大语言模型在金融端的应用原理、挑战及落地路径研究

Research on Application Principles,Challenges,and Implementation Path of Large Language Models in the Financial Sector

新质生产力的核心是技术创新与应用,人工智能是铸造新质生产力最有效的手段,随着人工智能技术的快速进步,大语言模型在金融行业的应用引起了广泛的关注。这些模型在处理金融文本、预测市场趋势、管理风险、执行算法交易以及改善客户服务等方面展现了显著的潜力,助力新质生产力发展。尽管如此,要将这些先进技术融入金融领域,同时确保数据隐私、模型的解释性和准确性仍然存在诸多挑战。文章深入探讨了大语言模型在金融领域应用的核心原理、面临的主要挑战、最具潜力的应用场景、有效的效果评估方法、关键的落地实施因素、解决可解释性问题的策略、维护数据隐私和安全的重要性,以及预期的未来发展趋势和可能带来的行业变革。通过全面的分析,为金融机构利用大语言模型提供指导,同时为未来的研究方向提出建议。

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 advance-ment of artificial intelligence technology,large language models have gained widespread attention in the finan-cial 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 de-velopment 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 arti-cle delves into the core principles,major challenges faced,most promising application scenarios,effective eval-uation methods,key factors for successful implementation,strategies to address interpretability issues,the im-portance 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.