Core Insights - The financial industry's digital transformation is accelerating, with data becoming the core driver of change, reshaping financial services and their boundaries [1][2] - Digital finance is viewed as the "new infrastructure" of finance, supporting key areas such as inclusive finance, green finance, and technology finance [2][4] - The development of digital finance requires a robust organizational structure and strategic alignment to adapt to business needs [3][4] Data as the Foundation - Data is recognized as the fundamental element of digital finance, essential for the digital transformation of various financial sectors [2][3] - The industry is moving from conceptual discussions to practical implementations, emphasizing the importance of data in driving financial innovation [2][4] Organizational Structure - The organization of CITIC Baixin Bank includes a Digital Finance Promotion Committee and an AI Innovation Application Committee to ensure strategic alignment and focus on technology innovation [3][4] - The bank aims to create a strong data and technology platform to enhance resource efficiency and support frontline business needs [3][4] AI Model Applications - The application of AI models in finance is still developing, with a focus on creating tailored versions for specific financial needs [5][6] - AI models have shown significant efficiency improvements in tasks such as anti-money laundering, where they can process large volumes of data much faster than manual methods [5][6] Customer Interaction Transformation - The evolution of customer interaction is moving towards a "one-sentence bank" model, allowing customers to express needs simply and receive tailored services [7][8] - The bank is leveraging AI to enhance customer service experiences, making interactions more intuitive and efficient [7][8] Balancing Innovation and Foundation - Emphasis is placed on the importance of foundational data work, which is critical for enabling innovation in AI applications [9][10] - The bank advocates for a balanced approach to innovation, ensuring that foundational data practices are solid before pursuing advanced applications [9][10] AI Governance - AI governance is a complex issue that requires balancing regulation and innovation, with a focus on establishing clear boundaries and responsibilities [10] - The industry is encouraged to develop self-regulatory frameworks to address ethical and legal challenges associated with AI technology [10]
中信百信银行首席数字官陈龙强：数据要素驱动服务变革 先做数据“细活” 再求服务“质变”
2 1 Shi Ji Jing Ji Bao Dao·2025-08-20 22:38