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DCC · DATA COMPLIANCE CHINA China data law, for overseas counsel.
§ TAG · COMMENTARY

Filed under commentary

Every brief tagged "commentary".

  • § 25 · CROSS-BORDER

    Mutual Trust Mechanisms for Cross-Border Data Flow — China's 'Trusted Data Space' Bet

    Compliance Talker's global legal policy team analyzes three competing models for cross-border data mutual trust: the EU's 'rule trust' (adequacy + SCC), the US's 'market trust' (CLOUD Act + DPF), and China's 'technology trust' bet on Trusted Data Spaces (TDS). The NDA's November 2024 *TDS Development Action Plan 2024-2028* makes confidential computing, federated learning, and blockchain the technical layer through which China seeks to demonstrate cross-border data flow can be 'usable but invisible.' For overseas teams, this is the most concrete view of where Chinese cross-border data infrastructure is heading.

    cross-border · trusted-data-space · confidential-computing
  • § 26 · FACIAL-RECOGNITION

    Reading the FRT Application Measures — What the 100k-Record Filing Threshold Actually Triggers

    The Administrative Measures for the Application Security of Facial Recognition Technology took effect June 1, 2025. The May 2025 announcement on FRT filing implementation followed. Compliance Talker's global legal policy team walks through the seven specific compliance obligations the Measures impose — the non-exclusive-use rule, end-side storage default, 100k-individual filing threshold, separate-consent reinforcement, PIA mandate, and more — with practical implementation guidance on each. For overseas firms with any China-facing FRT deployment, this is the operational walkthrough.

    facial-recognition · frt-measures · sensitive-personal-information
  • § 27 · IMPORTANT-DATA

    How to Identify 'Important Data' — A Plain-Language Method from Wang Qinglan

    Wang Qinglan, head of compliance at a Chinese data exchange, walks through China's unique 'important data' concept in plain language: where it came from, why no other major jurisdiction has anything quite like it, how the U.S., EU, Japan and Korea solve the same problem differently, and — most useful for compliance teams — three methods to identify whether a dataset is 'important' in practice. Her own 'unorthodox' shortcut: ask whether a hostile foreign actor could use this data to cause trouble. If yes, treat it as important data.

    important-data · data-classification · cross-border
  • § 28 · DATA-FUNDAMENTALS

    What Is Data, Really? — A Plain-Language Primer on Rules and Compliance

    What does it actually mean to call something 'data,' and what turns raw recordings into a data asset? Wang Qinglan uses a toy storage room metaphor to walk through the foundational concept overseas readers often skip: data is not just 'records' — it's records made under rules. Master data, metadata, ontology, the three-tier compliance taxonomy (legal / ethical / promised), and the three-step compliance workflow (select / allocate / execute) — all anchored in a concrete example a non-specialist can follow.

    data-fundamentals · data-governance · compliance-architecture
  • § 29 · DATA-GOVERNANCE

    Data Governance vs. Data Management vs. Data Compliance — A Plain-Language Disambiguation

    Wang Qinglan disambiguates three terms that compliance and data teams habitually conflate: data governance, data management, and data compliance. Using a 'data manor' metaphor (the family council vs. the steward team vs. the community monitor), she maps each function to its job — setting direction, executing efficiently, and operating sustainably within external rules and self-imposed commitments. The piece is useful precisely where bilingual confusion is highest: 'data governance' in English carries different connotations than 数据治理 in Chinese practice.

    data-governance · terminology · dama
  • § 30 · CROSS-BORDER

    FTZ Data Export Negative Lists — How 17 Sectors Across Seven Provinces Now Identify Important Data

    Article 6 of the 2024 CBDF Provisions authorized Free Trade Zones to publish data-export negative lists. Since then, Tianjin, Beijing, Hainan, Shanghai, Zhejiang and others have published negative lists covering 17 sectors — automotive, pharmaceuticals, retail, civil aviation, reinsurance, deep-sea industry, seed industry, and more. Compliance Talker's analysis walks through the structural convergence of the negative lists, the important-data identification refinements each FTZ has produced, and the operational impact on enterprises both inside and outside the FTZs.

    cross-border · important-data · ftz-negative-list
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