Enterprise Practices for Precise Data Rights, Dynamic Compliance, and Data Asset Management

Data assetization requires accurate data rights and broader data circulation; the article introduces the company's practice in precise data rights and dynamic compliance solutions.

Drivers : Internal and external pressures such as cybersecurity, personal data protection laws, and national digital strategies push the need for compliant data flow while also encouraging data value creation.

Path : Guided by the "Data 20" policy, the company adopts a framework of precise data rights and dynamic compliance, establishing mechanisms for data ownership, circulation, revenue sharing, and governance.

Practice : Five key work areas are outlined – (1) data compliance and shared processing, (2) rights authorization and governance, (3) cost quantification and value assessment, (4) revenue measurement and transaction facilitation, and (5) risk monitoring and technical support.

Compliance Mechanism : A comprehensive compliance framework is built, including scenario‑based authorization, a personal‑information authorization matrix, electronic "double‑list" inventories, and shared third‑party lists, all supported by business‑driven technical implementation.

Dynamic Authorization : The solution creates atomic, electronic agreements stored in a compliance repository, enabling real‑time updates of authorization across channels (APP, counter) and linking front‑end agreements with back‑end permission checks for billions of customers.

Cost Management : The company quantifies data‑related costs, distinguishing primary and secondary cost allocation to reflect the true value of data assets.

Transaction Circulation : A two‑level architecture with three‑level authentication and a six‑step process supports large‑scale data sharing, value certification, and billing across both professional subsidiaries and the group platform.

Risk Monitoring : A 20+ category risk monitoring system and tools accelerate personal‑information risk assessment, reducing evaluation time from 20 days to 3‑5 days and enhancing overall efficiency.

The combined practices aim to promote data assetization, support digital transformation of data departments, and gradually shift data management value to the front‑end of the business.