Group 1 - The core concept of Real Data Assets (RDA) and Real World Assets (RWA) represents innovative paths for compliant circulation of domestic data assets and digitization of cross-border assets, forming a "dual-wheel drive" model for corporate digital strategies [3][4] - RDA is defined as data resources legally owned or controlled by enterprises, which are processed in compliance, have clear business scenarios, and can generate economic benefits, forming standardized digital assets through specific institutional registration and encapsulation processes [4][19] - The RDA model emphasizes the integration of data with real-world assets, enhancing the value of data through compliance and market mechanisms, while RWA focuses on the tokenization of various real-world assets for global circulation [16][19] Group 2 - The statistics for listed companies' digital assets in 2024 indicate a growing trend in the recognition and valuation of data assets, reflecting the increasing importance of data in corporate financial statements [5][24] - The process of RDA involves several steps including data resource sorting, quality assessment, compliance checks, and accounting entries, which are crucial for the successful integration of data assets into corporate financial frameworks [8][9][10] - The legal and regulatory framework surrounding data assets is evolving, with various policies and guidelines being issued to standardize the management and valuation of data assets, ensuring compliance and transparency in the market [15][24] Group 3 - RWA is characterized by the tokenization of real-world assets, allowing for the creation of programmable and divisible digital representations of existing assets, which enhances liquidity and democratizes investment opportunities [16][18] - The comparison between RDA and RWA highlights their distinct characteristics, with RDA focusing on data assets within domestic markets and RWA encompassing a broader range of asset types for global trading [19][20] - The advantages of RDA include optimizing financial statements and enhancing corporate competitiveness, while RWA improves asset liquidity and reduces financing costs, thereby broadening funding channels [20][21] Group 4 - The exploration of the "A+H" model suggests that companies can leverage domestic RDA for compliance and asset confirmation while establishing offshore structures to meet international regulatory requirements, facilitating global asset strategies [22][23] - The significance of digital asset realization for listed companies lies in its potential to enhance corporate valuation and optimize financial conditions, while also promoting market development and resource allocation efficiency [24]

Core Insights - The data exchange market in China has rapidly evolved since 2015, with over 50 data trading institutions established by July 2025, and the trading scale projected to exceed 300 billion yuan by 2025 [2][4][19] - Data exchanges serve as a regulated marketplace for data, allowing for the standardized transformation of data products and facilitating compliance and quality assurance [3][5] - The market is characterized by a diverse range of participants, including government entities, data service providers, and large internet companies, with buyers spanning various industries such as finance, healthcare, and AI [5][6] Group 1: Market Development - The trading scale has grown from "billion-level" in 2015 to "trillion-level" by 2024, indicating significant growth in both quantity and quality of data transactions [2][19] - The market is expected to reach approximately 2.841 trillion yuan by 2025, with a compound annual growth rate of 46.5% from 2021 to 2025 [19][34] - The introduction of policies and frameworks, such as the "Data Element ×" three-year action plan, aims to enhance the coordination between on-site and off-site trading by 2026 [6][10] Group 2: Key Players and Institutions - Major data exchanges include Beijing International Data Exchange, Shanghai Data Exchange, Shenzhen Data Exchange, and Guizhou Data Exchange, which are leading the market [4][7][12][15] - By June 2025, Beijing International Data Exchange had achieved a trading scale of 2,250 TB, with an annual growth rate exceeding 200% [12] - Shanghai Data Exchange reported over 2,000 signed data merchants and a trading amount exceeding 50 billion yuan in 2024 [13] Group 3: Emerging Trends and Technologies - The data trading landscape is expanding into new fields such as AI model training, medical diagnostics, and scientific research, reflecting the increasing importance of data in driving technological and economic development [20][34] - The introduction of advanced technologies like blockchain and privacy computing is enhancing the security and traceability of data transactions [22][28] - Data assetization is becoming a significant trend, with projections indicating that the market for data assets will reach 8,278 billion yuan by 2030 [19][34] Group 4: Case Studies - Notable case studies include the successful assetization and financing of data by companies like BAIC New Energy and the implementation of the "U235" framework by Shanghai Data Exchange, which utilizes blockchain for transparency and efficiency [24][27] - Shenzhen Power Supply Bureau's data product for enterprise electricity behavior was successfully traded, showcasing the application of privacy computing in data transactions [31] - The collaboration between Southern Power Grid and a chemical group demonstrates the practical benefits of data trading in optimizing production and reducing costs [32]

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]

证券日报网讯世纪恒通（301428）8月6日在互动平台回答投资者提问时表示，公司2024年已完成一项数 据资产入表工作并在定期报告中进行了披露。目前公司暂无其他正在推进的数据资产入表项目，后续如 有相关项目进展，公司将严格按照信息披露规则及时履行披露义务。 ...

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]