1月26日，亚洲金融论坛在香港举行。在数智金融发展与创新分论坛上，香港财经事务及库务局常务秘书长甄美薇在发言中表示，作为全球领先的国际金融 中心，香港展现了其强劲的发展韧性与独特优势。 据甄美薇介绍，在最新全球金融中心指数中，香港位列全球第三、亚太第一，其中金融科技领域排名更是跃居世界首位。市场数据同样亮眼，2025年香港 IPO募资额达285亿美元，较上年大幅增长225%，重夺全球IPO募资额榜首宝座；股市平均每日成交额接近2500亿港元，较2024年增幅高达90%。这一系列亮 眼成绩，充分印证了香港金融市场在复杂环境下依然保持着充足的流动性与广阔的市场广度，彰显了其作为国际资本融通枢纽的核心地位。 在人工智能金融应用领域，香港同样走在前列。2024年10月，香港特区政府发布《金融市场负责任应用人工智能政策声明》，为AI在金融领域的合规应用 指明方向。香港金融管理局分别于2024年8月及2025年4月推出两轮生成式人工智能试点计划，为银行提供了风险可控的框架，助力银行业以负责任的方式测 试AI应用场景，实现创新与风险防控的平衡。 甄美薇强调，金融稳定是金融市场发展与创新的核心前提，香港将持续依托"一国两制" ...

Group 1 - The core viewpoint emphasizes the mutual empowerment of artificial intelligence (AI) and finance, which is a necessary outcome of the development of both sectors, providing strong support for their high-quality growth [1] - The People's Bank of China aims to promote the application of AI in finance in a proactive, stable, safe, and orderly manner, highlighting the need for institutional support and overcoming technical bottlenecks [1][2] - The development of AI in finance should focus on real demands from the real economy, ensuring deep integration of technological innovation with business scenarios [1] Group 2 - The top-level design includes the issuance of the "Opinions on Deepening the Implementation of 'Artificial Intelligence+' Action" in August 2025, which sets the direction for AI applications in various sectors, including finance [2] - Challenges in the development of "AI + Finance" include the need for stronger governance of technological ethics, risks of model homogeneity, inherent flaws in algorithm architecture, and challenges in data governance and security [2] - To address these challenges, a collaborative approach involving financial security, risk prevention, and an innovative application environment is essential, requiring deep exploration of institutional frameworks and continuous improvement of collaborative mechanisms [2] Group 3 - Looking ahead to the 14th Five-Year Plan, the focus will be on safety, innovation, and ecological collaboration, with policies guiding the development direction and establishing a tiered risk prevention system [3] - Key areas for AI empowerment in finance include credit financing, risk management, and customer service, aiming for effective implementation of AI applications [3] - Strengthening collaboration among government, enterprises, and research institutions is crucial for technological breakthroughs in financial models, alongside investing in talent to support sustainable AI applications in finance [3]

Core Insights - Artificial intelligence (AI) is recognized as a crucial engine for high-quality development across various industries, particularly in the financial sector, where it is expected to enhance digital transformation and governance [1][2]. Group 1: AI in Financial Sector - The "14th Five-Year Plan" is concluding, and the "15th Five-Year Plan" is being formulated, marking a significant year for the integration of AI and finance, aiming for collaborative innovation and deep integration [1]. - Financial institutions are actively promoting the application of AI in various areas such as office assistance, intelligent customer service, credit risk control, and compliance review, achieving positive results [1]. Group 2: Support for AI Development - The development of AI applications in finance is supported by a robust industrial system, with significant reductions in the cost and barriers to entry for large model applications, alongside advancements in intelligent computing chips [2]. - Challenges in AI applications include the need for enhanced ethical governance, risks of model homogeneity, inherent flaws in algorithm architectures, and data governance and security issues [2]. Group 3: Strategic Recommendations - Strengthening overall planning is essential, with a focus on integrating AI applications into the financial technology development plan for the "15th Five-Year Plan" [3]. - Establishing a sound risk control system is necessary, including the development of safety standards for AI applications in finance and enhancing ethical governance [3]. - Improving application levels by focusing on key areas such as credit financing, risk control, and marketing services, while exploring AI-driven service models [3]. - Supporting industry development through collaboration between financial institutions and AI companies, enhancing the competitiveness and safety of foundational AI models and intelligent computing devices [3].