The rapid advancement of artificial intelligence (AI) has profoundly transformed financial trading, enhanced efficiency, accuracy, and customer service while introducing new challenges. This paper explores AI’s applications in quantitative trading, risk forecasting, and intelligent customer interactions, demonstrating its ability to optimize decision-making and reduce operational costs. However, the integration of AI also raises significant concerns, including data security risks, algorithmic opacity, and increased market volatility, as evidenced by incidents like the 2010 “Flash Crash” and recent AI-driven stock fluctuations. To address these challenges, the paper proposes strengthening data protection through advanced encryption and access controls, improving algorithmic transparency with Explainable AI (XAI), and enhancing regulatory frameworks to monitor high-frequency trading. By balancing technological innovation with robust risk management and policy support, the financial industry can harness AI’s potential while ensuring market stability. The study underscores the need for collaboration among financial institutions, technologists, and regulators to foster sustainable development in AI-driven financial markets.
Boyang Li (Thu,) studied this question.
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