Core Insights - The banking industry is experiencing a dichotomy in attitudes towards AI application, with some professionals expressing skepticism while others advocate for its integration [1][2][3] - Many banks are reflecting on the necessity of AI and digital transformation, emphasizing practical applications rather than adopting technology for its own sake [3][4] - A notable trend is the increasing urgency among certain banks to enhance their digital capabilities and AI deployment, with some even incorporating data transformation rates into performance metrics [3][5] Group 1: AI Application in Banking - Numerous banks are exploring AI capabilities across various business scenarios, including customer service, wealth management, and risk control [5][6] - AI is being utilized to enhance customer interactions, with intelligent customer service systems leveraging existing semantic understanding and workflow capabilities [5][6] - In wealth management, banks are using AI to analyze customer preferences and market conditions to create tailored investment portfolios [5][6] Group 2: Challenges and Realities - Despite the enthusiasm for AI, many banking professionals express concerns about the effectiveness of AI in core business functions, particularly in customer service [2][3] - Some banks have invested heavily in AI infrastructure, such as GPU clusters, but the actual utilization rates do not justify the expenditures [3][4] - There is a recognition that technology should not be pursued for its own sake, and banks need to focus on integrating AI into practical business applications [3][4] Group 3: Future Outlook - As banks approach the release of their semi-annual reports, there is anticipation regarding more genuine disclosures about AI technology applications and digital transformation efforts [6] - The ongoing development of proprietary AI models tailored to banking needs is expected to enhance the effectiveness of marketing, customer service, and risk management [6] - The evolution of AI in banking is seen as a gradual process, requiring time for both employees and the market to adapt to these changes [6]

Core Viewpoint - The article discusses the contrasting perspectives among banking professionals regarding the application of AI in the industry, highlighting both skepticism and enthusiasm towards digital transformation and AI integration [1][2]. Group 1: Attitudes Towards AI and Digital Transformation - Many banking professionals express a cautious approach, emphasizing the need for practical applications rather than adopting AI for its own sake [2][3]. - There is a growing realization among banks that digital transformation should not merely be a superficial exercise, as evidenced by the proliferation of various AI agents claiming to empower banking functions [2][4]. - Despite the enthusiasm for AI, some banks struggle with the effective implementation of AI tools, leading to increased manual work rather than streamlining processes [3][5]. Group 2: Practical Applications of AI in Banking - Banks are increasingly utilizing AI in various business scenarios, including customer service, wealth management, risk control, and credit assessment [6][7]. - Common applications of AI include intelligent customer service that leverages existing capabilities to assist customer managers, and AI-driven investment portfolio customization based on client preferences [6][7]. - AI is also being employed in fraud prevention by analyzing customer behavior and transaction characteristics to enhance identification accuracy [6][7]. Group 3: Differentiation Among Banks - A divide is emerging among banks regarding their approach to digital transformation, with some adopting a more aggressive stance towards AI deployment and others taking a more passive approach [5][6]. - Certain banks are incorporating AI into less common areas, such as financial market operations, and are setting performance metrics related to AI utilization [5][6]. - The ongoing evolution of AI applications in banking reflects a gradual but significant transformation, with banks recognizing the need for time to fully realize the benefits of AI technology [7].

8月15日，盛业控股集团有限公司（简称"盛业"，股份代号：6069.HK）发布2025年中期业绩。截至 2025年6月30日，盛业实现主营业务收入4.05亿元（人民币，单位下同），同比小幅下降7.1%，但净利 润逆势增长约23%至2.03亿元。这一业绩表现凸显了公司战略转型的成效，平台科技服务收入达2.11亿 元，同比大幅增长37%，占总营收比重突破50%，成为集团主要增长动力。 平台科技服务收入的增长主要得益于盛业平台生态的持续扩张和科技实力的不断增强。截至2025年6月 30日，盛业平台累计客户数超过19,100家，同比增长约14.4%，资金合作方数量也增长了31.2%达到181 家。平台普惠撮合业务规模占比约88.0%，同比增长28.3%。中小微企业客户占比超97%，客户留存率超 80%。此外，盛业通过AI Agent等技术为客户提供增值服务，首次实现AI信息服务收入超40万元，并依 托轻资产战略优化资金结构，融资成本同比下降33.9%。这些数据表明，盛业在助力中小微企业降本增 效的同时，正加速向轻资产运营模式转型。 值得关注的是，盛业已连续11年保持盈利记录，并连续7年实施高分红政策。根据2024年1 ...

Core Insights - The widespread application of intelligent customer service is a reflection of how fintech is reshaping banking services [1][3] - The digital transformation of banks is deepening, with a significant reduction in customer visits to physical branches, leading to the adoption of intelligent customer service as a standard [2][3] Group 1: Industry Transformation - The number of bank customer service personnel in China decreased to 50,200 by the end of 2021, down by 4,200 from 2020, marking a shift from previous growth trends [3] - The total amount of off-counter transactions in the banking sector reached 257.28 trillion yuan in 2021, a year-on-year increase of 11.46%, with an average electronic channel diversion rate of 90.29% [3] - The COVID-19 pandemic has accelerated the digital transformation of banks, pushing user habits further online and increasing the frequency and depth of online interactions [3] Group 2: Investment in Technology - In 2020, A-share listed banks invested 207.8 billion yuan in information technology, a year-on-year increase of 25% [6] - Major state-owned banks invested nearly 100 billion yuan in fintech in 2020, with Industrial and Commercial Bank of China investing 23.82 billion yuan, a 45.47% increase year-on-year [7] - China Merchants Bank reported an information technology investment of 13.29 billion yuan in 2021, a year-on-year increase of 11.58%, accounting for 4.37% of its operating income [7] Group 3: AI and Customer Service - In 2021, China Merchants Bank's AI initiatives replaced over 6,000 human roles through intelligent customer service and related technologies [4] - Intelligent customer service has expanded its application beyond routine inquiries to marketing and collection efforts, with voice robots effectively screening potential customers [5] - A report indicated that the satisfaction level of intelligent customer service is limited, with common complaints about repetitive responses and inadequate problem-solving capabilities [5] Group 4: Competitive Landscape - The demand for AI in the financial sector is steadily increasing, with total AI investment expected to exceed 22 billion yuan in 2022 [9] - Companies like BaiRong Cloud have reported significant revenue growth, with a 43% increase in total revenue to 1.623 billion yuan in 2021 [9] - Smaller banks are beginning to adopt AI technologies, with Guilin Bank collaborating with iFlytek to launch a virtual digital employee for customer service [10]

Core Insights - The Chinese government is promoting the "Artificial Intelligence +" initiative, aiming to integrate digital technology with manufacturing and market advantages, supporting the widespread application of large models in various industries, including finance [1] - KPMG's report indicates that the Chinese banking sector is at the forefront of implementing large models, with applications expanding from state-owned banks and joint-stock banks to leading regional banks [1] - The application of AI in banking is broadening, covering front-office services like intelligent investment advisory and product consultation, as well as middle and back-office functions such as intelligent anti-money laundering and regulatory compliance [1] Group 1 - The banking industry is experiencing unprecedented efficiency improvements and innovative breakthroughs due to the transformation of business processes through human-machine collaboration [1] - By 2025, more banks are expected to actively embrace AI and explore its application potential across various fields [1] - Challenges related to data security, model governance, ethical compliance, and talent skill upgrades accompany the application of new technologies, necessitating banks to establish comprehensive governance frameworks and risk prevention mechanisms [1] Group 2 - Despite the widespread application of large models in banking, there remains a gap between actual performance and user expectations, particularly in areas like AI customer service, which often leads to communication difficulties [2] - The banking sector needs to deepen its exploration of large models, shifting from "usable" to "optimal" applications, and from "broad" to "specialized" implementations [2] - Future efforts should focus on understanding the actual needs of different business scenarios, particularly in wealth management and investment strategies, potentially integrating AI with industry experts to address the limitations of large models in complex decision-making [2] Group 3 - There is ongoing potential for the application of large models in banking, particularly in customer marketing, business innovation, risk management, and institutional operations [3] - The emergence and promotion of open-source large models have reduced cost inputs for many banks, but the focus should be on optimizing and enhancing model performance rather than merely achieving usability [3] - Continuous resource investment is necessary for the ongoing exploration of "Artificial Intelligence + Banking" applications, ensuring data quality and improving the effectiveness of large model applications [3]

近日， 未可知人工智能研究院携手全景网，在大湾区成功举办了以"AI赋能财务，智启CFO新 未来" 为主题的行业沙龙。 本次沙龙吸引了众多大湾区企业的首席财务官（CFO）及财务领域专业人士参与，共同探讨人 工智能技术在财务工作中的应用前景与实践路径。 未可知人工智能研究院院长杜雨博士作为本次沙龙的主讲嘉宾，为在场的 CFO们带来了一场 关于AI如何助力企业降本增效的精彩分享。 杜雨博士指出，随着人工智能技术的飞速发展， 生成式AI正逐渐成为产业革新和经济增长的新 引擎。 在财务领域，AI的应用不仅能提高工作效率，还能为企业带来更精准的决策支持。 全景网自 1999年成立以来，一直致力于为中国证券市场提供创新服务，其打造的网上路演、 投资者互动平台等服务已成为 行业标杆 。 凭借多年积累的品牌影响力、强大的资本圈资源以及雄厚的采编和专业服务力量， 全景网如今 已发展成为覆盖媒体、路演互动、金融服务等业务的一站式资本服务平台。 此次与未可知人工智能研究院的联合举办，旨在借助双方优势，为大湾区的财务精英们搭建一 个前沿技术交流与思想碰撞的平台。 | | 学收 (亿 | 同比增长 | 归母净利 | 同比增长 | 毛利率 ...