此次数据资产质押融资的落地，是政企银三方协同创新的成果，更是破解中小企业融资难题、激活数据 要素市场的重要突破。传统融资模式中，企业往往因缺乏有形抵押物面临融资困境，而数据质押融资则 为企业打开了新的融资通道：一方面，它打破了"数据资源"与"金融资本"之间的壁垒，让沉淀的数据资 产转化为企业发展的"真金白银"，为中小企业数字化转型和技术创新注入金融活水；另一方面，它推动 金融机构创新服务模式，从传统的抵质押评估转向数据资产价值评估，从而推动金融行业提升对数字资 产的认知与服务能力。 对于产业升级而言，"AI感知预测模型"的实践探索，不仅让企业充分挖掘自身数据资源的战略价值，更 推动全社会数字化转型向纵深发展。西海岸公用集团的实践证明，数据资产确权、评估、质押的全流程 可落地、可复制，其构建的风险防控体系也为行业提供了重要参考。 成立30年来，民生银行始终秉承"服务大众，情系民生"使命，坚持以客户为中心，持续守正创新。未 来，随着数据要素市场的不断完善，民生银行将持续深耕数据金融领域，推出更多定制化金融产品，为 企业数字化转型保驾护航，书写数字经济与实体经济融合发展的新篇章。 来源:金融界资讯 在数字经济浪潮奔 ...

Core Insights - Qingdao aims to transform public data from "sleeping resources" to "flowing assets" to drive high-quality urban development through institutional building, platform establishment, scenario expansion, and ecosystem cultivation [1][2][6] Institutional Innovation - Qingdao is constructing a "1+1+N" data foundational institutional system by 2025, including the first local comprehensive data regulation, the "Qingdao Data Regulation (Draft)," which has passed the first review by the local legislature [2] - The city has developed a full lifecycle management system for data assets, facilitating data resource registration, asset evaluation, and revenue distribution, leading to the first administrative data product transaction in the national transportation sector [2] Platform Support - Qingdao has been approved as one of the first national data industry aggregation area pilot cities, establishing a provincial data circulation infrastructure hub that connects with eight other cities [3] - The city has launched specialized platforms for public data operations, including the "Port and Shipping Zone" and "Electronic Guarantee Zone," enhancing targeted data development [3] Scenario Empowerment - Qingdao has initiated a "Data Element ×" award program, attracting 194 entries in a competition, with 55 winning provincial awards and 3 national awards, creating 173 application scenarios across various fields [4] - The city has facilitated over 35 billion yuan in loans for more than 25,000 enterprises through credit data, supporting market entities [4] Ecosystem Cultivation - Qingdao has established a data enterprise database and developed an industrial map, creating a collaborative development pattern among various parks and attracting data industry chain enterprises [5] - The city has initiated various training and exchange activities, establishing a data element cultivation center and promoting data asset recognition across multiple regions [5] Future Outlook - By 2026, Qingdao plans to deepen market-oriented reforms in public data resource utilization, enhancing institutional frameworks, platform support, application scenarios, and industrial ecosystems to establish itself as a national data resource aggregation and trading center [6]

Core Insights - Data has become an indispensable strategic resource for enterprises, often referred to as the "new oil" of business development. Efficient data collection, scientific analysis, and effective utilization are essential for driving decision-making, optimizing operations, and unlocking innovation [1] Group 1: Necessity of Data-Driven Management - The rapid development of IoT, big data, and AI is driving a comprehensive digital transformation in the global economy, resulting in massive data generation across all operational aspects of businesses [2] - Traditional management models relying on experience and intuition are becoming inadequate in the face of explosive data growth and rapidly changing market conditions, leading to slower responses and inaccurate judgments [2] Group 2: Core Elements of Data-Driven Management - **Data Resource Optimization**: Companies are shifting focus from merely pursuing advanced models to deeply optimizing their unique internal data resources, which are crucial for AI application and differentiated innovation [3] - **Technological Empowerment**: Advanced technologies like AI, machine learning, and big data analytics serve as the engine for data-driven management, enabling precise market trend predictions and operational insights [4] - **Talent Development**: There is a growing need for composite talents who understand both business and data, with positions like data scientists experiencing significant growth in demand [6] Group 3: Practical Pathways for Data-Driven Management - **Precision Decision-Making**: Companies should establish data-based decision-making mechanisms, integrating data analysis into strategic planning, market expansion, and product iteration [7] - **Process Optimization**: Businesses should utilize data to identify and eliminate redundant processes, enhancing efficiency in production, supply chain management, and financial operations [8] - **Risk Prevention**: A data risk warning system should be established to capture potential market, credit, and operational risks in real-time [9] - **Value Creation**: Companies need to leverage data as a core driver for innovation in business models and services, enhancing customer engagement and operational efficiency [10] Group 4: Challenges and Responses in Data-Driven Management - **Data Security and Privacy**: Companies must strengthen data security measures to prevent breaches and ensure compliance with legal regulations [11] - **Data Quality and Governance**: Establishing stringent data quality standards and governance frameworks is essential to avoid misleading decisions due to low-quality data [12] - **Technological Iteration and Talent Shortage**: Companies should invest in R&D and collaborate with educational institutions to keep pace with rapid technological advancements and address talent shortages [13] Group 5: Future Outlook for Data-Driven Management - The latest accounting standards require companies to recognize data resources as assets, marking a significant step towards data assetization. Several companies have begun to disclose the monetary value of their data resources [14] - The emergence of financialization cases for data assets indicates new financing channels for businesses, driven by technological advancements and regulatory frameworks [15] - Embracing a data culture and building core competitive capabilities will be crucial for companies to navigate the challenges and opportunities in the digital economy [16]

Core Insights - China's data technology development has entered a new phase of systematic layout and collaborative promotion, with efforts to cultivate various data circulation service institutions and accelerate the construction of an open, shared, and secure national integrated data market [1][5] Group 1: Data Market Development - The marketization and efficient utilization of data are core paths to activate the multiplier effect of the digital economy, with data exchanges playing a crucial role in connecting data supply and demand [2] - The National Data Bureau has categorized data circulation service institutions into three types, marking a new stage in the construction of the data factor market [2][3] - Data exchanges are essential components of the national integrated data market, and their future development should focus on "three deep integrations" to clarify their functional positioning and innovation direction [2][6] Group 2: Types of Data Circulation Service Institutions - Data circulation service institutions are evolving, with a need to include platform enterprises and data merchants in the research scope beyond just data exchanges [3] - Data exchanges are exploring the establishment of a full-chain service system for data circulation transactions, but their current role and transaction scale are still limited [3] - Industry data integration and utilization models are being accelerated by data circulation service platform enterprises, which focus on value co-creation through data sharing and exchange [4] Group 3: Role of Data Merchants - Data merchants, as key players in data production and operation, are actively gathering data resources and developing data governance and trading practices [5] - They are innovating in exploring new data circulation transaction models, such as high-quality data sets and data-as-a-service models [5] Group 4: Policy Recommendations for Data Exchanges - Data exchanges should deeply integrate with the development of the real economy, assisting enterprises in data utilization and assetization [7][8] - They should also support public data transactions by providing compliance review and valuation services [8][9] - The construction of data circulation infrastructure is crucial for enhancing the efficiency of data market operations [10][11] Group 5: Innovation and Regulation - Safety, regulation, and innovation are essential for the sustainable development of the data market, with data exchanges needing to establish norms and promote innovative practices [11][12] - A systematic policy framework is necessary to support the long-term development of data exchanges, focusing on capability building and ecosystem cultivation [13][14]

Core Insights - Guangdong Yuehai Feed Group Co., Ltd. has successfully launched the "Customer Credit Risk Assessment Data Product," marking a significant milestone in the aquaculture industry by obtaining the first national data property registration certificate [2][4] - The product aims to address common challenges in the aquaculture sector, such as customer dispersion and high breeding risks, thereby facilitating financial credit and improving capital turnover [2][3] Company Overview - Yuehai Feed is a leading enterprise in the aquaculture feed industry, ranking among the top three in the special aquatic feed sector, with over 70% of its sales coming from special feeds [2] - For the first three quarters of 2025, the company reported a revenue of 4.997 billion yuan and a net profit of 26.198 million yuan, representing year-on-year growth of 12.18% and 138.86%, respectively [2] Product Features - The "Customer Credit Risk Assessment Data Product" transforms vast amounts of data from the company's ERP system into compliant and tradable data assets [3] - The product features three core technological innovations: dynamic assessment for real-time risk control, comprehensive customer profiling for enhanced risk insight, and intelligent decision-making to improve credit efficiency [3] Industry Impact - The launch of this data product represents a breakthrough in data assetization for Yuehai Feed, extending internal information technology achievements to core business decision-making and financial management [4] - As the first in the national aquaculture industry to obtain data property registration, this product sets a replicable example for the industry to promote data productization and assetization [4] Regional Significance - Yuehai Feed is the first private enterprise in Zhanjiang to receive data property registration, contributing to the city's recognition as one of the top 100 cities in Guangdong for data factor market development [4] - The breakthrough establishes a digital benchmark for Zhanjiang's data trading service base and injects new momentum into the region's digital economy [4] Future Prospects - With the maturation of the data factor market, Yuehai Feed aims to transform into a data factor enterprise, collaborating with industry partners to create a data space for the aquaculture feed sector [4][5] - The company plans to leverage its core data system, supported by over 30 subsidiaries, to enhance competitiveness and promote the integration of smart agriculture and fisheries [5]

Core Insights - The article highlights a significant milestone in the aquaculture feed industry with the launch of the "Customer Credit Risk Assessment Data Product" by Yuehai Feed, marking the first data property registration in the water industry in China [1][3] Group 1: Company Achievements - Yuehai Feed has become the first private enterprise in Zhanjiang to obtain data property registration, indicating a pioneering step towards data assetization in the aquaculture sector [1] - The company reported a revenue of 4.997 billion yuan and a net profit of 26.198 million yuan for the first three quarters of 2025, reflecting year-on-year growth of 12.18% and 138.86% respectively [1] - The core shrimp and crab feed products of Yuehai Feed experienced a year-on-year growth rate exceeding 20% [1] Group 2: Industry Context - The aquaculture industry in China has surpassed a production value of 1.3 trillion yuan in 2023, with projections to reach 1.7 trillion yuan by 2028 [1] - The industry faces challenges such as customer dispersion, high farming risks, and difficulties in credit assessment, which hinder financial credit and fund circulation [1] - The data product aims to address these common pain points, facilitating financial credit and promoting high-quality development in the industry [1] Group 3: Technological Innovations - The data product leverages three core technological innovations: dynamic assessment for real-time risk control, comprehensive risk profiling through over 20 data dimensions, and intelligent decision-making to enhance credit efficiency [2] - The system updates customer credit scores daily using cloud computing, ensuring timely and accurate data [2] - The product not only identifies credit risks but also supports core business operations such as customer selection and credit strategy optimization, thereby reducing bad debt losses and improving cash flow efficiency [2] Group 4: Future Outlook - The data property registration and product launch represent a critical breakthrough for Yuehai Feed, extending internal information technology achievements to core business decision-making and financial management [3] - The company aims to evolve into a data factor enterprise, collaborating with industry partners to create a data space for the aquaculture feed sector, thus advancing digital and intelligent transformation [3] - Yuehai Feed is positioned to become a representative "data factor enterprise" in the industry, seizing opportunities in the wave of digital transformation [3]

Core Viewpoint - Guangdong Yuehai Feed Group has launched the first data product in the national aquaculture industry, aimed at addressing the challenges of credit assessment in aquaculture [2][3]. Group 1: Product Launch and Significance - The "Customer Credit Risk Assessment Data Product" was officially launched on January 14, 2026, at the Guangzhou Data Exchange, marking a significant milestone in the aquaculture sector [2][5]. - This data product is the first of its kind to be traded in the national aquaculture industry, facilitating the path for data assetization in the sector [3][4]. - The product has successfully passed the review by the Guangzhou Data Exchange and has obtained the first data property registration certificate in the aquaculture industry [7][9]. Group 2: Technical Innovations and Features - The core of the data product involves transforming data accumulated from the ERP system into compliant data assets, with a focus on calculating customer credit coefficients and risk factors through risk control models [10][11]. - Key technological innovations include: 1. Dynamic assessment using cloud computing to update customer credit coefficients daily, ensuring real-time risk management [13][14]. 2. Precise profiling that integrates over 20 data dimensions to generate visual risk control reports, aiding in comprehensive risk assessment [15]. 3. Intelligent decision-making that automatically calculates credit limits based on configurable rules, enhancing the efficiency and scientific basis of credit decisions [16]. Group 3: Industry Application and Benefits - The data product addresses the unique challenges of the aquaculture industry, such as customer dispersion, high farming risks, and difficulties in credit assessment, by enabling precise identification and dynamic management of customer credit risks [18][19]. - Its application directly supports customer screening and optimization of credit strategies, helping to reduce bad debt losses and improve capital turnover efficiency [20][21]. - The successful registration signifies a key breakthrough for Yuehai Feed in data assetization, with plans to continue advancing the productization and assetization of accumulated data across various dimensions [27][28].

Core Insights - Jiangsu Province has officially released the first batch of data enterprises for cultivation, with Suning.com being recognized for its outstanding performance in data resource integration, technological innovation, and industry empowerment [1][4]. Group 1: Company Recognition - Suning.com has been included in the first batch of data enterprises in Jiangsu Province, categorized under three cultivation types: data application, data technology, and data resources [2][5]. - The company holds a certificate valid until December 2029, indicating its commitment to data-driven initiatives [2]. Group 2: Data-Driven Initiatives - As a leading enterprise in the retail industry, Suning.com has accumulated vast data resources over more than 30 years, focusing on data-driven business innovation [4]. - The company is actively participating in national initiatives related to data elements and the "AI + Manufacturing" strategy, developing core data products such as commodity transaction datasets and a supply chain financial platform [4][5]. Group 3: Technological Advancements - Suning.com has developed its own retail domain "LingSi" large model, achieving breakthroughs in inference efficiency and training cost reduction through key technological upgrades [5]. - The company has created a "Retail Cloud County Town Smart Internet Platform," which serves over 15,000 county and town merchants, facilitating the digital transformation of grassroots commerce [5]. Group 4: Future Directions - Suning.com aims to deepen the market-oriented reform of data elements and accelerate the application of AI technologies in the physical industry, contributing to the establishment of a digital economy and advanced manufacturing integration demonstration zone in Jiangsu [5].

Core Insights - The article highlights a significant shift in the Chinese large model industry, with application projects accounting for nearly 60% of the market, indicating a transition from technical competition to value validation in commercial scenarios [1][3][25] - In 2025, the number of large model-related bidding projects reached 7,539, with a disclosed amount of 29.52 billion yuan, marking a dramatic increase of 396% and 356% compared to 2024 [1][3] - The report emphasizes the importance of industry-specific knowledge and high-quality private data as key competitive advantages in the evolving market landscape [19][20] Market Trends - Application projects dominated the bidding landscape, comprising 58% of the total projects, with a peak of 63% in November 2025 [1][5] - The trend shows a quarterly increase in application project share from 44% in Q1 to 61% in Q3, stabilizing at 60.5% in Q4 [5] - The highest monetary share came from computing projects at 52.9%, but their quantity share was only 27%, indicating a preference for direct procurement of computing power and existing models for application development [5] Industry Distribution - The top five industries by project quantity were education, government, telecommunications, energy, and finance, with the government sector leading in monetary share at approximately 40% [5] - The financial sector showed a notable shift from computing investment to application deployment in the latter half of 2025 [5] Vendor Landscape - Major players in the bidding market included general large model vendors like iFlytek, Baidu, Volcano Engine, and Alibaba Cloud, alongside specialized vendors like Zhongguancun KJ, which focused on niche markets [6][11] - Zhongguancun KJ ranked fourth among financial industry large model vendors, showcasing its deep industry expertise and successful project implementations [13] Case Studies - Zhongguancun KJ's collaboration with China Shipbuilding Group led to the development of a large model for the shipbuilding industry, integrating a vast knowledge base and enhancing operational efficiency [11][12] - In the finance sector, Zhongguancun KJ has served over 500 leading financial institutions, creating a comprehensive financial intelligent agent matrix that integrates AI capabilities into core business processes [13][14] Future Outlook - The market is expected to enter a "deep water zone" in 2026, where return on investment (ROI) will become a critical metric for evaluating AI projects [18] - The relationship between specialized vendors and general platforms is anticipated to evolve from competition to collaboration, fostering a symbiotic ecosystem [22][23]

Core Viewpoint - 汇东财金网 is a comprehensive listing service platform aimed at assisting Chinese SMEs in entering international capital markets, providing a full range of listing advisory services [1][3]. Group 1: Listing Services - The company offers various listing options including NASDAQ, Hong Kong, and domestic exchanges such as the main board, SME board, Sci-Tech Innovation board, and others [1]. - It also facilitates company listings on OTC markets and various local equity trading centers [1]. Group 2: Consulting Services - The firm provides comprehensive consulting services including business plan development, company valuation, strategic positioning, branding, business model design, top-level design, equity structure, and IPO path planning [2]. - It assists in financing through equity financing, debt financing, industry chain financing, and venture capital matchmaking [2]. Group 3: Data Services - 汇东财金网 offers data rights confirmation and assetization services, as well as traditional asset RWA blockchain integration and tokenized financing services in Hong Kong [3]. - The core value of the company lies in providing tailored advisory services to growth-oriented enterprises throughout various stages of their lifecycle, including IPOs, early-stage capital raising, and mergers and acquisitions [3].