Research on the Application of Machine Learning Technology in Enterprise Intelligent Finance

Abstract

As the complexity of enterprise financial management environments and the volume of data surge, traditional financial analysis methods face significant challenges. Machine learning technology, with its powerful data processing and predictive capabilities, is becoming an essential tool to address these challenges. This paper aims to explore the application of machine learning technology in intelligent finance for enterprises, covering areas such as budgeting and forecasting, risk management, automated financial reporting, and fraud detection. By summarizing the basic concepts and commonly used algorithms of machine learning, and analyzing the needs of intelligent finance, this paper discusses how machine learning can enhance the accuracy and efficiency of financial decision-making. Additionally, through case studies, the paper analyzes key factors for successful applications and the challenges faced. The paper also discusses the obstacles to implementing machine learning in enterprise financial management and offers future development trends and optimization suggestions. The research indicates that while machine learning technology has significant potential applications, enterprises must overcome issues such as data quality and algorithm limitations to achieve optimal intelligent financial outcomes.