- 期刊
生成式人工智慧對金融場景的應用與挑戰
Application and Challenges of Generative Artificial Intelligence in Financial Scenarios
摘要
隨著技術的不斷進步和數據的爆炸性增長，金融行業正面臨著巨大的挑戰和機遇。傳統金融模式已經無法滿足快速變化的市場需求和複雜的風險管理要求。而人工智慧作為一種強大的技術工具，為金融行業的創新和發展提供了新的可能性。生成式人工智慧作為人工智慧在金融領域的重要應用之一，具有廣泛的應用前景和推動力。本文將重點研究生成式人工智慧在金融領域的應用情況，探討其對金融業務的影響和變革。本研究針對生成式人工智慧在金融領域的應用，以內容分析法兼具預測性和啓發性地探究金融場景的應用與挑戰，研究生成式人工智慧在金融行業中的優勢和潛力，旨在爲快速變化的金融市場提供清晰有條理的參考。本研究首先簡要闡述了生成式人工智慧的基礎概念、技術發展和應用，接著探討了企業和消費者的應用場景，然後轉移到市場參與者如何建立可持續商業模式的問題上，最後基於金融行業如何更好地應用生成式人工智慧內容，並利用生成式人工智慧技術改進金融業務，提出相應的對策建議。
並列摘要
With the continuous advancement of technology and the explosive growth of data, the financial industry is facing enormous challenges and opportunities. The traditional financial model is no longer able to meet the rapidly changing market demands and complex risk management requirements. Artificial intelligence, as a powerful technological tool, provides new possibilities for innovation and development in the financial industry. Generative artificial intelligence, as one of the important applications of artificial intelligence in the financial field, has broad application prospects and driving force. This article will focus on the application of generative artificial intelligence in the financial field, exploring its impact and transformation on financial business. This study focuses on the application of generative artificial intelligence in the financial field, using content analysis method to explore the application and challenges of financial scenarios with both predictability and inspiration. It studies the advantages and potential of generative artificial intelligence in the financial industry, aiming to provide clear and organized references for the rapidly changing financial market. This study first briefly elaborates on the basic concepts, technological development, and applications of generative artificial intelligence. Then, it explores the application scenarios of enterprises and consumers, and then shifts to the issue of how market participants can establish sustainable business models. Finally, based on how the financial industry can better apply the content of generative artificial intelligence, and use generative artificial intelligence technology to improve financial business, corresponding countermeasures and suggestions are proposed.