证券日报网讯 2月27日，中国交建在互动平台回答投资者提问时表示，公司在交通基础设施的设计、建 设以及高速公路运营等领域深耕数十年，积累了丰富的数据资产，目前，公司正有序推进数据资产的梳 理、确权与价值评估工作，相关入表数据将在符合会计准则及信息披露要求的前提下，于定期报告中及 时披露。公司高度重视数据资产开发应用，将其作为数字化转型的重要抓手，持续释放数据要素价值。 （文章来源：证券日报） ...

Core Viewpoint - The article emphasizes the significant gap between the United States and China regarding the recognition and valuation of data as an economic asset, with China taking proactive steps to classify data as a production factor and implement data assetization practices [1][5]. Group 1: Data Valuation in the U.S. vs. China - The U.S. has a low valuation of data, while China has recognized data as an asset, implementing regulations that allow companies to classify qualifying data resources as intangible assets or inventory [1][5]. - The U.S. has not formally acknowledged the economic value of data, despite the fact that data brokers generate over $200 billion in revenue annually from information not reflected on corporate balance sheets [2][5]. - The U.S. legal system has recognized the value of customer data in bankruptcy cases, indicating that data can be one of the most valuable assets for companies [2][5]. Group 2: Government Data Governance Challenges - The U.S. federal data policy framework is disorganized, lacking a systematic approach to understanding and protecting data, which complicates the establishment of a data valuation framework [5][6]. - The article highlights the need for a structured approach to data valuation to enhance data protection and privacy, referencing past data breaches as evidence of the risks associated with unvalued data [5][6]. - The comparison between the U.S. and China illustrates a stark difference in data strategy, with China actively pursuing data assetization while the U.S. remains indifferent [5][6]. Group 3: Recommendations for U.S. Data Policy - The article suggests that the U.S. Financial Accounting Standards Board should initiate projects to establish standards for recognizing data assets, and the SEC should enhance research on data asset disclosure requirements [6]. - It calls for Congress to mandate federal agencies to assess the value of their data assets, with state and local governments encouraged to follow suit [6]. - The author argues that the current refusal to quantify data value in the U.S. overlooks a vast economic potential, as illustrated by the example of a $2 reward for survey participation, which could multiply across the entire population [6].

Core Viewpoint - The draft of the "State-Owned Assets Law" marks a significant milestone by officially recognizing data as an asset within the legal framework, addressing the long-standing issue of data ownership and valuation in China's digital economy [3][4][5][10]. Group 1: Legal Recognition of Data Assets - The "State-Owned Assets Law (Draft)" concludes public consultation on January 25, 2026, and will be reviewed by the National People's Congress, marking the first formal legal recognition of data assets [3][4]. - This law aims to establish a multi-layered regulatory framework for data asset management, addressing challenges in ownership, valuation, circulation, and security management [4][5][10]. - The draft law introduces a broad definition of "other state-owned assets," which includes data and other emerging asset types, reflecting a forward-looking legislative approach [4][5]. Group 2: Implications for Digital Economy - The recognition of data as a legal asset signifies a shift from viewing assets as tangible entities to recognizing intangible elements in the digital age, enhancing China's position in the global digital economy [6][10]. - The law provides a legal basis for the valuation, accounting, trading, and collateralization of data assets, which is essential for developing a unified and regulated data market [5][10][20]. - The draft law's provisions will facilitate the transition of public data from mere administrative records to valuable assets requiring strict management and security [7][18]. Group 3: Governance and Management Framework - The draft law outlines three key provisions that create a comprehensive governance framework for state-owned data assets, focusing on management responsibilities, capacity building, and legal status establishment [7][19]. - It mandates that government agencies actively manage data generated during their operations, thus clarifying ownership and regulatory boundaries for public data assets [7][18]. - The law emphasizes the need for a digital regulatory system that allows for real-time monitoring and analysis of data assets, moving towards a dynamic governance model [19]. Group 4: International Significance - The "State-Owned Assets Law (Draft)" is a pioneering effort globally, as no other country has yet established a legal framework that explicitly recognizes data as an asset [11][20]. - This legislative innovation is expected to play a crucial role in the development of data asset systems, marking a significant step in the evolution of digital governance [20].

Core Viewpoint - The recent joint announcement by four regulatory bodies aims to enforce stricter accounting standards for data assets, emphasizing cost measurement and enhancing cost management to curb valuation irregularities in data assets [1] Group 1: Regulatory Changes - The new regulations require companies to measure data assets based on actual costs incurred, eliminating the use of future value assessments, thereby preventing asset bubbles from forming [2] - Companies are prohibited from retroactively capitalizing previously expensed data resources, ensuring the authenticity and comparability of financial data [2] - An annual impairment test is mandated for data assets, requiring companies to assess and adjust the book value of data assets based on their current utility and potential obsolescence [2] Group 2: Information Disclosure - Companies must provide detailed disclosures regarding data asset classification, measurement methods, useful life, and impairment status, increasing transparency and reducing information asymmetry [3] - The new rules aim to enhance the reliability of financial data, thereby reducing the risk of investors falling into overvaluation traps when making investment decisions [3] - The regulations offer clear guidelines for auditing firms, enabling them to perform their roles more effectively and reducing the risk of professional judgment errors [3]

Core Insights - Data assets are identified as the core driving force behind the digital transformation of the manufacturing industry, particularly in Suzhou, where the release of data asset value is crucial for achieving high-quality industrial development [1][2]. Group 1: Data Asset Definition and Importance - The report outlines the basic connotation, classification system, and key characteristics of data assets, emphasizing that high-quality, governable, and structured data assets are essential for optimizing production and enhancing management efficiency [1]. - The evolution of data assets is described in three stages: "business dataization," "data resourceization," and "data assetization," highlighting the strategic resource role of data assets in intelligent decision-making and business model innovation [1][2]. Group 2: Technological Empowerment - The report analyzes how cutting-edge technologies such as blockchain, artificial intelligence (AI), and virtual reality (VR) empower data asset management, with blockchain ensuring data rights and trustworthy circulation, AI enhancing data analysis and application efficiency, and VR aiding in the construction of high-value digital knowledge assets [1][2]. - Practical applications in manufacturing, such as predictive maintenance and flexible customization, demonstrate how data assets can be effectively transformed into productivity, exemplified by a clothing company that achieved a 50% reduction in order response time and a 50% increase in capacity through an industrial internet platform [1]. Group 3: Challenges in Data Asset Management - Suzhou's manufacturing sector faces significant challenges in data asset management, including data silos due to non-unified equipment protocols, lack of standards leading to "one item, multiple codes," a shortage of professional talent, security concerns hindering data sharing, and unclear paths for realizing data asset value [2]. - The report proposes strategies to address these challenges, such as building an industrial internet ecosystem, solidifying data quality foundations, creating vertical domain corpora, and transitioning from "experience-driven" to "data-driven" approaches [2].

Core Insights - The report from Shanghai Jiao Tong University's Shanghai Advanced Institute of Finance indicates a steady growth in the data asset reporting of listed companies, although the growth rate has slowed compared to 2024 [1] Group 1: Non-Listed Companies - As of September 30, 2025, 375 non-listed companies in China have disclosed their data asset reporting, securing a total financing amount of 1.899 billion yuan, with a noticeable slowdown in growth [2] - Local state-owned enterprises are the main contributors to data asset reporting among non-listed companies, with 310 local state-owned enterprises accounting for 82.67% of the total, raising 1.710 billion yuan [2] - The types of businesses and data categories for non-listed companies that have reported data assets are diverse, with the leading sectors being information transmission, software and IT services, and leasing and business services, which together account for 75.50% of the total [2] Group 2: Regional Distribution - The coverage of data asset reporting among non-listed companies has expanded to 27 provincial-level administrative regions, with Shandong and Jiangsu leading [3] - More than half of the companies have chosen to register their data assets on local platforms, indicating a localized trend in registration [3] - The proportion of technology companies among the reporting non-listed companies is significant, making up 33.60% of the total [3] Group 3: Listed Companies - As of August 31, 2025, 109 out of over 5,000 listed companies in A-shares have disclosed data asset reporting, involving a total amount of 2.640 billion yuan, with a steady growth in overall scale but a slowdown in growth rate compared to 2024 [4] - The "intangible assets" category remains the primary method for listed companies to disclose data resources, with 101 companies reporting amounts totaling 1.706 billion yuan [4] Group 4: Industry Trends - The number of financial industry companies reporting data assets has significantly increased by 33% compared to the end of 2024, involving an amount of 0.054 billion yuan, primarily from banks and securities firms [4] - The three major telecom operators have made a notable contribution, with a total reporting amount of 1.600 billion yuan, accounting for 60.7% of the market total [4] - The report introduces a new section on data asset valuation, detailing the concepts, processes, methods, and examples of data asset valuation, while discussing the current challenges and future outlook [4]

Group 1 - As of Q3 2023, 375 non-listed companies in China have disclosed data resource inclusion, securing a total financing amount of 1.899 billion yuan [1] - The implementation of the Ministry of Finance's interim regulations on accounting treatment of enterprise data resources will officially start on January 1, 2024, which aims to standardize the accounting methods for data resources [1] - The growth rate of data asset inclusion is slowing down as companies face more challenges in promoting data assets from "single-point breakthroughs" to "overall promotion" [1] Group 2 - Local state-owned enterprises are the main contributors to data asset inclusion among non-listed companies, with 310 local state-owned enterprises accounting for 82.67% of the total, securing 1.71 billion yuan in financing [2] - The leading industries for data asset inclusion are information transmission, software and IT services, leasing and business services, and transportation, accounting for 75.50% of the total companies [2] - Data asset registration is predominantly localized, with over half of the companies choosing to register on local platforms within their province [2] Group 3 - Among listed companies, 109 out of over 5,000 A-share companies disclosed data resource inclusion, involving a total amount of 2.64 billion yuan, indicating steady growth but a slowdown compared to 2024 [3] - The majority of listed companies report data resources under the "intangible assets" category, with 101 companies accounting for 1.706 billion yuan, primarily using the straight-line method for amortization [3] - The financial sector has seen a significant increase in data asset inclusion, with a 33% rise in the number of companies compared to the end of 2024, mainly concentrated in banks and securities firms [3]

Core Insights - The implementation of data asset recognition for companies has shown steady growth, but the growth rate has slowed down since its initiation on January 1, 2024 [1][2] Summary by Category Listed Companies - The number of A-share listed companies recognizing data resources increased from 40 in mid-2024 to 109 by mid-2025, with total recognized amounts rising from 1.36 billion to 2.64 billion yuan [1] - The "intangible assets" category remains the primary disclosure method, with 101 companies reporting data resources as intangible assets totaling 1.71 billion yuan [1] - Most data resources in intangible assets are generated through self-development, with straight-line amortization over 3-5 years being the mainstream practice [1] Industry Distribution - The financial sector saw a significant increase in the number of listed companies recognizing data assets, up 33% from the end of 2024, with a total amount of 0.54 million yuan, primarily from banks and securities firms [2] - The three major telecom operators contributed significantly, with a total recognition amount of 1.6 billion yuan, accounting for 60.7% of the market total [2] - Data asset recognition has expanded to cover 25 provincial administrative regions, with an increasing number of high-market-cap companies participating [2] Non-Listed Companies - As of September 30, 2025, 375 non-listed companies have disclosed data asset recognition, with a total financing amount of 1.899 billion yuan [2][3] - Local state-owned enterprises are the main contributors, accounting for 82.67% of the total recognized companies, with a cumulative financing amount of 1.71 billion yuan [3] - The leading industries for non-listed companies recognizing data assets include information transmission, software and IT services, and transportation [3] Challenges and Considerations - There is a gap between top-level design and practical implementation, with many ambiguities in specific rights confirmation, valuation standards, and auditing criteria [4] - Companies face challenges in matching investments with expected returns, as the complexity of data asset recognition requires significant resources [5] - Balancing information disclosure with commercial confidentiality is crucial, as excessive disclosure may risk revealing core algorithms and user data [5]

Core Insights - The Xinjiang Free Trade Zone has achieved 72 provincial-level institutional innovation results in two years, enhancing the level of institutional openness [1][2] Group 1: Institutional Innovations - The innovations cover eight key areas: trade facilitation, investment facilitation, personnel flow facilitation, government management innovation, financial openness innovation, industrial development, business environment, and regulatory oversight [2] - The implementation of a comprehensive regulatory system for bonded aviation fuel has serviced over 9,400 flights, with a monthly supply capacity growth rate of 18% [2] - A new "QR code" rapid customs clearance model for self-driving export vehicles has improved clearance efficiency by 80% [2] Group 2: International Cooperation - The Xinjiang Free Trade Zone is deepening international cooperation with Central Asia, West Asia, and South Asia, exemplified by the collaboration between the Kashgar area and Kyrgyzstan's Naryn region to build an international industrial park [3] - The Urumqi area has pioneered a "business + technology" model to promote bonded aircraft maintenance services and has innovated a comprehensive service model for fruit and vegetable exports, reducing costs per container by 15% [3] - The Horgos area is testing new models for cross-border services in traditional Chinese medicine and tourism, expanding international cooperation in healthcare, culture, and digital sectors [3] Group 3: Business Environment Optimization - The Xinjiang Free Trade Zone focuses on transforming government functions to optimize the business environment, offering over 100 exclusive services for high-level talents through initiatives like the "Red Mountain Talent Card" [3] - Innovative financing tools such as data assets and "Hui Trade Loan" have effectively alleviated financing difficulties for small and micro enterprises [3] - A cross-border settlement platform has been established, supporting transactions in 18 currencies, including the ruble [3][4]

Core Insights - The strategic partnership between People's Data and the China Electronic Technology Standardization Institute aims to enhance the market-oriented allocation of data elements and improve the data ecosystem for high-quality agricultural development [1][3]. Group 1: Partnership Details - People's Data and the China Electronic Technology Standardization Institute will collaborate on various aspects including data infrastructure, standard development, data application, and governance [3]. - The China Electronic Technology Standardization Institute is a key research institution under the Ministry of Industry and Information Technology, focusing on standardization in the electronic information technology sector [3]. Group 2: Objectives and Future Plans - The partnership is a significant outcome of the "People's Roadshow" event, which is part of a broader initiative to facilitate communication between government and enterprises [4]. - People's Data plans to continue organizing events that promote the integration of resources across government, industry, academia, and research to support local industrial development and the digital economy [4].