the accuracy of financial forecasting. The purpose of the research is to assess the impact of intelligent data processing on the financial efficiency of a business, identify key problems and propose solutions. To achieve this goal, a review of the literature was conducted, methods for optimizing business processes were identified, barriers to the introduction of IDP and prospects for its application were identified. The research methods include comparative, systematic and statistical analysis. The use of these methods allowed us to deeply explore the problem of implementing IDP in real business cases. The results of the study confirm that intelligent data processing significantly increases the financial efficiency of companies. However, the implementation of IDP is fraught with a number of problems, such as the need for additional investments, restructuring of business processes and ensuring staff qualifications. Despite the difficulties, the introduction of IDP allows companies to significantly increase their competitiveness and profitability. The conclusion of the research emphasizes that intelligent data processing in the modern economy is an important tool for improving the financial stability and competitiveness of businesses. With well-organized implementation, IDP helps optimize processes, improve forecasting and risk management, which leads to improved financial results.