重塑肌会管理 的四大趋势 对公银行业务未来展望 The better the question. The better the answer. The better the world works. 二 安永 Shape the future with confidence 聚信心 塑未来 ■ ■ ■ ■ 日家 06 财资自动化从流程效率向业务 智能化演进 11 数据驱动型服务重塑银行的企业 现金管理角色 16 行业定制化解决方案成为对公银 行业务的标准范式 20 区块链市场基础设施：打造价值交 换新方式和银行增长新机遇 26 联系安永 安永未来银行业务研究与前沿报告 安永对公银行业务未来研究为我们的前沿报告系列刊物提供了内容基础，是对2020年起发布的 相关研究报告的延续。发布《现金管理的未来图景》报告之后，我们还计划于今年晚些时候发布 《企业融资的未来图景》报告。 2 | 重塑现金管理的四大趋势 下载 三三 "未来不同往昔"。这句老话恰如其分地映照出对公银行现金管理业务的发展前景。从诸多方 面看，未来实则已至。最具魄力的银行正在积极把握机遇，通过量身定制的解决方案及服务体 验,不断丰富其价值主张、拓展现金 ...

以常州瑞声科技为例，在高精密的生产过程中，瑞声科技运用人工智能和机器学习技术提升产品检测效率，通过自动化实现模具循环使用和铜材回收等工 艺，减少材料浪费，践行可持续发展承诺。 崔玉善说："苹果公司也致力于让世界更美好，过去十年间，已将全球碳足迹降低了超过60%，并大幅提升了再生材料的使用比例。苹果公司承诺到2030 年，在供应链和整个产品生命周期中实现百分百碳中和。" 据悉，目前，苹果公司产品在中国已有超过90%的生产制造采用可再生能源，立讯精密等供应商已完全实现使用清洁能源生产苹果公司产品，并在关键 iPhone部件中100%使用再生稀土元素、再生铜和再生钨。 【环球网科技报道 记者 张阳】11月18日，以"汇聚新质生产力开放合作赢未来"为主题的2025年产业链供应链国际合作交流会暨企业家太湖论坛在无锡成功 举办。作为商务部"投资中国"系列活动重要组成部分，论坛搭建起跨国界、跨行业的交流合作平台，吸引了苹果、辉瑞、LG新能源等全球知名企业代表齐 聚，共探产业链供应链高质量发展新路径。 论坛现场披露的数据显示，江苏已成为外资企业投资兴业的优选地。2024年江苏实际使用外资190.5亿美元，占全国比重16.4% ...

[文/观察者网 阮佳琪] 中国人工智能技术正以爆发式速度迭代，与美国的差距快速拉近。据彭博社19日报道，一项最新统计显 示，清华大学在人工智能领域发表的学术论文中，入选"全球引用量最高100篇论文"的数量位居全球高 校之首，且该校获批的相关专利数量更超过麻省理工学院、斯坦福大学、普林斯顿大学与哈佛大学这四 所美国顶尖高校的总和。 报道引述励讯集团（RELX）旗下专利数据分析服务商律商联讯（LexisNexis）的数据称，2005年至 2024年末，清华累计获得4986项人工智能与机器学习相关专利，仅去年一年就新增900余项。而在全球 该领域的有效专利族（同一项核心技术在多国/地区申请的全部专利）中，中国占比已过半。 不过目前，美国在人工智能领域仍保有最具影响力的专利与性能最优的模型。例如，在专利影响力排名 中，哈佛大学与麻省理工学院始终领先于清华大学。斯坦福大学发布的《人工智能指数报告》也显示， 2024年美国科研机构研发的知名人工智能模型达40个，而中国为15个。但在部分性能测评指标上，中国 机构正逐步缩小与美国的差距。 这也让美国想要保住人工智能科研领域的领先地位，正面临不小挑战。华盛顿智库美国信息技术与 ...

Core Insights - The article emphasizes the accelerating impact of artificial intelligence (AI) on industrial transformation, highlighting the shift from theoretical breakthroughs to practical applications across various sectors [2][3][4]. Group 1: AI Development and Trends - AI has evolved significantly over the past 70 years, transitioning from expert systems to machine learning and now to deep learning, which utilizes neural networks to solve complex problems [3][4]. - The introduction of large language models (LLMs) marks a new phase in AI development, enabling better understanding and generation of human language [4][5]. - The current trends in AI include a shift in focus from model training to inference, with increasing demand for practical applications and solutions to real-world problems [6][7]. Group 2: Policy and Industry Response - The Chinese government is actively supporting the "AI+" initiative, aiming to integrate digital technology with manufacturing and market advantages, with a target for widespread adoption of intelligent applications by 2027 [2][7]. - Companies are encouraged to adopt a four-step methodology for AI implementation, which includes identifying business pain points, defining core values, executing plans, and adapting organizational structures to leverage AI effectively [8][9]. Group 3: Philosophical Considerations - The debate on whether AI will replace humans is ongoing, with contrasting views from industry leaders. Some express concern over AI's potential to surpass human capabilities, while others believe it will enhance human productivity and quality of life [10][12]. - The efficiency of human cognition, which operates on approximately 20 watts, starkly contrasts with the energy demands of training advanced AI models, highlighting the unique advantages of human intelligence [11].

Core Insights - The article highlights a significant shift in the global remote sensing research landscape, with China increasing its share of published papers from nearly zero in the 1990s to 47% by 2023, while the U.S. share plummeted from 88% to 9% [1][2][5]. Group 1: Research Output - In 2023, China accounted for nearly half of the global remote sensing publications, while the U.S. share fell below 10% [2]. - The number of remote sensing papers published globally has grown exponentially, from just over ten per year in the 1960s to more than 13,000 annually by 2023 [9]. - A study analyzed over 126,000 scientific papers from 72 journals between 1961 and 2023, revealing China's rapid rise in research output [5]. Group 2: Funding and Institutional Support - Research funding levels are strongly correlated with publication output, with over 53% of China's remote sensing papers funded by the National Natural Science Foundation, compared to only 5% for U.S. institutions [6]. - The top six funding agencies for remote sensing research from 2011 to 2020 were all Chinese, while NASA and the National Science Foundation (NSF) ranked seventh and eighth, respectively [7][8]. Group 3: Technological Advancements - China has made significant breakthroughs in remote sensing technologies, including multi-spectral and hyperspectral imaging, synthetic aperture radar, and advancements in data transmission and processing [12]. - Recent innovations include a dual-station collaborative ranging technology achieving nanometer-level precision, which could support high-precision space research [12]. Group 4: Future Outlook - The article suggests that unless the U.S. government significantly adjusts its funding priorities, it is unlikely to regain its leadership in remote sensing innovation [13][14]. - The ongoing investment in artificial intelligence, machine learning, and quantum computing by China is expected to further enhance its capabilities in remote sensing [10].

Core Insights - The importance of small and medium-sized enterprises (SMEs) in economic growth and job creation is emphasized, highlighting that isolated enterprises struggle to survive [3][6][8] - The concept of industrial clusters, particularly in the context of SMEs, is discussed, noting that these clusters can enhance innovation and competitiveness against larger firms [2][3][6] - The evolution of SME clusters in China is traced, indicating that many of these clusters are rooted in specific localities and have emerged due to globalization and international outsourcing [6][8][10] Group 1 - SMEs are crucial for economic growth and job creation, but isolated firms face significant challenges [3][6] - The concept of industrial clusters, where SMEs can both compete and collaborate, is vital for enhancing innovation capabilities [2][3][6] - The rise of digital platforms and the establishment of a nurturing ecosystem for SMEs are essential for their development in the current technological landscape [8][10] Group 2 - Historical examples of successful SME clusters in China, such as the cashmere industry in Hebei and the sock industry in Zhejiang, illustrate the potential for growth and innovation [11][12] - The role of community building and local government support is highlighted as critical for the sustainable development of SME clusters [11][12] - The need for a structured approach to fostering these clusters, including the establishment of dedicated organizations and leveraging non-profit resources, is emphasized [11][12]

Core Viewpoint - The forum discussed how finance can support the development of new productive forces, emphasizing the need for collaboration between commercial banks and innovative enterprises [1] Group 1: Financial System and Innovation - The current banking-dominated financial system must expand its support for technological innovation, with banks establishing specialized departments to provide tailored financial services for high-tech and specialized small and medium enterprises [3] - Long-term exploration of the investment-loan linkage model encourages banks to collaborate with external investment institutions to share risks while gaining better insights into the operational conditions of loan enterprises [3] - Development of intellectual property pledge financing is facilitated by advancements in AI and digital banking, which improve the assessment of intellectual property market value [3] Group 2: Bond Market and Venture Capital - Establishment of a technology board in the bond market is supported by the central bank, which promotes the issuance of innovation bonds for tech enterprises and provides risk compensation through structural tools [4] - The central government is advancing the establishment of a national venture capital guidance fund to address fundraising, investment, management, and exit issues, particularly focusing on improving exit channels beyond IPOs [4] - The equity market is encouraged to support innovation enterprises, enhancing the service levels of the Sci-Tech Innovation Board and the Growth Enterprise Market [4] Group 3: Technology Empowering Financial Services - The use of AI and machine learning to create intelligent risk control models can lower decision-making costs and risks for financial institutions, optimizing the efficiency of fund utilization [5] - Dynamic credit profiles can enhance risk identification capabilities, while effective risk-sharing and compensation mechanisms, such as insurance, are necessary for financing technology enterprises [5] - The integration of smart technology in financial services is expected to create effective channels for supporting the development of new productive forces [5]

在11月13日举行的太湖世界文化论坛.钱塘对话上，中国国际经济交流中心副理事长、国务院发展研究 中心原副主任王一鸣表示，新一轮科技革命在加速突破，人工智能是核心驱动力，带来了广泛的各领域 的深刻的变革和创新。 他进一步表示，在现有的以商业银行为主导的金融体系下，可以加强与风投机构等金融机构合作，对投 资机构通过净值调查意向投资的科创企业、专精特新企业相应地提供贷款。 同时，王一鸣表示，要大力发展并购市场，鼓励设立市场化的并购基金，来解决创投机构的退出问题。 此外，王一鸣表示，要加强科技对金融服务的赋能，利用人工智能、机器学习来构建智能的风控模型， 动态评估企业的信用风险，降低金融机构的决策成本和决策风险，通过智能投顾为企业提供定制化的投 融资方案，优化资金的使用效率等。 要借助智能技术来构建动态的信用画像提升金融机构的风险识别能力，同时要建立有效的风险的分担和 补偿机制，比如通过保险和再保险，为科技型企业融资实行风险分担；要探索地方政府对科创企业征信 和风险的补偿机制。 "我们要把握主动权就要加强原始创新和关键核心技术攻关，通过科创和产业创新的深度融合。"王一鸣 说，未来，要推动三个转变：从过去的跟跑转向更多 ...

Core Viewpoint - The article discusses the automation of accounts receivable (AR) and accounts payable (AP) processes, highlighting the expected growth of the global market and the key trends driving this transformation [6][20]. Market Overview - The global accounts receivable and accounts payable automation market is projected to reach $5.67 billion by 2030, with a compound annual growth rate (CAGR) of 7.2% in the coming years [6]. - The top five manufacturers are expected to hold approximately 22.0% of the market share in 2024 [9]. Product Type Segmentation - Cloud-based solutions dominate the market, accounting for about 84.1% of the total share [12]. Application Segmentation - The automation solutions cater to both small and large enterprises, indicating a broad applicability across different business sizes [29]. Market Trends 1. **Dominance of AI and Machine Learning**: AI serves as a core engine for automation, enhancing data accuracy and improving collection rates through predictive analytics [20]. 2. **Shift to End-to-End Platforms**: Companies are moving towards integrated platforms that manage the entire procure-to-pay (P2P) and order-to-cash (O2C) cycles, improving cash flow transparency [21]. 3. **Embedded Payments and Real-Time Execution**: Modern AP platforms now include embedded payment options, streamlining payment cycles and enhancing customer experience [22]. 4. **Power of Data and Predictive Analytics**: Automation platforms are evolving into rich data sources, enabling better cash flow forecasting and strategic supplier relationships [23]. 5. **Enhanced Fraud Detection and Security**: Advanced security features in modern automation systems are addressing the evolving risks of digital financial processes [24]. Key Drivers 1. **Accounts Receivable (AR)**: AR automation software optimizes invoice and payment processes, significantly reducing the time spent on collections and improving cash flow [25]. 2. **Accounts Payable (AP)**: AP automation enhances efficiency and accuracy in the accounts payable department, integrating with accounting solutions or ERP systems [25]. Major Challenges 1. **Integration**: The integration of AP automation solutions with accounting and ERP systems remains a challenge, particularly for companies using outdated legacy systems [26]. 2. **Business Intelligence**: Rapid technological advancements in business intelligence create continuous pressure for participants in the AR/AP automation market to keep up [26].

后端即服务（Backend as a Service，BaaS）是一种云计算服务模型，旨在简化和加速应用程序的开发过 程。它提供了一个托管的后端基础架构，包括服务器、数据库、存储和其他相关组件，使开发人员能够 专注于应用程序的前端开发，而无需关注后端基础设施的细节。 后端即服务的主要特点包括： 数据存储和管理：BaaS提供了数据存储和管理的功能，开发人员可以使用API来创建、读取、更新和删 除数据，而无需编写复杂的后端代码。 用户管理和身份验证：BaaS提供了用户管理和身份验证的功能，开发人员可以轻松地创建用户账户、管 理用户权限，并实现用户身份验证和授权。 云函数和业务逻辑：BaaS允许开发人员编写和部署云函数，用于处理应用程序的业务逻辑。这些云函数 可以在云端执行，从而减轻了客户端的负担。 文件存储和管理：BaaS提供了文件存储和管理的功能，开发人员可以上传、下载和管理文件，以支持应 用程序的文件操作需求。 实时通信和推送通知：BaaS提供了实时通信和推送通知的功能，开发人员可以使用API实现实时聊天、 实时数据同步和推送通知等功能。 通过使用后端即服务，开发人员可以快速构建和部署应用程序，减少了开发周期 ...