On August 1st, 2023, the Ministry of Finance issued “Interim Provisions on Accounting Treatment of Enterprise Data Resources” (hereafter “Interim Provisions”). Interim Provisions explicitly introduces a new item, "Data Resources" under the categories of inventory, intangible assets, and development expenditures in the balance sheet. Eligible data resources meeting specified criteria are to be recognized in the balance sheet. Enterprises have sequentially initiated the recognition of data resources into their accounting, recognizing that data resources and assets possess unique characteristics distinct from traditional items, necessitating considerations such as precise data measurement, cost-effective amortization, and efficient inter-departmental collaboration during the recognition process.
On the afternoon of June 28th, Peking University Shanghai Lin-gang International Science and Technology Innovation Center (PKU-IICSH), in collaboration with Shanghai Lin-gang Special Area Cross-Border Data Port, Wintell & Co, and KPMG China hosted a seminar titled Enterprise Data Resources Recognition Techniques and Practices（“企业数据资源入表技术与实务”）, delving into enterprise data resources accounting from various perspectives, including technology, law, and finance.
Drawing from research and exploration into core recognition technologies such as precise data measurement and data resource cards, the Data Cross-border Transfer Technology Research Center at PKU-IICSH released the "DCCB Four-Step Self-Testing Method" for the recognition of corporate data resources.
The Recognition of Corporate Data Resources DCCB Four-Step Self-Testing Method
1. Data Availability (D)
The existence of data is a prerequisite for recognition. Enterprises should preliminarily inventory their current data volume, including databases, data entries, unstructured data, and data volume in gigabytes. There exists a certain correlation between the sum of money included and the volume of data. Enterprises with little data volume therefore cannot expect a high inclusion sum.
2. Cost Availability (C)
Having associated costs is crucial for recognition. Enterprises can preliminarily assess costs related to data, including significant items such as (1) IT costs, (2) procurement costs, (3) governance costs, and (4) labor costs.
3. Legal Ownership or Control (C)
Examining whether an enterprise has legal ownership or control over its data involves a thorough review of the current prevailing general laws and regulations, industry laws and regulations, and contracts and agreements of data-related business. It must be clarified which data is legally owned or controlled by enterprises and which do not meet relevant requirements in accounting standards for recognition.
4. Expected Economic Benefit (B)
Enterprises need to evaluate strategically and from a business perspective whether existing data (especially data related to costs) has played a role in internal management and business processes (non-informational), whether it has been realized in compliance, or is planned for realization.
Head and researcher of Data Cross-border Transfer Technology Research Center, PKU-IICSH, member of the Expert Committee of the China Committee of 100 of Digital Economy, CEO of Shuquantong Technology
Liu Feng, Head of the Data Cross-border Transfer Technology Research Center at PKU-IICSH, highlighted that since the issuance of the Interim Provisions, the recognition of data resources has become a pressing business for corporate executives, gathering significant momentum for related industry and the digital transformation development of enterprises. However, executives often have inflated expectations regarding new concepts such as "recognition," leading to a substantial gap between its implementation in ideality and reality. We hope that the DCCB Four-Step Self-Testing Method can contribute to the objective evaluation of recognition work, clarifying current foundations, rationalizing development paths, and establishing a sustainable recognition work system.
Zhang Xuchun (Jessie Zhang), Senior Partner and Co-Director of Data Compliance Committee, Wintell & Co Law Firm, Deputy to the Shanghai Pudong New Area’s People’s Congress
Zhang Xuchun (Jessie Zhang), Senior Partner and Co-Director of Data Compliance Committee, Wintell & Co Law Firm, Deputy to Shanghai Pudong New Area’s People’s Congress, expatiated on data resources recognition methods by discussing the current status, challenges, legal basis, compliance methods, and case analysis of data resources recognition, reminding enterprises to ensure compliance governance regarding recognition.
Zhang Hangchuan, Director of Digital Empowerment Business at KPMG China
Zhang Hangchuan, Director of Digital Empowerment Business at KPMG China, provided an in-depth interpretation of data elements policy from the perspectives of policy logic, data logic, industry logic, and financial logic. Through extensive analysis of actual cases of large-scale data resources recognition and data capitalization, he further helped enterprises broaden their thinking on data capitalization management.
The recognition of data resources can help enterprises reflect the value of data resources in financial statements, enhancing total assets and market value. After being recognized as assets, data resources can also enhance a company's financing capabilities. Through the DCCB Four-Step Self-Testing Method for corporate data resources recognition, enterprises can establish a practical, objective, and rational starting point for recognition work, integrating it with their data strategies for reasonable planning and practical advancement, providing robust support for corporate digital transformation.
