銀行服務業應對生成式人工智慧技術的創新策略與應用展望 --以玉山商業銀行為例

Abstract

金融科技為銀行帶來了方便以及創新驅動力，改善服務流程以及營運效率。然而，當新科技在社會中出現並擴散時，銀行必須考驗自身的科技創新模式與組織文化接納度，以能夠快速應對和運用這些技術。隨著ChatGPT引發的生成式人工智慧應用風潮，各大產業都在熱烈討論如何將相關技術應用於商業中。然而，由於金融業需要考慮安全性和監管要求，對於相關應用的討論並不如其他產業般熱烈。 本研究透過搜集國內外金融業對生成式人工智慧的態度與應用相關報導與專文，以了解業界對該技術的應用期望和風險態度。同時，採用創新擴散理論架構分析生成式人工智慧所具備的創新特質，以評估其在銀行服務業中擴散的速度，並了解各銀行在技術生命週期中所扮演的採用者角色。接著本研究運用個案分析法，深入了解玉山商業銀行在金融科技與人工智慧領域的科技管理模式。透過與相關科技策略和技術人員進行深度訪談，研究掌握了玉山銀行對生成式人工智慧的創新態度和應用潛力看法。 經由文獻搜集和訪談整理，本研究歸納出生成式人工智慧在銀行業的應用潛力，並發現該技術在銀行業中的傳播速度應屬中等，主要考慮到目前銀行的數位轉型趨勢和風險控制機制。大多數銀行被歸類為接近晚期大眾的類別，對於新科技持謹慎和保守的態度。然而，個案公司玉山商業銀行運用自身的科技創新模式，早期對該新技術進行探索和認識，具有早期接受者的特點。 最後，本研究針對金融創新模式提出相關建議，並認為未來銀行人才需要跨領域、跨專業的協作模式，以應對新科技帶來的衝擊和挑戰。

Financial technology has brought convenience and innovation to banks, improving service processes and operational efficiency. However, as innovative technologies emerge and spread in society, banks must evaluate their own technology innovation modes and organizational culture adaptability in order to quickly respond to and utilize these technologies. With the rise of the application trend of generative artificial intelligence sparked by ChatGPT, industries are actively discussing how to apply such technologies in business. However, due to the security and regulatory considerations in the financial industry, the discussion of these applications is not as fervent as in other industries. This study aims to understand the attitudes and application of the financial industry towards generative artificial intelligence by collecting relevant reports and articles from domestic and international sources. Additionally, the study employs the framework of diffusion of innovation Theory to analyze the innovative characteristics of generative artificial intelligence (GAI), evaluate its diffusion speed in the banking service industry, and understand the roles played by different banks as adopters in the technology life cycle. Subsequently, a case study approach is employed to gain in-depth understanding of the technological management model of E.Sun Commercial Bank in the field of financial technology and artificial intelligence. Through in-depth interviews with relevant technology strategists and technical personnel, the study grasps the bank's innovative attitudes and potential applications of generative artificial intelligence. Through literature collection and interview analysis, this study summarizes the potential applications of generative artificial intelligence in the banking industry and finds that the diffusion speed of this technology in the banking industry is moderate, primarily considering the current digital transformation trends and risk control mechanisms of banks. Most banks are categorized as late adopters, holding cautious and conservative attitudes towards innovative technologies. However, the case company, E.Sun Commercial Bank, demonstrates early adopter characteristics by utilizing its own technology innovation mode to explore and understand this new technology at an early stage. Finally, this study proposes relevant recommendations for financial innovation modes and believes that future banking talents need to adopt a cross-disciplinary, cross-professional collaborative approach to cope with the impact and challenges brought by new technologies.