The integration of artificial intelligence (AI) in banking systems has revolutionized financial services, enhancing efficiency while posing significant challenges to personal data protection and security. This study analyzes legal mechanisms safeguarding personal data in AI-driven banking environments, identifying regulatory gaps and proposing innovative solutions. Employing an interdisciplinary approach, including legal scholarship, financial technology research, and comparative regulatory analysis, the research examines algorithmic transparency, automated decision-making, cross-border data processing, and consumer protection. Findings reveal that traditional data protection laws are insufficient for addressing AI-specific risks, such as machine learning opacity and algorithmic bias. A comprehensive AI governance framework is proposed, balancing innovation with robust consumer safeguards through adaptive regulations, enhanced transparency, and accountability mechanisms. The study underscores the need for evolving legal frameworks to ensure trust, compliance, and fairness in AI-powered banking.