近期，中国银行、建设银行、南京银行、广发银行等多家银行机构，集中启动2026年度博士后研究人员 招聘工作。与以往相比，此次招聘聚焦人工智能、金融科技，凸显银行对"金融+科技"复合型人才的迫 切需求。 南开大学金融学教授田利辉表示，这一趋势更折射出银行业人才需求的深层变革，即从"单一技 能"向"跨界融合"转型、从"论文导向"转为"问题导向+价值创造"。银行愈发青睐"金融+科技"复合背景 人才，重视从业经验与专业资格，与高校侧重学术研究不同，银行更强调研究产出的可落地性、可审计 性，同时注重团队协作与行内跟岗实践，以此缩短科研成果向实际应用的转化链路。 11月18日，南京银行发布公告称，为匹配高质量发展需求，其博士后科研工作站公开招收2026年博士后 研究人员。报考者需近三年内在国内外获得博士学位或将于2026年7月份前毕业，年龄不超过35周岁； 专业背景需覆盖经济学、金融学、统计学、计算机、人工智能、金融科技等相关领域，且具备较强研究 能力与敬业精神，同等条件下，具有金融从业经验者优先考虑。 此前，广发银行也披露了2026年度博士后招聘计划，面向2024年1月份至2026年8月份毕业的博士研究生 开放申请，要求 ...

天眼新知|双十一购物节进入新常态：理性消费与产业协同驱动发展 2025年的"双十一"购物节再次以惊人的数据刷新了人们对中国消费市场的认知。开卖首小时内，天猫平台即有80个品牌成交额突破亿元，30516个品牌实 现成交额同比翻倍，而京东平台同期亦有超过5.2万个品牌成交额同比翻倍增长。走过16个年头的"双十一"，其意义早已超越单纯的促销活动，进化为观 察中国消费韧性、产业变革与技术创新最重要的窗口。 消费趋势变迁与品牌格局重塑，理性个性化选择驱动产业精准适配 2025年的双十一显示，消费行为正朝着更理性、更注重品质和个性化的方向演变。平台的营销策略也随之调整，普遍采用"官方立减"、"一件直降"等简化 规则替代复杂的凑单模式，以迎合消费者对透明实惠和便捷体验的追求。 品牌格局在双十一期间呈现出更显著的分化态势。一方面，具备强大数字化运营能力的新老国货品牌表现抢眼。另一方面，新品与技术仍是吸引消费者的 关键。品牌增长分化加剧，具备数字化运营能力的商家更能抓住销售窗口期，这也对品牌的综合能力提出了更高要求。 消费市场的细分与下沉趋势同样明显。"Z世代"、"小镇青年"等新兴消费群体带来多元化、个性化的细分需求。与此同时 ...

Core Insights - The "Double Eleven" shopping festival has evolved into a longer event, with major platforms extending the promotional period to over 30 days, reflecting a shift towards more rational consumer behavior [1][2] - AI technology is enhancing the shopping experience, allowing for personalized recommendations and improved efficiency for merchants, leading to the rise of niche markets [2][3] - Instant retail is becoming a significant trend, integrating online and offline resources to improve delivery efficiency and consumer satisfaction [3][5] Group 1: Changes in Consumer Behavior - This year's "Double Eleven" has seen a shift towards rational consumption, with consumers focusing more on quality rather than just price sensitivity [1] - Promotional strategies have simplified, moving away from complex calculations to more straightforward discounts, indicating a change in consumer expectations [1] - The use of professional knowledge and deep experiences in live streaming has become a competitive advantage for e-commerce platforms [1] Group 2: AI's Role in the Market - AI tools like "AI万能搜" and "AI清单" are addressing millions of consumer needs and providing customized shopping lists, significantly enhancing the shopping experience [2] - The shift in traffic logic from "explosive product recommendations" to "target audience matching" allows smaller merchants to gain visibility [2] - AI is also optimizing operational strategies for merchants, improving both service quality and efficiency [2] Group 3: Instant Retail Development - Instant retail has gained traction, with platforms like Meituan and Douyin facilitating rapid delivery from local stores, enhancing consumer convenience [3][4] - Over 30,000 brands and 400,000 stores have joined platforms like Taobao Flash Sale, demonstrating the integration of online and offline retail [5] - The collaboration between e-commerce platforms and physical retailers is creating a synergistic effect, driving digital transformation in the retail sector [5]

Core Insights - The article discusses the challenges faced by companies in implementing AI technologies, particularly the disconnect between high expectations from leadership and the practical limitations of AI applications [1][3][5]. Group 1: AI Implementation Challenges - Companies are experiencing "AI anxiety," where leadership has high expectations for immediate results from AI applications, leading to pressure on CIOs to deliver [1][3]. - There is a lack of integration in AI application scenarios, resulting in fragmented functionality and value, making it difficult for traditional enterprises to achieve systematic breakthroughs [2][4]. - The overhyped perception of AI as a universal solution has led to unrealistic expectations, with leaders often overlooking the complexities involved in AI implementation [3][5]. Group 2: Root Causes of AI Value Realization Issues - Cognitive biases among leadership lead to inflated expectations of AI's capabilities, causing projects to get stuck in a "high but not achievable" dilemma [5][6]. - Organizational challenges include the absence of a dedicated technical team and a lack of cross-departmental collaboration, resulting in AI projects being disconnected from actual business needs [6][7]. - The foundational issues encompass inadequate technical, management, and data infrastructure, as well as insufficient funding for sustained AI initiatives [7][8]. Group 3: Recommendations for Overcoming AI Implementation Barriers - Companies should learn from industry benchmarks by conducting field research on successful AI applications, focusing on real implementation paths and lessons learned [9]. - It is essential to engage in deep communication with business departments to clarify AI implementation goals and develop a strategic path that aligns with business needs [9]. - Starting with small-scale pilot projects can help validate technical paths and business value, avoiding the pitfalls of overextending resources at the outset [9].

Group 1 - The A-share market is currently consolidating, with mixed performance among the three major indices. The electric grid equipment sector rebounded in the afternoon, while large financial sectors like securities and insurance showed strength. Conversely, sectors such as computing hardware stocks, humanoid robots, and power equipment faced declines [1] - The AI ETF (515070) experienced a 2.4% drop during the trading session, with notable gains in stocks like Beijing Junzheng, Zhongke Xingtou, and 360, while stocks such as KYC Data, New Yisheng, and Cambricon Technologies saw significant declines. Over the past five days, the AI ETF attracted 326 million yuan [1] - The 2025 World Internet Conference in Wuzhen concluded, focusing on building an open, cooperative, secure, and inclusive digital future. The conference showcased the trend of AI transitioning from technology research to industrial application, with companies like Ant Group and Alibaba presenting multiple AI application results across finance, industry, and healthcare [1] Group 2 - Huaxi Securities pointed out that AI applications are shifting from general scenarios to more segmented and in-depth explorations, with industrial intelligence and digital transformation becoming key breakthrough areas. The continuous open-source iteration of domestic large models is accelerating the adoption of AI in vertical fields such as industry, education, and healthcare [2] - The AI ETF (515070) tracks the CS Artificial Intelligence Theme Index (930713), selecting component stocks that provide technology, basic resources, and application end stocks for artificial intelligence, focusing on the midstream and upstream of the AI industry chain, often referred to as the "robot brain" creators and the "infrastructure" of the Internet of Everything [2]

Core Insights - The report by PwC Strategy& highlights the revolutionary impact of artificial intelligence (AI) on the retail industry, emphasizing the potential for significant profit increases if AI is scaled and industrialized by 2030 [1] - It estimates that the global retail industry's annual operating profit could increase by $310 billion, with an overall profit growth rate nearing 20% [1] - Retail companies that implement AI across their organizations could see their operating profit margins rise from the industry average of 3% to 14.4%, representing a more than fourfold increase [1] Key Steps for Implementation - Adjust organizational structure to enable AI delivery, establishing a governance mechanism that aligns with AI strategy [2] - Balance platform strategy with innovative tools, adopting a hybrid delivery model while retaining in-house development capabilities to ensure technology control [2] - Enhance data maturity and open access to strategic data assets, improving data management capabilities to solidify the AI foundation [2] - Actively address regulatory and ethical issues, ensuring compliance and ethical standards are met [2] - Foster a data culture and promote the use of data and AI among employees to enhance acceptance and ensure scalable implementation [2]

Investment Rating - The report maintains a "Buy" rating for the company, indicating a positive outlook for future stock performance [4][7]. Core Insights - The company's profitability has significantly improved due to cost reduction and efficiency enhancement measures. In Q3 2025, the company achieved revenue of 230 million yuan, a decrease of 11.32%, while net profit attributable to the parent company was 28 million yuan, a slight decrease of 0.58%. The net profit margin increased to 12.07%, up by 1.30 percentage points [1]. - The introduction of AI technology has enhanced service capabilities and operational efficiency, leading to a notable improvement in internal processes and a reduction in personnel needs. The company has successfully integrated AI into various operational areas, resulting in increased gross margins for online brand management and content e-commerce services [2][3]. - The company has expanded its client base, adding five well-known brands while maintaining stability with existing clients. This has contributed to a year-on-year growth of 14.86% in GMV for Q3 2025 [2]. Financial Summary - For the fiscal year 2023, the company reported a revenue of 1.288 billion yuan, a decrease of 16.31%, and a net profit of 108 million yuan, down by 40.05%. Projections for 2025 estimate revenue at 1.081 billion yuan and net profit at 145 million yuan, reflecting a significant recovery with a growth rate of 91.05% [5][11]. - The company's earnings per share (EPS) is projected to increase from 0.32 yuan in 2024 to 0.91 yuan in 2027, indicating a positive growth trajectory [5][11]. - The price-to-earnings (P/E) ratio is expected to decrease from 75.00 in 2024 to 33.38 in 2027, suggesting an improving valuation as earnings grow [5][11].

Core Insights - The EMNLP 2025 conference will be held in Suzhou, China, from November 4-9, 2025, focusing on breakthroughs in data-driven NLP technologies [1] - WeBank has three papers accepted at EMNLP, exploring federated large model frameworks, model compression, and knowledge transfer in reasoning [1] - WeBank is a pioneer in digital banking in China, committed to making financial services accessible to the public through technological innovation [2] Group 1 - WeBank is accelerating its transition from a "digital native" to an "AI native" bank, focusing on AI infrastructure, applications, and governance [2] - The bank has achieved a record high of nine papers accepted at top conferences in 2025, including EMNLP, NeurIPS, and CVPR [2] - WeBank led the development of the national standard GB/T 46284-2025 for federated learning technology, effective from October 5, 2025 [2] Group 2 - WeBank's AI research emphasizes a problem-oriented approach, aiming to address real industry pain points [3] - The bank has published over 50 papers in top international conferences, with technologies applied in financial risk control, intelligent customer service, and fraud prevention [3] - Future research will focus on transforming AI research outcomes into industrial value, contributing to a safe, efficient, and fair AI application ecosystem [3]

Core Viewpoint - The Ministry of Industry and Information Technology has named several companies, including Sogou Browser and iQIYI, for difficulties in connecting to human customer service, highlighting a significant issue in customer service management [2] Group 1: Customer Service Challenges - The shortage of human customer service representatives is attributed to high job pressure, intense workload, and frequent turnover [2] - The widespread adoption of intelligent customer service systems aims to reduce labor and management costs, but these systems often fail to understand customer inquiries, leading to increased communication costs and high complaint rates [2] Group 2: Need for Human Interaction - Improving the intelligence of customer service systems is a key area for enhancement, but personalized needs that exceed the capabilities of these systems still require human intervention [2] - Maintaining a reasonable proportion of human customer service is essential for preventing service quality degradation, which can lead to customer attrition and is also a responsibility to protect consumer rights [2]

Group 1: Conference Participation - The EMNLP 2025 conference will be held in Suzhou, China from November 4-9, 2025, focusing on breakthroughs in NLP technology [1] - WeBank has three papers accepted at EMNLP, exploring federated large model frameworks, model compression, and knowledge transfer in reasoning [1] Group 2: Company Strategy and Achievements - WeBank, as China's first digital bank, emphasizes the mission of making finance accessible to the public and is committed to technological self-reliance [3] - The bank is transitioning from a "digital native" to an "AI native" model, enhancing AI infrastructure and applications while establishing a robust AI governance system [3] - In 2025, WeBank achieved a record of nine papers accepted at top conferences such as EMNLP, NeurIPS, and CVPR, showcasing its research capabilities [3] - WeBank led the development of the national standard GB/T46284-2025 for federated learning technology, effective from October 5, 2025 [3] - The bank, in collaboration with Tongji University and Microsoft Research Asia, won the CCF Science and Technology Achievement Award in Natural Science, highlighting its technological innovation [3] Group 3: Research Focus and Future Plans - WeBank's AI research is guided by a problem-oriented approach, aiming to address real industry challenges, with over 50 papers published in top conferences [4] - The bank plans to continue deepening its AI core technology research, focusing on financial technology and smart living, to convert research outcomes into industrial value [4] - WeBank aims to provide leading technological solutions for building a "safe, efficient, and fair" AI application ecosystem [4]