The core of new quality productive forces lies in technological innovation and application, and artificial intelligence is the most effective means to forge new quality productive forces. With the rapid advancement of artificial intelligence technology, large language models have gained widespread attention in the financial industry. These models have shown significant potential in processing financial texts, predicting market trends, managing risks, executing algorithmic trading, and improving customer service, so as to promote the development of new quality productive forces. However, integrating these advanced technologies into the financial domain while ensuring data privacy, model interpretability, and accuracy poses numerous challenges. This article delves into the core principles, major challenges faced, most promising application scenarios, effective evaluation methods, key factors for successful implementation, strategies to address interpretability issues, the importance of maintaining data privacy and security, anticipated future development trends, and potential industry transformations of applying large language models in the financial sector. Through comprehensive analysis, this article provides guidance for financial institutions in utilizing large language models, also offering suggestions for future research directions.