Core Insights - The domestic data factor industry is evolving towards a higher value "government-industry linkage" model, driven by policy guidance and industrial construction [1] - The digital economy's core industries are becoming significant drivers of the overall economic system, with the data factor market expected to exceed 300 billion yuan by 2028, growing at a compound annual growth rate (CAGR) of approximately 20.26% [6] - The establishment of a data value circulation system is crucial for the efficient flow of data assets, with a focus on compliance and rights confirmation [11][13] Policy Analysis - The improvement of the data industry value chain and local data systems is essential for the circulation of data factors, marking a new phase of quality enhancement in the digital industry [3] - The "Data Twenty Articles" policy has initiated the construction of a data ownership system, which is vital for the efficient circulation of data value [11] Market Scale - The digital economy in China has grown from 27.2 trillion yuan in 2017 to 53.9 trillion yuan in 2023, with a CAGR of about 12.07% [6] - By 2025, the overall scale of the data factor industry is expected to reach around 200 billion yuan, with data processing and analysis becoming the largest segment, projected to reach 144 billion yuan by 2028 [6] Data Value Chain Circulation - The construction of a data value circulation system is supported by advanced technology and regulatory compliance, focusing on the phased development of data value [8] - Data asset registration is crucial for the division of ownership and promoting the market circulation of data assets [13] - The establishment of a data evaluation policy framework is necessary for the accurate assessment of data value, which is essential for market circulation [16][17] Capitalization of Data Assets - The entry of data assets into financial statements marks a significant step in the capitalization of data factors, with the implementation of regulations starting January 1, 2024 [19] - The market for data asset transactions is characterized by a "cold inside, hot outside" distribution pattern, with off-market transactions dominating due to their flexibility [21] Industry Practices - The financial sector is expected to see a CAGR of approximately 19.06%, reaching over 100 billion yuan by 2028, driven by the integration of diverse data [32] - The industrial manufacturing sector is projected to grow at a CAGR of about 24.22%, with a focus on high-quality data sets and trusted data spaces [35] - The healthcare industry is anticipated to grow at a CAGR of around 23.69%, emphasizing the compliance and security of personal health data [37] Trends - The construction of high-quality data sets is crucial for the development of the artificial intelligence industry, transitioning from "point breakthroughs" to "holistic development" [40] - The establishment of trusted data spaces will be fundamental for ensuring the circulation and high-value application of data factors [43]

Core Viewpoint - The article emphasizes the importance of transforming "sleeping" data into active capital for enterprises, particularly small and micro enterprises, through government support and innovative financing solutions [1][12]. Group 1: Company Overview - Shandong Portong Data Intelligence Co., Ltd. focuses on the digital transformation of port logistics and has developed a series of digital products in smart logistics and smart ports [1]. - Established in 2019, the company has been engaged in data collection, processing, and external services, highlighting its commitment to leveraging data for business growth [1]. Group 2: Financing Process - Shandong Portong successfully obtained a 5 million yuan loan through a data asset pledge loan facilitated by the Yantai Big Data Bureau, addressing common financing challenges faced by small enterprises [1][11]. - The process involved several steps: inventorying data assets, confirming ownership and rights, valuing the data, and applying for loans, which took approximately three months to complete [11][12]. Group 3: Data Asset Management - The company identified 11 core data assets, including port resources and BIM model components, which were categorized and assessed for reuse and value [5][10]. - A third-party evaluation determined the value of these data assets at 10.0194 million yuan, which was crucial for securing the loan [10][11]. Group 4: Policy Support - In September 2024, Shandong issued guidelines to accelerate the market-oriented allocation of data elements, supporting eligible enterprises in data asset registration [4][13]. - The initiative has already seen over 30 enterprises in Yantai complete the data asset registration process, indicating a growing trend in data capitalization [14].

Group 1 - The company, Yihualu (300212), focuses on providing professional data asset entry services for various industry clients [1] - The company currently does not have any data assets for entry on its own balance sheet [1] - Investors are encouraged to pay attention to the company's publicly disclosed information for further details [1]

Group 1 - The company, Yihualu (300212), has accumulated a significant amount of data assets from large central state-owned enterprises, covering various industries such as energy, transportation, and manufacturing [1] - The company is capable of supporting data entry for hydropower stations, photovoltaic power stations, and thermal power stations from both consulting and technical tool perspectives [1] - Investors are encouraged to pay attention to the company's publicly disclosed information for further details on these developments [1]

Core Viewpoint - Century Hengtong (301428) has completed a data asset inclusion project for 2024 and disclosed it in its periodic report [1] Group 1 - The company has no other ongoing data asset inclusion projects at this time [1] - The company will adhere to information disclosure rules for any future project developments [1]

Group 1 - The development of artificial intelligence (AI) is expected to give rise to new job roles related to intelligent agents by next year, as highlighted by the National Federation of Industry and Commerce's AI Committee [1] - The AI Committee has been conducting research on key enterprises in representative cities since December last year, focusing on the integration of "industry + AI" and has formed multiple proposals and suggestions [1] - The committee aims to leverage AI technology to enhance productivity and promote industrial intelligence upgrades, capitalizing on local industrial advantages [1] Group 2 - The National Data Bureau has been promoting data openness and has implemented measures regarding data rights, circulation, and trading, with pilot projects in the Greater Bay Area [2] - The concept of "data assets on the balance sheet" is discussed, emphasizing that the true value of data lies in its usability and confirmation by customers, rather than merely listing it as an asset [2] - As national laws and regulations become more refined, data trading is expected to become more standardized and orderly, which is crucial for realizing data value [2] Group 3 - The evolution of AI is categorized into several stages: logical reasoning (1950-1980), knowledge reasoning (1980-2000), deep learning (2000-2020), and the current AIGC stage starting in 2023 [3] - The AI industry has transitioned from voice recognition companies to image processing and machine vision firms, culminating in the emergence of generative AI led by companies like DeepSeek and Baidu [3] - The focus is on promoting AI applications while ensuring safety, with efforts to showcase successful industry cases and enhance AI platform construction [3]

在他看来，上市公司确实有一部分数据资产应该入表，因为有一些数据确实是会有价值的，但大部分的 数据在确权上也面临边界模糊的问题，相信未来在交易上会越来越规范，这也是关键所在。（文猛） 新浪科技讯 8月6日上午消息，今日举办的第十三届互联网安全大会（简称ISC.AI 2025）上，全国工商 联人工智能委员会常务秘书长范丛明在与新浪科技沟通中表示："社会主义公平的体现在于要素公平， 过去说的是土地均匀分配，现在数据作为一个重大要素，他的有效供给非常重要，所以行业协会作为未 来数据要素供给的一个重要抓手，下一步我们的重要工作就是作为党委政府推动数据治理的重要桥梁， 推动数据确权流转、规范治理。 对于企业数据资产入表，范丛明表示，"作为2023年底兴起的热门议题，我觉得最大的价值在于客户确 认的价值，一个数据不断的流转没有价值，数据跟土地不同的地方就是这样，土地属性是唯一性，但数 据属性是可复制性的，最终我还是要发挥数据要素的价值。" 责任编辑：石秀珍 SF183 ...

Core Insights - The first approved data asset securitization project in China, "Huaxin-Xinxin-Data Asset 1-5 Phase Asset Support Special Plan," was officially issued on July 31, marking a significant step in recognizing data as a new asset class in the capital market [1][2] - The project demonstrates the feasibility of using data assets as collateral for financing, breaking the traditional reliance on physical assets and providing a new financing pathway for asset-light data companies [2][3] - The penetration rate of data asset recognition in financial statements is increasing, with a notable rise in the number of listed companies recognizing data assets, indicating a growing acknowledgment of data value [3][5] Data Asset Securitization - The launch of data asset securitization projects this year reflects the capital market's high recognition of data as a new asset class and serves as a breakthrough in facilitating the conversion of data from resources to assets to capital [2][3] - The first data asset-enabled securitization product was issued on July 17, further enriching the asset securitization product matrix and providing new financing options for technology-driven enterprises [1][2] Data Asset Recognition - Data asset recognition in financial statements is essential for the capitalization and marketization of data assets, with the implementation of new accounting regulations set to normalize this practice starting January 1, 2024 [2][3] - The number of listed companies recognizing data assets has significantly increased, from 12 companies with a total of 0.54 million yuan in Q1 2024 to 82 companies with a total of 33.43 million yuan in Q1 2025 [3][5] Market Ecosystem Optimization - Companies are encouraged to strategically plan their data asset management and establish comprehensive internal management systems to optimize the market ecosystem for data assets [5] - The establishment of data asset companies in China has surged, with 3,553 companies currently operating in this sector, indicating a growing market for data asset services [4]

Group 1 - The core viewpoint of the articles emphasizes the importance of data as a key production factor in the digital economy, with the release of standardized contract templates aimed at facilitating data circulation and transactions [1][2] - The standardized contract templates are designed to lower transaction costs, establish trust, and prevent disputes by clearly defining responsibilities and rights within data transactions [2][3] - The templates cover four typical data circulation scenarios: data provision, data entrusted processing, data fusion development, and data intermediary services, providing a framework for businesses to engage in data transactions [3] Group 2 - The initiative aims to promote a fair competitive environment by protecting the interests of all parties involved in data transactions and fostering a cooperative atmosphere [2] - The implementation of the standardized contracts aligns with existing laws and regulations, ensuring compliance and enhancing the security of data transactions [2] - The clarity in ownership and rights provided by the templates is expected to reduce concerns among businesses regarding data asset ownership, thus encouraging data collaboration and innovation [3]

Core Viewpoint - In the digital economy era, data is transforming from an intangible resource into a measurable, tradable, and manageable asset, becoming a new member of corporate balance sheets [1] Group 1: Data Asset Integration - Over 90 listed companies have integrated data assets into their 2024 annual reports, with a total scale of 2.495 billion yuan, compared to only 0.079 billion yuan from 17 companies in the first quarter of 2024 [1] - The integration of data assets into financial statements is reshaping the balance sheets of listed companies, with significant representation from the industrial and information technology sectors [2] - The first companies to integrate data assets include major telecom operators like China Mobile, China Telecom, and China Unicom, along with industrial firms such as Xiaoshangpin City, YTO Express, and Yunda Holdings [3] Group 2: Steps for Data Asset Integration - The process for a company to integrate data assets into its financial statements typically involves four steps: inventory of data assets, governance of data for integration, confirmation of data ownership, and measurement for accounting [4][5] - Companies must meet specific conditions for data asset integration, including legal control, predictable economic benefits exceeding 50%, and measurable costs [5][6] Group 3: Challenges and Considerations - Not all companies can smoothly integrate data assets due to policy restrictions, corporate concerns, and the current lack of a valuation system [1][10] - Common challenges include legal risks in data ownership, unclear data management processes, and discrepancies between expected and actual valuations [10][11] - The integration of data assets is not the end point but a starting point for value reconstruction, requiring clear data ownership and valuation systems to gain recognition from financial institutions [14] Group 4: Financial Implications - Integrating data assets can enhance a company's financial statements by capitalizing expenses, which may lead to increased short-term profits but could result in profit fluctuations in the long term due to amortization [12][13] - The potential for data asset depreciation and the subjective nature of data valuation can introduce uncertainties in financial reporting [17][18]