中经记者 石健 青岛报道 《中共中央关于制定国民经济和社会发展第十五个五年规划的建议》（以下简称"建议"）明确提出稳步 发展资产证券化。为数据要素与金融服务的深度融合指明了方向。 值得注意的是，今年我国数据资产证券化实现发行"破冰"。大公国际研报显示，截至2025年9月末，我 国共发行数据资产ABS产品7笔，合计规模24.9亿元。 在近期举行的第三届公共数据运营大会上，全国首个数据资产证券化生态联盟成立，这标志着数据证券 化进入落地阶段。青岛数据集团有限公司首席数据官、青岛数据资产登记评价中心主任赵传启在接受 《中国经营报》记者采访时说："数据资产不仅具有激励价值，数据资产还为融资起到诸多辅助作用， 数据资产作为真正的资产，金融机构把它当作金融资产来看待，来做入股和证券化时，其价值也会出 现。" 先试先行 今年7月，全国首单获批的数据资产证券化项目ABS"华鑫—鑫欣—数据资产1—5期资产支持专项计 划"首期在深圳证券交易所正式发行设立。该项目由南京鑫欣商业保理有限公司作为发行人、华鑫证券 有限责任公司作为管理人和销售机构，首期发行规模1.337亿元，优先级票面利率2%。 此后，数据资产证券化"破冰"加速。大公 ...

1. Report Industry Investment Rating - Not provided in the content 2. Core Viewpoints of the Report - The current data asset ABS has three models: "data - pledged loan", "accounts receivable/financial leasing + data pledge", and "data - empowered pricing". Policy support has been provided for the value transformation path from data "resources" to "assets" and then to "capital", but there are still pain points in the development of data asset ABS. Some data asset ABS products have investment value due to their asset pool quality, credit - enhancement measures, and yield advantages [2][12][13] 3. Summary by Relevant Catalogs 3.1 Current Models of Data Asset ABS - As of September 22, 2025, 7 data asset ABS have been issued in China, with a total scale of 2.49 billion yuan. Six of the issuers are state - owned enterprises, and only one is a private enterprise. The three models are: "data - pledged loan" (e.g., "Data 1 Phase"), "accounts receivable/financial leasing + data pledge" (e.g., "Rugao 01" and "Liantou 3 Phase"), and "data - empowered pricing" (e.g., "Zhongtoubao 2 Phase" and "Jiangong Project") [2][3][5] - The first approved data asset labeled product is the "Huaxin - Xinxin - Data Asset 1 - 5 Phase Asset - Backed Special Plan", with a total shelf scale of 500 million yuan. The first successfully established data asset ABS product is the "Ping'an - Rugao Phase 1 Asset - Backed Special Plan (Data Asset)", with a scale of 130 million yuan and a coupon rate as low as 2.4% [4] 3.2 Policy Support for Value Transformation - Policies such as the "Data Twenty Articles" in December 2022, the "Interim Provisions on the Accounting Treatment of Enterprise Data Resources" in August 2023, and the "Guiding Opinions on Strengthening Data Asset Management" in December 2023 have provided support for the value transformation from data "resources" to "assets" and then to "capital" [2][12] - However, the development of data asset ABS still faces pain points, including inconsistent data confirmation and registration standards, the lack of a perfect valuation system, and increasing data security and compliance risks [2][13] 3.3 Investment Value Analysis of Data Asset ABS - In terms of asset pool quality, "Zhongtoubao 2A/2C" and "25 Jiangong You/Ci" have excellent asset pools. "Data 1 You/Ci" is in the middle. "Rugao 01 You/Ci" and "25 Yihang You/Ci" have creditworthy but concentrated debtors. "Liantou 3 You/Ci" and "25 Xingzu 01/Ci" have relatively weak asset pools [16] - Regarding credit - enhancement measures, "25 Jiangong You/Ci" and "Rugao 01 You/Ci" have high credit - enhancement effectiveness. "Liantou 3 You/Ci" has a 100% data asset pledge but depends on the quality of underlying leasing assets. "Zhongtoubao 2A/2C" has traditional credit - enhancement methods [17] - Some data asset ABS have higher yields than other bonds of the same credit subject, same rating, and similar maturity due to structural complexity and liquidity premium. For example, on September 24, 2025, the yield of "Data 1 You" was about 11bp higher than that of "Meixin 3A" [2][19]

Core Insights - The first approved data asset-backed securities (ABS) product in China has been successfully issued, marking a significant step in the marketization and value transformation of data assets [1][5] - The project demonstrates the potential of data as a new type of asset, transitioning from "resource" to "asset" and then to "capital," which can enhance the added value across various industries [1][6] Group 1: Project Overview - The first phase of the data asset ABS, named "Huaxin-Xinxin-Data Asset 1-5 Phase Asset Support Special Plan," was issued with a scale of 133.7 million yuan and a priority ticket interest rate of 2.0% [1][2] - The cash flow for 89% of the project comes from data asset pledge loans, indicating a strong reliance on data-backed financing [1][2] Group 2: Participating Companies - Nine companies from different regions and sectors participated in the project, including data intelligence service providers and industry digitalization service providers [2][3] - The data assets included in the pool are categorized into three types: anonymized user behavior data, industry insight data, and technical interaction data [2][3] Group 3: Compliance and Risk Management - Huaxin Securities implemented a comprehensive compliance mechanism and introduced third-party evaluation systems to address legal and compliance challenges in the securitization process [3][4] - The company emphasized the importance of verifying data ownership, legality, and compliance to mitigate legal risks associated with data assets [4][5] Group 4: Market Potential and Future Outlook - The market for data asset securitization is expected to grow significantly, with projections indicating a potential market size in the hundreds of billions [6][7] - The company plans to expand the application scenarios for data asset securitization, focusing on public and industrial data sectors over the next three years [6][7]

Core Insights - Data asset securitization is emerging as a crucial financial innovation tool to activate data value and empower the real economy amid the ongoing reform of the national data factor market [1][3] Group 1: Event Overview - The "Data Asset Securitization Innovation Business Exchange Conference" was held in Nanjing, organized by the Jiangsu Data Exchange, gathering government representatives, academic experts, financial institutions, and data asset practitioners to discuss the policy framework, practical paths, and future opportunities of data asset securitization [1][3] - The conference aims to respond to the central financial work meeting's call to "make a significant contribution to digital finance" and implement the National Data Bureau's "Data Factor ×" action plan, promoting the transition of data resources to data assets and capital [3] Group 2: Key Developments - Jiangsu Data Group's General Manager Xu Yanwu emphasized the importance of building a comprehensive service ecosystem for data productization, marketization, and valuation to help enterprises activate data assets [3] - The "Data Asset Value Innovation Laboratory" was officially launched, focusing on key aspects such as data asset valuation, credit rating, and securitization product design to provide practical support for data asset securitization [3][6] - Strategic data merchants, including Guizhou Data Treasure and Deloitte Consulting, joined the Jiangsu Data Exchange, enriching the data ecosystem and providing professional support in data consulting, governance, evaluation, compliance, and financial services [3] Group 3: Expert Insights - Experts shared insights on data asset securitization, discussing policy frameworks, international experiences, and practical case studies, with notable presentations on the trillion-dollar data asset market and the exploration of data value in the AI era [5] - A roundtable forum featured discussions on data asset evaluation, legal compliance, and product innovation, with a consensus on the need to build a collaborative ecosystem involving government, industry, academia, research, and finance [6] Group 4: Future Directions - The Jiangsu Data Exchange aims to enhance cooperation across regions and sectors, focusing on improving data trading rules, data property registration, infrastructure for data circulation, and innovation in data assetization [6]

Group 1 - The first approved data asset securitization project in China, "Huaxin-Xinxin-Data Asset Phase 1 Asset Support Special Plan," has been officially listed with a scale of 500 million yuan [1] - The data assets involved come from state-owned enterprises, listed companies, and specialized small and medium-sized enterprises across seven cities in four provinces [1] - Another project, "Ping An-Rugao Phase 1 Asset Support Special Plan," has also been listed, marking a significant step in utilizing standardized financial products to activate local state-owned enterprise data assets [1] Group 2 - The design of the two products incorporates multiple innovations aimed at promoting high-quality development of the real economy [2] - The "Huaxin-Xinxin" plan includes a diverse range of data asset applications, such as autonomous driving data and smart agriculture data, allowing companies to secure financing between 10 million and 25 million yuan [2] - An innovative mechanism using multiple data asset pledge loans has been established, demonstrating the feasibility of using data assets as collateral for financing [2] Group 3 - The development of data asset securitization is supported by an increasingly robust data element ecosystem, with approximately 100 A-share listed companies in Jiangsu involved in data asset accounting [3] - In 2024, the total amount of data assets accounted for by A-share listed companies in Jiangsu is estimated to be around 2.164 billion yuan, with 88% of companies including data resources as intangible assets [3] - The national data market transaction scale is projected to exceed 160 billion yuan in 2024, reflecting a year-on-year growth of over 30% [3]

Core Insights - The article emphasizes the importance of data as a core production factor in business operations, highlighting the need for effective integration and measurement of data resources to maximize their value [1][20] - The introduction of the "Data Twenty Articles" and the "Interim Regulations on Accounting Treatment of Enterprise Data Resources" provides clear policy guidance and operational frameworks for data asset management [1][20] Policy Framework - The "Data Twenty Articles" establishes the institutional foundation for the data factor market, clarifying data ownership, circulation rules, and security requirements, which are essential for the legal and compliant use of data resources [1] - The "Interim Regulations" further detail accounting treatment methods, ensuring that enterprises can scientifically and reasonably recognize, measure, and report data assets while adhering to accounting standards [1] Data Inventory and Assessment - Conducting a comprehensive data inventory is crucial for enterprises to identify the types of data they possess, where it is stored, and which teams manage it, allowing for precise delineation of data suitable for financial reporting [3] - The process of selecting valuable data for inclusion in financial statements is likened to gold mining, emphasizing the need for careful selection to ensure that only valuable data is reported [3] Ownership and Valuation Challenges - Data ownership remains a significant challenge due to historical reasons and cross-border complexities, necessitating industry guidelines to clarify rights and responsibilities [5] - Choosing appropriate valuation methods for data assets is critical, with cost, income, and market approaches each having specific applicability depending on the data's maturity and revenue generation potential [5] Measurement and Reporting - Once data is included in the balance sheet, ongoing measurement is essential, with inventory-type data requiring regular impairment testing and intangible data needing differentiated treatment based on its useful life [7] - Maintaining consistency in measurement methods is fundamental to ensuring the rigor of financial information [7] Risk Management in Data Asset Financing - When considering data assets for collateralized loans, risk management is paramount, with banks typically setting a collateral ratio not exceeding 50% of the assessed value and requiring compliance with registration procedures [9] - Selecting data with strong resilience to depreciation as collateral can effectively mitigate credit risk associated with rapid asset value decline [9] Asset Securitization Challenges - Asset securitization is a viable method for activating existing assets, but it faces challenges such as complex legal relationships, difficulties in cash flow forecasting, and a lack of historical default data [10] - Overcoming these challenges requires learning from successful domestic and international cases and continuous improvement of relevant laws and regulations [10] Strategic Importance of Data Asset Management - Successful inclusion of data assets in financial statements optimizes corporate financial structures, reduces debt ratios, and enhances asset turnover efficiency, particularly for asset-light technology companies [20] - Strengthening talent development through cross-training between IT and finance teams is essential for improving data asset management capabilities [20] - The process of data asset inclusion is a systematic project involving policy interpretation, resource organization, rights definition, value assessment, accounting treatment, and risk control [20]

Core Viewpoint - The company, Daily Interaction, reported a revenue of 218 million yuan for the first half of 2025, highlighting its commitment to embracing artificial intelligence technologies and the steady development of its data intelligence business, with expectations for scalable revenue in the coming year [1] Group 1: Business Performance - The company has maintained steady progress in its core business despite external market pressures, showcasing strong business resilience [2] - Developer services generated a revenue of 24.17 million yuan, reinforcing the company's leading position in the industry [2] - Commercial services achieved a revenue of 40.97 million yuan, while brand services contributed 8.46 million yuan, indicating positive growth potential [2] - Public services generated a revenue of 139 million yuan, focusing on mature products and actively exploring new intelligent products [2] Group 2: Investment in Artificial Intelligence - To capitalize on the opportunities presented by the AI wave, the company has increased its investment in artificial intelligence, establishing an AI division and appointing a Chief AI Officer [3] - Approximately 50 key personnel have been allocated to focus on AI product and project development [3] - The company has developed a series of AI products, including GAI OS, GAI Office, and GAI Store, and launched a high-end AI workstation [3] Group 3: Data Value Enhancement - The company is focusing on its "Data Station" strategy to facilitate the safe and efficient circulation of data among various stakeholders [4] - A nationwide "Hundred Cities, Hundred Scenarios" co-creation plan has been initiated, with successful implementations in multiple cities [4] - The company is actively exploring data asset securitization, having participated in the first approved data asset ABS product in July [4] - The company is committed to the "data + intelligence" development direction and plans to continue exploring AI, despite uncertainties in new product development [4]

Core Viewpoint - The National Development and Reform Commission plans to introduce over ten systems, including data property rights, to accelerate the release of data factor value, which is becoming a new engine for high-quality economic development, particularly in the financial sector [1][2]. Group 1: Data Factor Value in Financial Sector - Data factors are being recognized as valuable assets, with policies facilitating their entry into capital markets through instruments like Asset-Backed Securities (ABS) and Real Estate Investment Trusts (REITs) [2]. - The first closed-end infrastructure securities investment fund based on data centers was launched, with significant market recognition reflected in the buying amounts of 233 million and 388 million yuan for two specific funds [2]. - Data factors are enhancing credit assessment by integrating various data sources, which helps financial institutions with risk pricing and enables small and medium enterprises to convert hidden credit into financing capabilities [2][3]. Group 2: Challenges in Data Factor Financial Applications - Despite initial successes, the integration of data factors into financial services faces challenges such as data ownership confirmation, compliance, and security issues [4][5]. - The complexity of data as an asset, including its non-standard nature and valuation difficulties, complicates its integration into standardized financial products [5][6]. - Policies are being developed to address these challenges, including the establishment of data factor comprehensive experimental zones in various regions to explore data asset circulation models [6].

Group 1: Urban Development and Revitalization - Nanjing has revitalized urban spaces through the activation of 539 land and asset projects, with 212 already revitalized, covering approximately 1.26 million square meters of property and 0.52 million acres of land [1] - The Nanjing Health Grand City, a large-scale commercial project, has opened after a decade of stagnation, featuring a multi-modal transport hub that connects various public transport options, enhancing consumer accessibility [2][3] - The RE-PARK project on Ruijin Road has transformed an old garment factory into a trendy urban space, integrating commercial, cultural, and recreational functions, with an expected annual revenue exceeding 600 million yuan [5] Group 2: Transportation-Oriented Development (TOD) - The newly completed Sojie Complex is Nanjing's first public transport-oriented development (TOD), designed to optimize land use while maintaining its primary function as a bus station, featuring a mix of public transport facilities and commercial spaces [3] - The TOD model aims to enhance land productivity, with projected economic output exceeding 10 million yuan per hectare [3] Group 3: Data Asset Utilization - Nanjing is actively promoting the monetization of data assets, exemplified by the Jiangsu Future Urban Travel Technology Group's participation in a data asset securitization project, raising 5 million yuan [7] - The Nanjing Big Data Group has initiated the market-oriented operation of public data resources, successfully launching multiple public data products and enhancing the efficiency of data asset allocation [8][9]

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]