作为资产规模超9万亿元的股份制银行，浦发银行一直以来都是吸纳人才的大户，员工总数超6万 人。但从近两年的数据来看，浦发银行也在对团队进行优化。 东方财富Choice数据显示，浦发银行员工数量也从年初的63582人下降到年中的61892人，半年减少 1690人。值得关注的是，在2022年末，浦发银行职工总数曾高达64731，不到两年的时间，浦发银行已 减少近3000人。 此外，还有部分银行出现了小幅"缩编"。例如，南京银行员工数量从年初的16342人下降到年中的 16260人，减少82人；沪农商行员工数量从年初的11295人下降到年中的11240人，小幅减员55人。 作为传统就业大户，银行一直都是金融专业毕业生就业的重要选择。然而，在金融科技降本增效的 作用下，银行对于人力资源的依赖正在逐步降低，精简团队、提升科技人员占比成为不少机构的选择。 随着上市银行中报的陆续披露，各家银行的员工变动情况正在逐步浮出水面。从上半年的情况来 看，哪些银行正在优化人才队伍？哪些银行又在扩充"正规军"？ 多家银行优化人员结构 截至《金融时报》记者发稿前，共有7家上市银行公布了2024年中期业绩报告，5家上市银行公布了 2024年 ...

Core Insights - The trend of shutting down and integrating banking apps continues, with Zhuhai China Resources Bank announcing the termination of its "Run Wallet App" service, reflecting a broader industry shift towards digital transformation aimed at reducing operational costs and enhancing efficiency [1][2] Summary by Category App Shutdown and Integration - Zhuhai China Resources Bank will officially stop the "Run Wallet App" service on October 15, 2025, migrating its functions to the China Resources Bank App for a one-stop service [2] - Many banks, including state-owned and joint-stock banks, are accelerating the consolidation of their apps, particularly focusing on credit card and direct banking apps [2][3] - The number of available credit card apps has significantly decreased, with most remaining apps concentrated among major state-owned banks, while city commercial banks and rural commercial banks have seen a decline in their credit card app offerings [2] Industry Trends - The integration of credit card and direct banking apps is driven by the need for banks to adapt to changing industry dynamics, as these apps have overlapping functions and are becoming less relevant [3][4] - The trend began several years ago, with banks starting to optimize channels and integrate apps, which has accelerated since 2023 [4] Reasons for Integration - The primary reasons for app consolidation include a shift from broad operations to more targeted approaches, focusing on enhancing user experience and operational efficiency [4] - Regulatory policies have also played a role, with the National Financial Regulatory Administration issuing guidelines to strengthen the management of mobile applications in the banking sector [4] Future Directions - The future of banking apps is expected to focus on three main trends: scenario-based integration, comprehensive ecosystem development, and intelligent upgrades through technology [6] - Banks aim to create a "financial + scenario ecosystem" that integrates various life services, enhancing user engagement and loyalty [6]

Core Viewpoint - The development of large models and AI technologies is creating new paths for technological empowerment in the banking industry, aiming to enhance asset organization efficiency and reduce operational costs through digital transformation [1]. Group 1: Relationship between Large Model Capabilities and Banking Application Scenarios - Large model technologies have achieved significant breakthroughs in natural language processing, including content generation, information extraction, and dialogue interaction, which align well with the knowledge-intensive characteristics of the banking industry [1][9]. - Applications in the front office include knowledge bases and intelligent customer service, with examples showing a 10% reduction in call duration and an 80% decrease in labor costs [5][14]. - In the middle office, intelligent credit assessment has reduced due diligence report writing time from one week to five minutes, indicating a potential shift towards real-time, comprehensive, algorithm-intensive credit review processes [1][21]. - The backend development has seen improvements in code generation efficiency, with several banks reporting a 20%-30% increase in productivity [5][24]. Group 2: Generative AI vs. Discriminative AI - Generative AI excels in creating new content from unstructured data but faces challenges such as high computational costs and poor interpretability, while discriminative AI (e.g., logistic regression, decision trees) is widely used in banking risk control due to its efficiency and accuracy [2][31]. - Future collaboration between generative and discriminative AI is expected to create two models: a "hub-and-spoke model" where generative AI disassembles tasks and integrates results, and a "serial model" where both types work at the same level [2][39]. Group 3: AI and Banking Digital Transformation - The application of large models aims to drive digital transformation in banks, which requires deep changes in business processes supported by strategic planning, organizational collaboration, and technology implementation [3][7]. - Historical analysis shows that significant technological innovations in the banking sector have always been accompanied by process adjustments, emphasizing the need for comprehensive transformation commitment from financial institutions [3][56]. - The digital transformation success rate in enterprises is only 16%, highlighting the importance of integrating digital technology deeply into business processes for sustained competitive advantage [51][55].

Core Viewpoint - The increase in work intensity among bank employees is closely related to the pressure of business assessments, leading to a feeling of being "data-driven" in their roles [1][11]. Group 1: Work Intensity and Data Utilization - Employees like Zhao Fei have experienced a significant increase in work intensity due to the implementation of daily business data reporting, which has shifted their work from a passive to an active approach in client engagement [2][11]. - The construction of data platforms in banks has improved the timeliness of data collection and analysis, allowing for quicker business optimization decisions, but has also resulted in increased task metrics for frontline employees [3][5]. - The shift from weekly to daily reporting of business performance has led to a reported increase in workload by at least 30% for some employees, causing stress and sleep issues due to performance pressures [5][11]. Group 2: Decision-Making Efficiency - Enhanced data timeliness has improved decision-making efficiency at various levels within banks, allowing branch leaders to quickly grasp the latest operational status and adjust strategies accordingly [6][7]. - Real-time performance data enables branch leaders to monitor key performance indicators and respond to anomalies, thereby supporting effective operational decisions [7][8]. - The development of personal performance dashboards for frontline employees has motivated them to improve their performance, although it has also led to complaints about increased pressure and workload [8][11]. Group 3: Employee Sentiment and Management Pressure - Employees express anxiety over their performance rankings, fearing repercussions from management if their branch's performance declines [9][10]. - The competitive environment created by daily performance monitoring has led to a culture of constant oversight and pressure to meet targets, resulting in a significant change in employee behavior and work dynamics [10][11]. - There is a growing desire among employees for a more balanced work environment that allows for effective performance without excessive pressure from constantly changing business targets [11].

Core Insights - The banking industry is experiencing increased work intensity for frontline employees due to the implementation of data platforms that enhance the timeliness of business data reporting [1][2][3] - Employees are now required to respond more quickly to performance metrics and adapt to frequent changes in business strategies, leading to heightened pressure and stress [6][10] Group 1: Impact of Data Platforms - Many banks have established data platforms to improve the speed and efficiency of data collection and analysis, which aids in making timely business decisions [2][4] - The shift from weekly to daily reporting of business performance has significantly increased the workload for employees, with some reporting a workload increase of at least 30% [3][6] - Enhanced data timeliness allows branch leaders to monitor performance metrics in real-time, enabling quicker adjustments to business strategies [5][6] Group 2: Employee Experience and Challenges - Frontline employees express concerns about the increased pressure to meet performance targets, with some feeling like they are "data-driven workers" [8][10] - The competitive environment created by real-time performance tracking leads to a culture of constant monitoring and pressure to perform, which can negatively impact employee morale [7][9] - Employees are seeking a balance between improved decision-making processes and a more manageable work environment [10]

Core Viewpoint - The banking industry is experiencing a significant turnover in executive leadership, with a trend towards younger executives and diverse hiring methods, which is expected to drive innovation and transformation within the sector [1][2][3][4]. Group 1: Executive Changes - In 2023, numerous banks, including major state-owned banks and smaller institutions, have seen changes in senior management, with over 30 banks appointing new presidents or vice presidents [2][3]. - Notable appointments include Zheng Guoyu as chairman of Postal Savings Bank, and Wang Dajun as vice president of Agricultural Bank, both of whom are from the "70s generation" [2][3]. - The trend of younger executives is particularly pronounced in city commercial banks, with several "80s generation" individuals taking on significant roles [3]. Group 2: Hiring Methods - The method of appointing bank executives is becoming increasingly diverse, with many smaller banks opting for public selection processes to attract new talent [4][5]. - Examples of banks utilizing public recruitment include Benxi Bank and Zhuhai Huaren Bank, which have both conducted open searches for executive positions [4][5]. - Regulatory encouragement for open recruitment is evident, as guidelines promote transparency and market-based selection of senior management [5]. Group 3: Future Trends - Predictions indicate that future executive recruitment in banks may become even more open, potentially including candidates from non-banking sectors to enhance organizational evolution and service quality [6]. - The trend towards open recruitment is expected to continue, reflecting a shift in the banking culture towards greater openness and adaptability in response to digital transformation and financial reforms [6].

Core Viewpoint - The banking industry is increasingly adopting a "365" model, providing year-round services to enhance customer experience and meet diverse banking needs, as exemplified by Shenzhen Futian Yinzuo Village Bank's announcement to resume 365-day service starting June 16, 2025 [1][5]. Group 1: Service Hours Adjustments - Shenzhen Futian Yinzuo Village Bank will operate Monday to Friday from 8:30 AM to 5:30 PM, and on weekends and public holidays from 9:00 AM to 4:00 PM [1]. - Baoding Bank announced adjustments to its personal business hours, effective June 21, with weekday hours from 9:00 AM to 5:00 PM and weekend hours from 9:30 AM to 4:30 PM [5]. - Hohhot Rural Commercial Bank and Huishang Bank are also adjusting their service hours, with the former resuming weekend operations for personal business and the latter implementing a weekend rotation system from April 1 to November 30, 2025 [7]. Group 2: Operational Strategies - The "365" model will be implemented through flexible weekend rotations and employee shifts to ensure continuous service [8]. - Many banks have also introduced "night banking" services to cater to customers' needs outside traditional hours, with some banks extending their operating hours until 11:30 PM [9]. Group 3: Industry Trends - The banking sector is experiencing a decline in physical branch visits due to the rise of digital banking, with a reported decrease in the number of bank branches in China, totaling approximately 220,000 by the end of 2024, down by 1,344 from 2023 [10]. - The shift from physical branches to digital platforms reflects a broader trend in the industry, where banks are focusing on enhancing customer experience through differentiated services amid intense competition [11].

Core Insights - The leadership changes in regional commercial banks reflect a trend towards younger executives, particularly those born in the 1970s and 1980s, which aligns with the industry's digital transformation and regulatory requirements [4][5]. Group 1: Leadership Changes - Urumqi Bank and Dalian Bank have appointed new leaders from the "70s" generation, with Wang Hui and Zeng Tao taking on the roles of chairman [2][3]. - Urumqi Bank's total assets reached 227.85 billion yuan, with a 7.70% increase year-on-year, while its non-performing loan ratio rose to 1.95% [3][7]. - Dalian Bank's total assets amounted to 520.28 billion yuan, reflecting a 6.56% increase, and it reported a net profit of 0.62 billion yuan, up 1.78% [4][3]. Group 2: Industry Trends - The trend of younger leadership is driven by the need for digital transformation in banking, as younger leaders are generally more adept at adapting to technological changes [4][5]. - Regulatory constraints on executive tenure are accelerating management turnover, promoting a younger leadership that is less associated with past risk events [5]. Group 3: Other Leadership Changes - Inner Mongolia Bank has appointed a seasoned leader, Hong Shaoping, born in 1967, indicating a different approach compared to the other banks [6]. - Inner Mongolia Bank's total assets were reported at 161.23 billion yuan, with a 9.92% increase year-on-year, and a significant loan balance increase of 9.73% [7].

Core Viewpoint - The announcement by Beijing Bank marks the end of an era for direct banks in China, as it plans to migrate its direct banking services to its "Jingcai Life" mobile banking app by June 25, 2025, leading to the discontinuation of the first direct banking channel in the country [1] Group 1: Industry Trends - The number of operational direct banking apps has decreased to fewer than 20, a significant drop from 135 at its peak in 2017, indicating an over 85% market elimination rate [1] - Direct banks were initially popular due to their convenience and low operational costs, but have faced challenges leading to their decline [2] Group 2: Historical Context - Beijing Bank launched the first direct bank in collaboration with ING Group in September 2013, during a time of rapid growth in internet finance, with direct banks seen as a key tool for digital transformation [2] - By 2015, Beijing Bank's direct banking customer base reached 246,000, with savings deposits increasing by 463.1% compared to the beginning of the year [2] - The last reported customer count for Beijing Bank's direct banking was 476,000 in 2019, with 60.7% being external customers, but this segment has since disappeared from annual reports [2] Group 3: Challenges Faced - The decline of direct banks is attributed to overlapping positioning and structural dependencies, leading to unclear development paths and customer confusion [3] - The distinction between direct banks and mobile banking has blurred, as mobile banking apps have integrated various services, resulting in significant product overlap [3][4] - Direct banks often lack independent management structures, being subordinate to traditional banks, which hampers their ability to innovate and compete effectively [4] Group 4: Future Outlook - The closure and integration of direct banking services are seen as a trend that will continue in the industry [6] - Remaining independent direct banks, such as Baixin Bank and YouHui WanJia, are exploring new development paths that differ from traditional departmental structures [6] - Baixin Bank, established in January 2017, aims to bridge traditional banking and internet enterprises, but has faced challenges, including a 23.74% decline in net profit in 2024 [6] - The evolution of direct banks serves as a lesson for commercial banks to explore a hybrid online-offline business model while maintaining a clear positioning and leveraging their strengths [6]

Core Viewpoint - Commercial banks are actively embracing digital transformation to enhance their service capabilities for the real economy, but there exists a "digital divide" between banks and enterprises, particularly affecting small and medium-sized enterprises (SMEs) and small banks [1][7]. Group 1: Information Asymmetry in Banking - Traditional banking methods cannot fully resolve the information asymmetry between banks and enterprises, leading to issues like credit rationing and discrimination [2]. - Research indicates that collateral can mitigate adverse selection, but reliance on collateral often disadvantages smaller enterprises that lack sufficient assets [2][3]. - The structure of the banking industry, dominated by large banks, further exacerbates the challenges faced by SMEs in accessing credit [3][4]. Group 2: Positive Impact of Digital Transformation - Digital transformation enhances banks' information collection and data processing capabilities, allowing for better credit risk assessment and reducing the need for collateral [4][5]. - The shift to digital banking has improved the credit accessibility for SMEs, particularly in remote areas, and has significantly shortened loan approval times [5][6]. - Digitalization has also improved banks' monitoring capabilities, enabling real-time oversight of enterprises and enhancing investment efficiency [6]. Group 3: Existing Challenges - There remains a "digital divide" where many SMEs lack the necessary digital infrastructure and skills to fully utilize online financing options [7]. - Data security and privacy concerns are increasingly prominent as banks handle sensitive enterprise information, raising risks of data breaches [8]. - Some enterprises, particularly medium-sized ones, face difficulties in securing funding for growth, missing opportunities to scale up [8]. Group 4: Policy Recommendations - It is recommended to strengthen digital inclusivity by enhancing digital infrastructure and supporting SMEs in improving their technological capabilities [9]. - Legislative measures should be taken to improve data security laws, ensuring comprehensive protection throughout the data lifecycle [9].