The Mechanism of Using Artificial Neural Networks in the Integration of Financial Accounting Systems and Their Impact on Improving the Efficiency of Budgeting

Abstract

This research aims to analyze the mechanism of using artificial neural networks in achieving integration between financial accounting systems, and to show the impact of this integration on improving the efficiency of budgeting in economic institutions. Contemporary accounting thought is witnessing an accelerated shift towards the adoption of artificial intelligence technologies as a supporting tool for decision-making, especially in light of the complexity of financial processes and the increasing volume of accounting data. Artificial neural networks are one of the most prominent of these technologies due to their high ability to self-learn and detect patterns that are not Linear, analyze historical data and predict future trends more accurately compared to traditional methods.

The research focuses on the role of artificial neural networks in supporting functional and information integration between financial accounting systems, by improving data quality, reducing accounting errors, and accelerating financial processing and aggregation processes.