Adversarial Robustness in Financial AI: Challenges and Implications

This ArXiv paper examines the critical issue of adversarial attacks on machine learning models within the financial domain, exploring defenses, economic consequences, and governance considerations. The study highlights the vulnerability of financial AI and the need for robust solutions to ensure system reliability and fairness.

• •Addresses the vulnerability of financial machine learning models to adversarial attacks.
• •Explores the economic and governance implications of these vulnerabilities.
• •Focuses on defenses aimed at improving the robustness of financial AI systems.