Compliance Pathways for Recognizing Data Resources on Balance Sheets and Legal Risk Prevention: A Practical Guide to Enterprise Data Assetization Nationwide

Introduction: Legal Challenges under the Wave of Data Assetization

In recent years, with the vigorous development of the digital economy, data has become a critical strategic resource for enterprises and nations. Effective January 1, 2024, the Interim Provisions on Accounting Treatment for Enterprise Data Resources officially came into force, marking the entry of data resource recognition into the operational implementation stage. However, as enterprises across the country explore data assetization, issues such as unclear ownership, undefined compliance pathways, and insufficient security assessments have become increasingly prominent, giving rise to legal risks that cannot be ignored. At a recent data compliance forum, multiple experts shared profound insights on topics including urban data asset exploration, compliance for recognizing data resources on balance sheets, and legal compliance for cross-border data transfers, providing valuable perspectives for enterprises and legal practitioners. This article will adopt a lawyer's perspective, integrate the core viewpoints from the forum, conduct an in-depth analysis of the compliance pathways for recognizing data resources on balance sheets and legal risk prevention strategies, and offer practical guidance for enterprise data assetization.

I. Data Resources Entering the Balance Sheet: Opportunities and Challenges Coexist

Recognizing data resources on the balance sheet, that is, confirming data resources as an asset in a company's balance sheet, is a major innovation in accounting treatment and also imposes higher requirements for legal compliance. In terms of opportunities, recognizing data on the balance sheet helps companies revitalize data assets, enhance financing capabilities, and strengthen market competitiveness. However, the challenges are equally significant: how should data ownership be defined? How can data quality be guaranteed? How can data security be ensured? There are still no unified answers to these questions at the legal level.

In the forum, lawyer Zhang Xuchun elaborated on the compliance pathway for incorporating data resources into balance sheets, pointing out three major difficulties that enterprises commonly face in practice: first, the imperfect mechanism for data rights confirmation, which leads to an unstable foundation for balance sheet inclusion; second, the lack of uniform standards for data security and compliance review, resulting in differences in practices across regions; third, the absence of unified norms for data value assessment, which affects the accuracy of asset recognition.

From the perspective of legal practice, the recognition of data resources as balance sheet assets first requires clarifying the legality of data sources. Under Article 127 of the Civil Code, where laws provide for the protection of data and virtual property on networks, such provisions shall apply. This means that enterprises must prove that their data was lawfully obtained, used, and processed; otherwise, the assets recognized may face defects in rights. In addition, Article 27 of the Data Security Law requires enterprises to establish and improve a comprehensive data security management system for the entire process, carry out data security education and training, and adopt corresponding technical measures and other necessary measures to ensure data security. Lawyers advise that before initiating data recognition, enterprises should conduct a comprehensive data compliance audit to ensure that the entire data lifecycle meets legal requirements.

II. Definition of Data Property Rights: Legal Framework and Practical Difficulties

The clear definition of data property rights is a prerequisite for the capitalization of data. Professor Kong Xiangjun shared his framework thinking on data property rights protection at the forum, pointing out that the current data property rights system is still in the exploratory stage, with a debate between "ownership" and "usage rights." From judicial practice, when hearing data dispute cases, courts often rely on the principled provisions of Article 2 of the Anti-Unfair Competition Law to regulate behaviors such as data crawling and use, but there is a lack of clear rules on the attribution of rights.

In practice, enterprises often face the following difficulties: first, the boundary between their own data and others' data is blurred, especially in data fusion scenarios, making ownership difficult to delineate; second, data leakage caused by employee departure or partner breach of contract lacks a clear basis for accountability; third, in data transactions, how can the buyer ensure that the seller has legitimate rights to the data.

In response, lawyers advise enterprises to adopt a trinity of "contract + technology + management" rights confirmation strategy. First, in the data collection stage, clarify the legitimacy of data sources through user agreements and authorization letters; second, in the data processing stage, use blockchain and other technologies to record the data flow process, forming a traceable chain of evidence; finally, in the data usage stage, establish an internal data classification and grading system, set different access permissions, and formulate emergency plans. In addition, enterprises should closely monitor updates to new regulations such as the "Measures for the Registration and Administration of Data Intellectual Property" and adjust their rights confirmation strategies in a timely

III. Cross-Border Data Compliance: Balancing Security and Development

As Chinese enterprises accelerate their global expansion, cross-border data flows have become increasingly frequent, and data export compliance has become a challenge that companies must address. Lawyer Zhang Jihong emphasized at the forum that legal compliance for data exports requires finding an optimal balance between personal information protection, data utilization, and national security. According to Article 31 of the Data Security Law and Article 38 of the Personal Information Protection Law, data exports must be conducted through security assessments, certification, or the signing of standard contracts.

However, common mistakes made by enterprises in practice include: failing to classify and grade outbound data, mistakenly treating sensitive data as ordinary data; failing to fulfill the obligation of informed consent, transmitting personal information abroad without authorization; and failing to sign legally binding contracts with overseas recipients, leading to ineffective supervision. These actions may give rise to administrative penalties and even criminal liability.

Lawyers remind that enterprises should establish a compliance process for cross-border data transfer: first, identify the scope of data to be transferred and conduct data classification and grading; second, assess the necessity of the transfer and select a compliant pathway (such as security assessment, standard contracts, etc.); third, sign a data processing agreement with the overseas recipient, clarifying the rights and obligations of both parties; finally, conduct regular compliance audits and dynamically adjust transfer strategies. At the same time, enterprises should pay attention to supporting regulations such as the Measures for Security Assessment of Cross-Border Data Transfer issued by the Cyberspace Administration of China, to ensure operations comply with the latest requirements.

IV. Legal Risk Prevention in Data Assetization and the Role of Lawyers

During the process of data assetization, the legal risks faced by enterprises are not limited to the compliance level, but also include contract disputes, intellectual property disputes, trade secret leaks, and more. Lawyer Li Hua emphasized at the forum that legal services should effectively protect data security and compliant application, with lawyers playing the dual role of "risk gatekeeper" and "value discoverer" in this process.

Specifically, lawyers can provide the following support to enterprises: first, drafting and reviewing data-related contracts, including data procurement, data licensing, and data cooperation agreements, to clarify rights and obligations; second, assisting enterprises in establishing a data compliance system, formulating internal management rules, and conducting employee training; third, representing enterprises in data dispute cases to protect their rights or defend against lawsuits; fourth, providing legal due diligence and transaction structure design services in scenarios such as data transactions and financing.

Taking a data breach as an example, under Article 57 of the Personal Information Protection Law, when a data breach occurs, companies should immediately take remedial measures and notify the competent authorities and affected individuals. Lawyers can assist companies in assessing the impact of the breach, formulating notification plans, cooperating with regulatory investigations, and responding to potential civil lawsuits. In addition, companies should also pay attention to fluctuations in the value of data assets; for instance, depreciation of data assets due to changes in laws and policies may affect the accuracy of financial statements and require timely adjustments.

V. Conclusion: Compliance First, Steady Progress for Long-Term Success

Data assetization is a major trend, but compliance is the prerequisite. Enterprises should prioritize legal risk prevention while pursuing the release of data value. As professional supporters, lawyers should keep pace with policy developments and provide forward-looking legal services. Guangdong Zhiming Law Firm has deep expertise in the data compliance field and rich practical experience, offering comprehensive legal support to enterprises nationwide, including data asset accounting, cross-border data transfers, and dispute resolution, helping enterprises move forward steadily in the data wave.

Data compliance is not a constraint, but a safeguard. In today's era of digital transformation, only by adhering to laws and regulations can the long-term value of data assets be realized.