With the wider use of AI and big data in banking, model risk management faces new challenges and opportunities. This paper explores strategies for using technology to enhance model risk management. Findings show that bank models are now core to decision-making, but issues remain in explainability, data governance, and lifecycle management. Building a full lifecycle management platform, improving data governance, using explainable AI, and creating human-AI risk control systems can significantly enhance control over model risks. This study provides a framework for banks to innovate safely and achieve sustainable growth.