ABSTRACT

The integration of Artificial Intelligence (AI) into the financial industry has witnessed significant growth, transitioning from an academic concept to widespread adoption in the industrial sector. This trend has given rise to various AI technologies, presenting both novel opportunities and potential risks within the financial landscape. In light of this development, the present research article aims to investigate the expanding role of AI in the financial sector, focusing on its applications and impact across financial products, channels, and service methodologies. To accomplish this objective, a specific AI algorithm called Support Vector Machine for Regression (SVR) has been selected for analysis. The SVR algorithm is particularly well-suited for small sample learning, making it an appropriate choice for examining trends in Shibor. By employing a combination of theoretical analysis, case studies, and risk assessment, this article contributes to fostering a profound and robust integration of AI and finance. Consequently, it delivers both theoretical insights and practical significance, offering valuable knowledge for industry practitioners and academic researchers alike.

摘要

人工智能（AI）与金融行业的融合取得了显着增长，从学术概念转变为工业领域的广泛采用。这一趋势催生了各种人工智能技术，在金融领域既带来了新的机遇，也带来了潜在的风险。鉴于这一发展，本研究文章旨在调查人工智能在金融领域不断扩大的作用，重点关注其在金融产品、渠道和服务方法方面的应用和影响。为了实现这一目标，选择了一种称为支持向量机回归（SVR）的特定人工智能算法进行分析。SVR 算法特别适合小样本学习，使其成为检查 Shibor 趋势的合适选择。本文结合理论分析、案例研究和风险评估，有助于促进人工智能与金融的深刻而稳健的融合。因此，它提供了理论见解和实践意义，为行业从业者和学术研究人员提供了宝贵的知识。