香港交易及結算所有限公司及香港聯合交易所有限公司對本公告的內容概不負責，對其準確性 或完整性亦不發表任何聲明，並明確表示，概不對因本公告全部或任何部份內容而產生或因倚 賴該等內容而引致的任何損失承擔任何責任。 百融雲創 （於開曼群島註冊成立以不同投票權控制的有限責任公司） （股份代號：6608） Bairong Inc. 盈利警告 本公告由百融雲創（「本公司」，連同其附屬公司及綜合聯屬實體統稱「本集團」）根 據香港聯合交易所有限公司證券上市規則（「上市規則」）第13.09條及香港法例第 571章證券及期貨條例第XIVA部項下之內幕消息條文（定義見上市規則）而作出。 股東及投資者於買賣本公司股份時務請審慎行事。 本公司董事（「董事」）會（「董事會」）謹此通知本公司股東（「股東」）及潛在投資 者，基於對本集團截至2025年12月31日止年度的未經審核綜合管理賬目及董事會 目前可得資料的初步評估，本集團預期於截至2025年12月31日止年度錄得未經審 核淨利潤約人民幣66.5百萬元至人民幣79.8百萬元，較截至2024年12月31日止年 度（約人民幣266.0百萬元）下降約70%至75%。該下降主要由於： 1 i. ...

Group 1 - The core viewpoint is that the Spring Festival marks a turning point for the widespread adoption of AI among consumers, with applications evolving from Chat to Agent [1][2] - The competition among internet giants for AI traffic entry is intensifying, and the integration of multiple business lines along with AI empowerment may drive performance and valuation [1][2] - Recommended companies include Alibaba-W and Baidu Group-SW, which are expected to benefit from the continuous improvement of open-source model capabilities and the rapid growth of domestic AI chips [2][5] Group 2 - OpenAI's revenue is projected to exceed its previous target, with a potential valuation of $850 billion following a $100 billion funding round [3] - Google's Gemini3.1Pro has significantly improved its performance in abstract reasoning tests, surpassing competitors like GPT-5.2 and Claude Opus4.6 [3] - Domestic AI companies like Zhiyu and MiniMax have seen substantial stock price increases, reflecting market recognition of their new large models [4] Group 3 - The investment recommendation emphasizes the commercialization of AI and the expansion of application scenarios, with a focus on companies benefiting from IT spending in state-owned enterprises [5] - In the automotive and autonomous driving sectors, the approval of domestic L3-level pilot licenses is expected to accelerate the commercialization of advanced driving technologies [5]

RWA 监管更加明晰，金融信息服务监管趋严 [Table_Industry] 综合金融 ——金融科技行业双周报第二十三期 | [姓名table_Authors] | 电话 | 邮箱 | 登记编号 | | --- | --- | --- | --- | | 刘欣琦(分析师) | 021-38676647 | liuxinqi@gtht.com | S0880515050001 | | 孙坤(分析师) | 021-38038260 | sunkun@gtht.com | S0880523030001 | 本报告导读： 国内大模型产品与营销均有亮点，带动金融科技相关标的受益，境外 RWA 监管明 细，金融信息监管趋严。合规金融机构更加受益。 投资要点： [Table_Report] 相关报告 综合金融《权益市场火热，居民边际配置权益资 产》2026.02.09 综合金融《境内虚拟货币违法，境外 RWA 监管 明晰》2026.02.08 综合金融《支付牌照缩减，多家投资咨询公司暂 停新增》2026.02.01 综合金融《消金监管趋严，行业加速出清》 2026.01.25 综合金融《业绩基准新规落地，助推行业长期发 展 ...

Investment Rating - The report assigns an "Overweight" rating for the financial technology sector [4]. Core Insights - The domestic large model products and marketing have shown highlights, benefiting related financial technology stocks. The overseas RWA regulation has become clearer, and financial information regulation is tightening. Compliant financial institutions are expected to benefit more [2]. Summary by Sections 1. AI - From February 2 to February 20, 2026, the financial technology index decreased from 3116.08 to 3093.77, with a return of -0.72%. The Hong Kong financial technology index fell by 3.48% during the same period. Financial IT and third-party payment sectors performed well due to increased marketing efforts of major AI models and new regulations on virtual currencies [7][8]. 2. Overseas RWA Regulation - **2.1 Financial IT**: On February 6, the People's Bank of China and eight departments issued a notice to prevent risks related to virtual currencies and clarified the RWA regulatory framework for overseas issuance [12][13]. - **2.2 Financial Information Services**: On February 9, the Shanghai and Shenzhen Stock Exchanges announced optimized refinancing measures, benefiting high-quality R&D enterprises [14]. - **2.3 Third-party Payment**: New scenarios for digital currency have emerged, and the concentration of licenses in the third-party payment sector is accelerating [16]. - **2.4 Consumer Finance**: The head effect is evident, with a focus on promoting domestic demand through consumer finance [18]. 3. Individual Company News and Announcements - **3.1** Lakala is accelerating the development of intelligent payment through MOSS, while Tonghuashun's vertical model has gained high usage rates among brokers [19]. - **3.2** ST Rendo's net assets are expected to turn positive, and Jiufang Zhitu has initiated a stock buyback [21]. 4. Investment Recommendations - Digital RMB is expanding its application scenarios, indicating significant growth potential. AI is driving the upgrade of financial services, presenting new investment opportunities. Recommended core companies include: 1. Financial IT firms benefiting from digital currency upgrades: Changliang Technology, Yuxin Technology, Zhongke Software, and New Zhiyuan Software [24][28]. 2. Financial information service companies focusing on intelligent investment research: Jiufang Zhitu, Tonghuashun, and Dongfang Caifu [24][28]. 3. Payment institutions adapting to digital currency functionalities: Lakala, Yika, and Lianlian Digital [24][28]. 4. Consumer finance companies leveraging intelligent customer service and marketing: Yixin Group and Qifu Technology [24][28].

Core Insights - The article discusses the emergence of "silicon-based assistants" as a solution to the labor shortage faced by traditional industries during the long Chinese New Year holiday [3][4] - It highlights the shift from traditional SaaS (Software as a Service) models to RaaS (Results as a Service) models, emphasizing the flexibility and efficiency of AI-driven solutions [8][14] Group 1: Silicon-Based Assistants - Silicon-based assistants are defined as AI agents capable of perceiving their environment and taking actions to achieve specific goals, thus streamlining daily tasks for employees [5] - Baifeng Zhang, CEO of BaiRong Cloud, implemented a silicon-based assistant to manage daily operations, allowing executives to focus on core business activities [4][6] - The silicon-carbon ratio within BaiRong indicates that one carbon-based employee can manage approximately 150 silicon-based employees, showcasing the scalability of this model [6] Group 2: Transition from SaaS to RaaS - The RaaS model charges clients based on the results achieved through silicon-based employees, contrasting with the rigid fee structure of SaaS based on the number of human employees [8][14] - The article cites a16z's report indicating a fundamental shift in the SaaS industry, where AI agents are expected to replace human labor in various tasks, leading to a new operational paradigm [8][10] - BaiRong's Results Cloud platform is designed to align business outcomes with AI capabilities, effectively transforming traditional labor dynamics into a more flexible and efficient model [10][12] Group 3: Performance Metrics and Impact - BaiRong's Results Cloud has shown significant performance improvements, with flagship silicon-based roles achieving remarkable results, such as a 217% increase in conversion rates for sales [12] - The revenue growth of BaiRong Cloud reached 22% in the first half of 2025, with a stable gross margin of 73%, indicating the financial viability of the RaaS model [14] - The article emphasizes the importance of private data in training AI agents, which enhances their performance and strengthens the relationship between the platform and its clients [14][15]

Investment Rating - The report does not explicitly provide an investment rating for the financial agent industry Core Insights - The financial agent industry is experiencing a transformation driven by AI, particularly through the adoption of intelligent agents that enhance operational efficiency and decision-making capabilities in financial services [9][17] - The report highlights the limitations of large models in financial applications, such as lack of autonomous perception, decision execution fragmentation, and insufficient controllability, which intelligent agents aim to address [9][10] - The adoption of intelligent agents is expected to accelerate, with significant deployment planned across banks, securities firms, and insurance companies by 2025 [17] Summary by Sections Financial Agent Core Value - Intelligent agents create a closed-loop process of perception, reasoning, planning, execution, and evolution, overcoming the limitations of large models [9] - They enable end-to-end automation of complex financial processes, integrating multiple tools and roles for improved collaboration [10] Financial Agent Application Scenarios - Intelligent agents are being applied in various financial sectors, including: - Banking: Credit risk management, customer qualification screening, and account management [12] - Securities: Research report interpretation, investment advisory, and market analysis [13] - Insurance: Product development, claims processing, and customer service [15] - The report indicates that intelligent agents have penetrated core business scenarios, significantly enhancing operational efficiency and risk management [17] Financial Agent Deployment Status - As of now, 25.0% of banks, 22.2% of securities firms, and 13.6% of insurance companies have adopted intelligent agent technology, with plans for further deployment in the coming year [17] - The report notes that the banking sector has the highest adoption rate, particularly in retail and credit risk management [17] Challenges in Financial Agent Implementation - Key challenges include data quality and security issues, technological foundation limitations, high deployment costs, and a shortage of skilled talent [19] - The report emphasizes the need for improved data management and collaboration mechanisms to facilitate the effective use of intelligent agents in financial services [19] Financial Agent Participants Landscape - The market features a mix of general vendors (e.g., Baidu, Alibaba) and specialized vendors (e.g., Ant Group, Financial Star) competing in the financial agent space [20][21]

Investment Rating - The report does not explicitly provide an investment rating for the financial agent industry Core Insights - The financial agent industry is poised for rapid transformation, with a significant increase in demand for AI-driven solutions across financial institutions. Currently, 25.0% of banks, 22.2% of securities firms, and 13.6% of insurance companies have adopted agent technology, with plans for further deployment in the coming year [16] Summary by Sections Financial Agent Core Value - The integration of large models into the financial sector enhances efficiency but has limitations such as lack of autonomous perception and environmental interaction, decision execution fragmentation, and insufficient controllability. Financial agents create a closed loop of "perception → reasoning → planning → execution → evolution" to reconstruct business processes and overcome the black-box nature of large models [8] Financial Agent Application Scenarios - Financial agents are applied in various scenarios including credit risk control, due diligence report generation, customer qualification screening, account management, and marketing strategies across banking, securities, and insurance sectors. For instance, in banking, retail and credit risk control are the primary application areas, accounting for 34.6% and 25.5% respectively [11][16] Financial Agent Deployment Status - By 2025, the financial agent industry is expected to enter an accelerated phase of intelligent transformation, with significant adoption across financial institutions. The report indicates that 37.5% of banks, 40.7% of securities firms, and 31.8% of insurance companies plan to accelerate deployment within a year [16] Challenges in Financial Agent Implementation - Key challenges include data quality and security issues, technological foundation challenges, high deployment costs, and a shortage of skilled talent. The financial sector faces difficulties due to heterogeneous data sources, lack of collaboration mechanisms, and the need for real-time data analysis to support intelligent decision-making [18] Financial Agent Participants Landscape - The competitive landscape of financial agents includes general vendors like Baidu and Alibaba, as well as vertical vendors such as Ant Group and other specialized firms. This indicates a diverse ecosystem of players contributing to the development and deployment of financial agent technologies [19]

智通财经APP讯，百融云-W(06608)公布，2026年2月13日耗资约246.99万港元回购21.2万股股份。 ...

格隆汇2月13日丨百融云-W(06608.HK)公告，2月13日耗资247万港元回购21.2万股。 ...

FF305 翌日披露報表 (股份發行人 ── 已發行股份或庫存股份變動、股份購回及/或在場内出售庫存股份) 表格類別： 股票 狀態： 新提交 公司名稱： 百融雲創 (於開曼群島註冊成立以不同投票權控制的有限公司) 呈交日期： 2026年2月13日 如上市發行人的已發行股份或庫存股份出現變動而須根據《香港聯合交易所有限公司（「香港聯交所」）證券上市規則》(「《主板上市規則》」)第13.25A條 / 《香港聯合交易所有限公司GEM證券 上市規則》(「《GEM上市規則》」)第17.27A條作出披露，必須填妥第一章節 。 | 第一章節 | | | | | | | | --- | --- | --- | --- | --- | --- | --- | | 1. 股份分類 | 不同投票權架構公司普通股 | 股份類別 B | | 於香港聯交所上市 | 是 | | | 證券代號 (如上市) | 06608 | 說明 | | | | | | A. 已發行股份或庫存股份變動 | | | | | | | | | | 已發行股份（不包括庫存股份）變動 | | 庫存股份變動 | | | | | 事件 | 已發行股份（不包括庫存股份）數 ...