Artificial Intelligence in Economics and Finance: Applications and Prospects of Machine Learning Methods

Abstract

In recent years, the rapid development of artificial intelligence technology has significantly advanced research innovations in the field of economics and finance. Particularly, machine learning methods, with their exceptional data processing and analytical capabilities, have been widely applied to areas such as predictive modeling, causal inference, and unstructured data analysis. This paper systematically examines the key differences between machine learning and traditional econometrics in terms of research paradigms, objectives, and data processing approaches. It provides an in-depth exploration of the application scenarios of machine learning in economics and finance, focusing on predictive modeling, alternative data analysis, and causal inference. Furthermore, it highlights the potential and breakthroughs of machine learning in addressing complex economic problems through specific case studies, demonstrating its practical effectiveness in macroeconomic forecasting, financial asset pricing, risk management, and policy analysis. In addition, this paper comprehensively analyzes the current challenges facing machine learning technology in economic and financial research, including issues of model transparency, difficulties in handling small sample sizes and noisy data, as well as data privacy concerns. Based on these challenges, several potential solutions are proposed, including the adoption of explainability tools, transfer learning, federated learning, and privacy-preserving computation. Future research directions are suggested, emphasizing the integration of multimodal data analysis, the exploration of large language models for policy and market analysis, and the deeper alignment of artificial intelligence technologies with industry practices. This study aims to provide theoretical guidance and practical insights for academia and industry, contributing to the advancement of research innovation and application expansion in the field of economics and finance.