Deep Learning in Finance Review: Opportunities, Challenges, and Future Directions
Xiaoquan Liu
Shanghai University of Finance and Economics
DOI: https://doi.org/10.59429/bam.v6i3.7370
Keywords: deep learning; financial sector; AI-driven finance application
Abstract
This comprehensive review examines the transformative impact of deep learning on the financial sector, exploring its applications, potential, and challenges. We analyze cutting-edge advancements in financial prediction, risk management, and asset pricing, highlighting deep learning’s superiority over traditional methods. The paper investigates innovative applications in financial democratization, systemic risk assessment, and regulatory technology. We critically discuss challenges including model interpretability, data privacy, and algorithmic bias. A “Responsible Financial AI” framework is proposed to guide the ethical development of deep learning in finance. This study offers significant implications for financial institutions, regulators, and academia, providing a roadmap for the future of AI-driven finance.
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