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人工智能增强金融系统:应用场景与发展趋势

Artificial Intelligence-Enhanced Financial Systems: Applications and Development Trends

  • 摘要: 人工智能在金融系统中具有广泛的应用场景并显著提高金融业的基础生产效率和劳动生产力。本文全面梳理人工智能在传统金融产业中的应用,包括人工智能赋能银行进行智能风控、智能投顾、智能获客、智能支付;在证券行业、保险行业以及私募、基金、投资等各行业均具有丰富的应用场景与应用需求。文章同时分析了生成式人工智能中的金融大模型如何重塑金融行业。作者认为生成式人工智能从整体上拉升基础服务素质,全面提升基础生产效率,减少低端生产线和服务业的投入,优化资源配置效率;降低冗余性和重复性劳动,提高劳动生产力。因此,金融行业由“金融+AI”正在向“AI+金融”的方向转型。此外,多模态、生成式的人工智能技术会进一步产生新的数据,促进金融领域新的研究方法向前迈进,由此引发金融这一复杂系统中的金融决策、资产定价等理论向前发展。

     

    Abstract: Artificial intelligence (AI) has broad applications in financial systems, significantly enhancing the fundamental productivity and labor efficiency of the financial industry. This article comprehensively reviews the applications of AI in traditional financial sectors, including its role in empowering banks with intelligent risk control, robo-advisory services, smart customer acquisition, and automated payment systems. Furthermore, AI demonstrates extensive application scenarios and demand in securities, insurance, private equity, funds, and investment industries. The article also provides an in-depth analysis of how generative AI, particularly large financial models, is reshaping the financial sector. This article argues that generative AI elevates the overall quality of foundational services, improves production efficiency, reduces reliance on low-end production lines and service labor, and optimizes resource allocation. By minimizing redundant and repetitive tasks, it enhances labor productivity. Consequently, the financial industry is transitioning from a “Finance + AI” model to an “AI + Finance” paradigm. Moreover, multimodal and generative AI technologies are expected to generate new data, advancing novel research methodologies in finance. This evolution will drive theoretical progress in financial decision-making, asset pricing, and other key areas within financial systems.

     

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