他进一步指出，成本降低不仅体现在技术部署层面，更推动了智能金融服务覆盖范围的扩大。过去受限 于算力成本与技术要求的中小银行、地方金融机构，如今也能借助轻量化、高效率的AI解决方案，实 现客户服务精准化、风险管理前瞻化和运营管理自动化。 在案例分享环节，吕仲涛特别提到上海银行AI手机银行以对话式服务替代传统界面、微众银行数字营 销系统降低获客成本等实践，表明中小机构正通过AI技术实现服务模式创新与运营效率提升。 "智能金融的发展始终需要以业务场景为核心导向，"吕仲涛总结道，"在未来，既要注重技术的前瞻 性，如构建'通算+智算'双驱动的韧性基础设施，也要坚持风险可控和伦理合规，确保算法可解释、数 据可信任。同时需构建支持规模化应用的智能体平台，打造数字原生的架构与安全治理体系，并通过建 立专业化 AI 人才队伍，实现技术能力与业务需求的深度耦合。" 责任编辑：郝欣煜 专题：2025年深圳香蜜湖金融年会 2025年12月20-21日，第二届"深圳香蜜湖金融年会"在深圳市福田区隆重举行，本届年会以"识变局，开 新局——促进粤港澳大湾区科技-产业-金融良性循环"为主题。中国工商银行原首席技术官吕仲涛出席 并发言。 吕仲 ...

吕仲涛指出，当前金融行业的AI创新已进入以大模型为关键抓手的新阶段。特别是随着以DeepSeek R1 为代表的开源大模型生态的崛起，推动大模型生态进入了开源的普惠期，特征包括模型的全能化，技术 的普惠化，应用的全面化，创新的全民化。他总结出智能金融发展的五大核心趋势： 趋势一：慢思考技术拓展复杂业务场景。 以DeepSeek为代表的"慢思考"（思维链）技术显著提升逻辑 推理上限，带来场景创新，使其在信贷授信决策、虚增销售识别、客户潜在需求洞察及舆情深度分析等 细分场景中发挥关键作用，助力实现客户服务精准化、风险管理前瞻化、运营管理自动化。 趋势二：推理成本降低助力智能金融普惠规模发展。 通过模型蒸馏等技术，小参数模型性能大幅提 升，显著降低了AI部署门槛和推理成本。这使得广大中小金融机构能够广泛应用AI技术，从核心业务 延伸至更多长尾场景，增强智能金融服务的高可及性。 趋势三：智能体迭代升级驱动金融智能新时代。 金融智能体正从"推理者"向"智能体"阶段演进。它们 通过增强的信息获取、决策和执行能力，能够执行复杂的金融任务，如交易监控、资产配置、风险评估 等，通过会话式界面串联业务功能，极大提升金融服务效率与 ...

Core Insights - The core message of the event is the importance of digital transformation in the financial industry, emphasizing the integration of AI technology to enhance efficiency and quality across the entire financial service chain [1][10]. Group 1: Digital Transformation in Banking - The digital transformation in banking has evolved from being a technology-driven necessity to a phase filled with both challenges and opportunities, referred to as the "deep water zone" [3][12]. - The key to improving quality and efficiency in finance lies in the process of driving new growth (incremental) to enhance existing operations (stock), which is a dynamic logic in financial reform [3][12]. - Many banks have made effective attempts at digital transformation, but without a clear linkage between new and existing systems, there can be internal competition for resources and assessments [3][12]. Group 2: Company’s Product Offerings - The company has developed a robust product line covering the entire credit process, data platforms, regulatory compliance systems, and digital banking, providing comprehensive support for financial institutions [4][13]. - The company has established four core platforms—customer profiling, comprehensive rights, marketing activities, and marketing strategies—to facilitate data sharing and business collaboration among banks [4][13]. Group 3: AI Implementation in Finance - The application of AI in the financial sector has shifted from a phase of technological enthusiasm to practical implementation, with a focus on engineering and governance as core issues [7][16]. - The company has identified five typical AI application scenarios, including information extraction, thematic analysis, review processes, decision support, and report writing, enhancing operational efficiency [9][18]. - The company has introduced an AI mobile banking product that transitions from graphical user interfaces to conversational services, providing personalized assistance and asset management [9][18]. Group 4: Future Development and Investment - The company plans to increase investment in key areas such as artificial intelligence, digital operations, and domestic innovation migration, aiming to strengthen integrated hardware and software solutions [10][19]. - The ongoing digital transformation is viewed as a continuous process rather than a one-time project, indicating a commitment to long-term development in the financial sector [10][19].

IDC最新发布的《中国智能体开发平台2025年厂商评估》给出了一个清晰信号：智能体正成为企业AI转 型与流程重构的核心。拥有全栈能力与行业经验的平台厂商已抢占先机，未来竞争将集中于复杂智能体 与应用的一体化开发。 蚂蚁数科旗下的 Agentar 全栈企业级智能体平台，正是在这轮转向中，被IDC评为"领导者"的代表之 一。更关键的是，它率先在金融这个最难落地、也最具价值的行业，跑通了智能体规模化应用的路径。 二、从"能用"到"敢用"， 一、导语 过去一年，智能体几乎成为所有大模型厂商的"标准配置"。代码智能体、办公智能体、营销智能体层出 不穷，但真正进入核心业务系统、能跑在生产一线的属于少数。 金融为什么是智能体的终极考场？ 金融几乎就是智能体的"终极考场"。 一方面，它是对 AI 最渴望的行业之一。从客服、风控到投研、运 营、合规，金融的每一个环节都建立在对信息密度、处理效率和人力规模的极致依赖之上：海量文本、 实时数据、复杂规则、快速决策，天然适合交给智能体来承担。 但与此同时，金融也是对 AI "不够友好"的行业。首先是数据的高度敏感与封闭。金融数据天然带有隐 私属性和机构壁垒，既涉及个人资产、征信、交易 ...

Core Insights - The banking industry is rapidly evolving into a data and algorithm-driven financial service platform, leveraging AI for customer insights, risk assessment, and intelligent restructuring of services [1] - Major banks are implementing AI technologies across various business areas, enhancing customer service, risk control, and marketing strategies [1][10] AI-Driven Service Transformation - Industrial and Commercial Bank of China (ICBC) has launched the "Leading AI+" initiative, introducing over 100 AI applications in personal finance, financial markets, and corporate credit [1] - China Construction Bank has empowered 274 internal application scenarios, focusing on credit approval and intelligent customer service [1] - Postal Savings Bank has integrated large model technology into its financial services, developing over 230 scenarios [1] - Beijing Bank has established a comprehensive AI system with integrated computing power and over 300 AI application scenarios [1] Intelligent Customer Interaction - Shanghai Bank's AI mobile banking allows users to interact through text or voice, simplifying access to services like pension inquiries and product highlights [2] - The AI system analyzes user behavior and preferences to proactively address customer needs, enhancing the overall service experience [2] AI in Small and Micro Enterprises Financing - MyBank is equipping small and micro enterprises with AI credit experts, utilizing intelligent assistants for comprehensive credit risk assessment [3] - The intelligent research assistant analyzes industry characteristics and credit-related data, while the due diligence assistant interacts with clients to gather information [3] Internal Operations Optimization - AI is integrated into internal banking operations, automating tasks like data collection and risk monitoring, thus improving efficiency and reducing costs [4] - Beijing Bank has developed a digital operation framework to provide tailored financial products to different customer segments [4][5] Digital Channel Integration - Beijing Bank's retail business employs a "sea, land, and air" strategy for customer engagement, utilizing online, offline, and remote channels [5] - The bank's mobile banking has nearly 20 million customers, with 99% of transactions completed without visiting a branch [5] Risk Management Enhancement - AI technologies are enhancing risk identification, assessment, and early warning systems in banking [7] - Qingdao Bank has implemented a risk cockpit and a comprehensive risk indicator library for real-time monitoring [7] - SuShang Bank has established a three-tier risk management system, transitioning from reactive to proactive risk control [8] Safety and Compliance in AI Applications - Banks are focusing on the safety and compliance of AI models, with measures in place to ensure secure operations [9] - Everbright Bank is building a "safety fence" around its AI models, conducting thorough safety tests and evaluations [9] Future of Banking with AI - The banking sector is actively advancing AI and large model development, aiming for secure and compliant core AI capabilities [10] - The integration of AI into business operations is expected to reshape the financial service ecosystem, leading to a more intelligent and inclusive banking environment [10]

Core Insights - Hong Kong is emerging as a crucial starting point for mainland Chinese tech companies to expand globally, leveraging its status as a leading international financial center and a "super connector" [1][2][9] - The recent Hong Kong FinTech Week showcased numerous mainland tech firms, highlighting their innovative solutions and the growing trend of "going global" through Hong Kong [2][3] Group 1: Hong Kong's Role in Global Expansion - Hong Kong serves as a vital platform for mainland tech companies to access international markets, with nearly 400 financial clients from over 20 countries benefiting from Tencent Cloud's digital solutions [1][3] - The city has seen a significant increase in the number of fintech companies, with over 1,200 firms operating, reflecting a 10% growth from the previous year [3][11] - The Hong Kong government is actively promoting a one-stop platform for mainland enterprises to facilitate their overseas expansion, including the establishment of an "Overseas Expansion Task Force" [9][10] Group 2: Technological Advancements and Collaborations - Major tech firms like Ant Group and Tencent are utilizing Hong Kong as a launchpad for their innovative technologies, such as AI banking and cross-border payment solutions [2][3] - The establishment of supportive policies, such as relaxed listing requirements for tech companies, has attracted more firms to consider Hong Kong for their IPOs [3][11] - The Digital Port in Hong Kong has become a hub for AI and data science startups, fostering collaboration and resource sharing among mainland companies [6][7] Group 3: Economic Impact and Future Outlook - In 2024, mainland China's outbound direct investment reached $192.2 billion, marking an 8.4% increase, with Hong Kong playing a pivotal role in this growth [9][10] - The ongoing development of the Guangdong-Hong Kong-Macao Greater Bay Area is expected to further enhance Hong Kong's position as the primary gateway for mainland enterprises [11] - The dual role of Hong Kong as both a "super connector" and a "super value creator" is anticipated to solidify its status as the best platform for mainland companies seeking to expand internationally [11]

Core Insights - The article highlights the significance of Hong Kong as a strategic launchpad for Chinese tech giants like Huawei, Tencent, Ant Group, and Du Xiaoman in their global expansion efforts [1][2] - The Hong Kong FinTech Week 2025 attracted over 37,000 participants from more than 100 economies, showcasing advancements in AI and blockchain technologies [2] - Hong Kong's fintech sector is experiencing rapid growth, with over 1,200 fintech companies, a 10% increase from the previous year, and projected revenues exceeding $600 billion by 2032 [2] Group 1: FinTech Development - The Hong Kong government aims to solidify its position as an international fintech hub, with approximately 75% of financial institutions adopting or trialing generative AI, expected to rise to over 87% in the next 3 to 5 years [5] - The Hong Kong Monetary Authority (HKMA) announced the "FinTech 2030" strategy, focusing on data and payment infrastructure, AI, resilience enhancement, and financial tokenization, encompassing over 40 specific projects [5] - The integration of AI in wealth management, risk control, and smart marketing is accelerating, enhancing operational efficiency in the financial sector [5] Group 2: AI and Cloud Services - The integration of AI models with the financial industry is a key highlight of the event, with major tech companies showcasing their latest advancements in AI [7] - Tencent Cloud's VP outlined five stages of AI development, emphasizing the transition from conversational AI to autonomous agents [7] - Ant Group presented its full-scenario AI upgrade solutions, including the Agentar platform and AI mobile banking applications, attracting significant attention [8] Group 3: Global Expansion Challenges - As domestic market growth slows, Chinese tech companies are increasingly looking to expand internationally, with Hong Kong serving as a crucial gateway due to its proximity to mainland China and established financial infrastructure [11] - Companies face strategic decisions on whether to prioritize serving Chinese institutions abroad or to secure local client contracts [11] - Compliance and cultural adaptation are significant challenges in the internationalization process, with local regulatory requirements and documentation standards differing from those in China [13] Group 4: Business Development Progress - Tencent Cloud has made substantial progress in overseas markets, with notable clients in Southeast Asia, including the Bank of Indonesia and Allo Bank, utilizing its cloud products [14] - The company reports double-digit growth in international markets, indicating a deepening engagement with clients' core systems [14]

Core Insights - Ant Group's AI business is actively supporting local commercial banks in China to adopt financial large models and intelligent agent technologies to enhance performance amidst challenges like narrowing net interest margins and intensified competition [1][3] - The implementation of AI has shifted from a trial phase to a necessity, transforming from a cost center to a core element of service, marketing, and value creation [1] Group 1: AI Adoption and Impact - Local commercial banks are experiencing significant improvements in employee efficiency, marketing conversion rates, and revenue scale through AI applications [1] - For instance, a pilot bank reported that the use of digital avatars for financial advisors increased the average number of clients served per advisor from 200 to 2000, leading to a revenue growth of approximately 20% [1] - The AI mobile banking solution developed for Shanghai Bank allows users to perform over ten high-frequency tasks through natural language interaction, resulting in a 10% increase in business conversion rates [2] Group 2: Strategic Approaches to AI Implementation - Different financial institutions should choose AI evolution paths that suit their resources and development stages, with regional banks advised to start with application scenarios and gradually increase investment [3] - Some banks are prioritizing the upgrade of existing mobile apps to AI mobile banking to enhance user experience and engagement [3] - The ideal model involves establishing a dedicated team to create a comprehensive knowledge base and data set, leveraging Ant Group's financial reasoning large model to drive end-to-end business process reengineering and organizational upgrades [3] Group 3: Market Coverage - Ant Group's financial digital services have reached 100% of state-owned joint-stock banks, over 60% of local commercial banks, and hundreds of financial institutions [3]

北京商报讯(记者刘四红)10月30日，在2025金融街论坛上，蚂蚁数科AI业务总裁、蚂蚁集团副总裁余滨 发表演讲时透露，当前不少城商行正积极拥抱金融大模型与智能体技术，寻求业绩突围。蚂蚁数科致力 于支持银行构建自主可控的金融大模型，江浙沪地区的部分城商行在员工工作效率、营销转化率、营收 规模等方面取得显著增长。 据了解，蚂蚁数科的金融数智化服务已覆盖100%的国有股份制银行、超60%的地方性商业银行及数百 家金融机构。 以上海银行（601229）为例，蚂蚁数科助力其打造的AI手机银行，以"对话即服务"为核心，用户通过自 然语言交互即可办理转账、还款、理财咨询、养老金查询等十余项高频业务。用户不用在复杂菜单中翻 找功能入口，操作门槛低了，老年客户满意度更高了，业务转化率提升了10%。 浙江一家头部城商行则与蚂蚁数科合作，系统性构建了"算力-平台-模型-应用"全栈AI能力，落地30多个 智能体场景，覆盖客户服务与内部运营两端。 余滨强调，不同金融机构的资源禀赋与发展阶段各异，应选择适合自身的AI演进路径。预算有限的区 域性银行，可以选择先从场景应用入手，按效果付费，逐步加大投入；也有很多银行优先将原有的手机 Ap ...

Core Insights - Ant Group's AI business is actively supporting city commercial banks in adopting financial large models and intelligent agent technologies to enhance performance amidst challenges like narrowing net interest margins and intensified competition [1][2] - The shift from AI being a trial to a necessity is emphasized, with AI transforming from a cost center to a core element of service, marketing, and value creation [1] Group 1: AI Adoption in Banking - Many city commercial banks are leveraging AI as a key strategy for performance improvement, with significant growth in employee efficiency, marketing conversion rates, and revenue scale reported in regions like Jiangsu, Zhejiang, and Shanghai [1] - The implementation of AI applications has expanded from basic functions like intelligent customer service to comprehensive systems covering marketing, risk control, investment advisory, and claims processing [1] Group 2: Case Studies and Results - For instance, Shanghai Bank's AI mobile banking service allows users to perform over ten high-frequency tasks through natural language interaction, resulting in a 10% increase in business conversion rates and higher satisfaction among elderly customers [2] - A leading city commercial bank in Zhejiang has developed a full-stack AI capability with over 30 intelligent agent scenarios, enhancing both customer service and internal operations [2] Group 3: Strategic Approaches to AI Implementation - Different financial institutions are advised to choose AI evolution paths that suit their resources and development stages, with options ranging from starting with application scenarios to upgrading existing mobile apps into AI-driven platforms [2] - Some banks are establishing dedicated teams to create comprehensive knowledge bases and datasets, utilizing Ant Group's financial reasoning models to build autonomous "financial brains" for end-to-end business process reengineering [2] Group 4: Market Coverage - Ant Group's financial digitalization services have reached 100% of state-owned joint-stock banks, over 60% of local commercial banks, and hundreds of financial institutions [2]