Veeam Completes Acquisition of Securiti AI to Create the Industry’s First Trusted Data Platform for Accelerating Safe AI at Scale

View

10 major changes in China’s finalized PIPL

Published October 11, 2021
Author

Muhammad Faisal Sattar

Director of Product Legal & Global Data Compliance

FIP, CIPT, CIPM, CIPP/Asia

Listen to the content

On August 20, 2021, China's Personal Information Protection Law (the “PIPL”) was officially adopted after its third revision. The PIPL came into effect on November 1st, 2021. The first and second drafts of PIPL were released on 21 October 2020 and 29 April 2021 respectively. This article will talk about the 10 major changes between the second draft and the finalized version of the PIPL.

Key Changes Under the Finalized PIPL

Under the finalised version of the PIPL, there are seven legal basis of the data processing:

  1. Consent;
  2. Contractual necessity or necessity arising from the human resources management implemented in accordance with the labour rules and regulations of the employer formulated according to the law or collective contracts signed according to law;
  3. Compliance with legal responsibilities or obligations;
  4. Responding to a public health emergency, or in an emergency to protect the safety of natural persons’ health and property;
  5. Processing personal information that is already made public within the reasonable scope and in accordance with the requirements of the PIPL;
  6. For purposes of carrying out news reporting and public opinion monitoring for public interests; and
  7. Other circumstances permitted by laws and regulations.

The only substantial change made from the second draft is the addition of the clause of contractual necessity in the finalized PIPL. This is a specific reference to labour governance rules that are signed in accordance with laws. This new addition will have a huge impact in the employment context.

Consent requirements under the finalized PIPL remain consistent with previous PIPL drafts. Furthermore, similar to the previous drafts, the term “separate consent” is not yet defined under the final form of the PIPL.

Compared with the second draft, article 28 of the finalized PIPL purports data of minors aged under 14 as “sensitive personal information”, and requires need to obtain separate consent from the minor's guardian before processing their data.

Cross-border data transfers

The finalized PIPL enhances its cross-border data transfer system, as compared to the second draft, introduces 3 changes:

  • PIPL states that cross-border treaties concluded by China may prevail over other treaties.
  • All personal information processors are required to adopt measures to ensure that processing activities of the destination country have an equivalent level of protection provided in the PIPL.
  • The PIPL requires organizations to obtain approval from government authorities before transferring data to foriegn organs for international judicial assistance or administrative law enforcement.

Data subject rights

The finalized version of the PIPL brings the following changes to data subject rights:

  • Deceased data subject rights: Next of the kin of the deceased data subject can request a copy, amendment and erasure of their relatives data.
  • Data portability: A data subject has the right to request a data processor to have his data transferred to another data processor provided that such transfer follows the requirements set by the Cybersecurity Administration of China (“CAC”).
  • Redress: If a data processor refuses to comply with a DSR, the data subject may seek redress in court of law.

Personal Information Processing

Organizations tend to collect personal information for different purposes, such as to understand customers’ behavior patterns and interests. However, sometimes, it is specifically collected for the purpose of sending them notification emails, text messages, etc.

In the final revision, under the General Provision section in Article (6), the regulatory authority has specified the restriction on personal information (PI) processing. The PIPL specifies that other than definite and reasonable purpose, the PI processing “be directly related to the purpose of processing.” In addition to that, the collection of personal information should be very limited.

Unlawful Personal Information Collection

In the first draft and second draft, the regulatory authorities restricted organizations from processing data which violated the laws and administrative regulations. In the finalized version, the regulatory authority further expanded the unlawful collection and processing of data.

As per the finalized version, organizations are prohibited from collecting and processing data illegally, disclosing it to any third-party, or using it in a way that would result in any damage to national or public interest.

Personal Information Processing of Minors

As per Article (15) of the second draft, PI processors were required to obtain the consent of the parent or a guardian before processing. The final version of PIPL merges Article (15) with Article (31), specifying that special processing rules should be created by the PI processor for data subjects under the age of 14.

Automated Decision Making

The second draft of the PIPL required automated decision-making systems to be transparent, fair, and reasonable. It also gave individuals the ability to inquire further about the decision made by the automated system or reject it altogether.

The final draft of PIPL merges Article (25) with Article (24), additionally requiring PI processors to “not engage in unreasonable differential treatment of individuals in trading conditions,” and prohibiting price discrimination through automated decision-making.

Personal Information Protection Impact Assessment

Article (55) of the second draft stated the requirement of assessing risks of certain personal information processing activities in advance and keeping a record of the processing. However, in the finalized PIPL, Article (55) named this risk assessment as “personal information protection impact assessment” and added a separate new Article (56) detailing the scenarios where this impact assessment will be required.

Penalties

Upon violations and non-compliance, PIPL penalizes fines of up to 1 million RMB on the processor and up to 100,000 RMB on the person supervising the processor. Serious fines may be imposed on the processor of up to 50 million RMB or 5% of turnover of the previous year.

The revised version of PIPL imposes serious penalties on the liable persons, including the processor and those in charge of the processor, prohibiting them from serving as managers or directors in any organization.

Conclusion

The finalized PIPL is set to go into effect in less than 2 months and organizations are not yet ready to comply with all the requirements set in place. Organizations need to incorporate automation if they hope to improve their processes in time for the enforcement of the PIPL.

Request a demo now to see how robotic automation and artificial intelligence can help you on your road to compliance with China’s PIPL.


Frequently Asked Questions (FAQs)

China PIPL, or the Personal Information Protection Law, is a comprehensive data protection regulation enacted in China to govern the processing of personal information by organizations. It sets out rules for the collection, use, and cross-border transfer of personal data.

While both China PIPL and GDPR (General Data Protection Regulation) aim to protect individuals' privacy, they have differences in scope, requirements, and penalties. China PIPL has a broader extraterritorial scope, and there are variations in the definitions and obligations compared to GDPR.

China PIPL has significant effects on how businesses handle personal information. It introduces stricter requirements for obtaining consent, imposes obligations on data processors, and includes severe penalties for non-compliance.

PIPL China is a comprehensive data protection law that regulates the processing of personal information in China. It focuses on user consent, data subject rights, and imposes obligations on data processors, with severe penalties for violations.

Analyze this article with AI

Prompts open in third-party AI tools.
Join Our Newsletter

Get all the latest information, law updates and more delivered to your inbox


Share

Take a
Product Tour

See how easy it is to manage privacy compliance with robotic automation.

Videos
View More
Mitigating OWASP Top 10 for LLM Applications 2025
Generative AI (GenAI) has transformed how enterprises operate, scale, and grow. There’s an AI application for every purpose, from increasing employee productivity to streamlining...
View More
Top 6 DSPM Use Cases
With the advent of Generative AI (GenAI), data has become more dynamic. New data is generated faster than ever, transmitted to various systems, applications,...
View More
Colorado Privacy Act (CPA)
What is the Colorado Privacy Act? The CPA is a comprehensive privacy law signed on July 7, 2021. It established new standards for personal...
View More
Securiti for Copilot in SaaS
Accelerate Copilot Adoption Securely & Confidently Organizations are eager to adopt Microsoft 365 Copilot for increased productivity and efficiency. However, security concerns like data...
View More
Top 10 Considerations for Safely Using Unstructured Data with GenAI
A staggering 90% of an organization's data is unstructured. This data is rapidly being used to fuel GenAI applications like chatbots and AI search....
View More
Gencore AI: Building Safe, Enterprise-grade AI Systems in Minutes
As enterprises adopt generative AI, data and AI teams face numerous hurdles: securely connecting unstructured and structured data sources, maintaining proper controls and governance,...
View More
Navigating CPRA: Key Insights for Businesses
What is CPRA? The California Privacy Rights Act (CPRA) is California's state legislation aimed at protecting residents' digital privacy. It became effective on January...
View More
Navigating the Shift: Transitioning to PCI DSS v4.0
What is PCI DSS? PCI DSS (Payment Card Industry Data Security Standard) is a set of security standards to ensure safe processing, storage, and...
View More
Securing Data+AI : Playbook for Trust, Risk, and Security Management (TRiSM)
AI's growing security risks have 48% of global CISOs alarmed. Join this keynote to learn about a practical playbook for enabling AI Trust, Risk,...
AWS Startup Showcase Cybersecurity Governance With Generative AI View More
AWS Startup Showcase Cybersecurity Governance With Generative AI
Balancing Innovation and Governance with Generative AI Generative AI has the potential to disrupt all aspects of business, with powerful new capabilities. However, with...

Spotlight Talks

Spotlight 50:52
From Data to Deployment: Safeguarding Enterprise AI with Security and Governance
Watch Now View
Spotlight 11:29
Not Hype — Dye & Durham’s Analytics Head Shows What AI at Work Really Looks Like
Not Hype — Dye & Durham’s Analytics Head Shows What AI at Work Really Looks Like
Watch Now View
Spotlight 11:18
Rewiring Real Estate Finance — How Walker & Dunlop Is Giving Its $135B Portfolio a Data-First Refresh
Watch Now View
Spotlight 13:38
Accelerating Miracles — How Sanofi is Embedding AI to Significantly Reduce Drug Development Timelines
Sanofi Thumbnail
Watch Now View
Spotlight 10:35
There’s Been a Material Shift in the Data Center of Gravity
Watch Now View
Spotlight 14:21
AI Governance Is Much More than Technology Risk Mitigation
AI Governance Is Much More than Technology Risk Mitigation
Watch Now View
Spotlight 12:!3
You Can’t Build Pipelines, Warehouses, or AI Platforms Without Business Knowledge
Watch Now View
Spotlight 47:42
Cybersecurity – Where Leaders are Buying, Building, and Partnering
Rehan Jalil
Watch Now View
Spotlight 27:29
Building Safe AI with Databricks and Gencore
Rehan Jalil
Watch Now View
Spotlight 46:02
Building Safe Enterprise AI: A Practical Roadmap
Watch Now View
Latest
View More
DataAI Security: Why Healthcare Organizations Choose Securiti
Discover why healthcare organizations trust Securiti for Data & AI Security. Learn key blockers, five proven advantages, and what safe data innovation makes possible.
View More
The Anthropic Exploit: Welcome to the Era of AI Agent Attacks
Explore the first AI agent attack, why it changes everything, and how DataAI Security pillars like Intelligence, CommandGraph, and Firewalls protect sensitive data.
CNIL’s Guidance on Multi-Device Consent View More
CNIL’s Guidance on Multi-Device Consent
Understand CNIL’s guidance on multi-device cookie consent—requirements for syncing preferences across devices, valid consent standards, transparency, and compliance risks.
View More
Navigating the EU Digital Omnibus Proposals
A clear guide to the EU Digital Omnibus proposals—what’s changing, impacted regulations, compliance implications, enforcement updates, and what businesses should prepare for.
2026 Strategic Priorities for Privacy Leaders: A CPO Brief View More
2026 Strategic Priorities for Privacy Leaders: A CPO Brief
A 2026 briefing for Chief Privacy Officers (CPOs), AI governance, global law updates, consent modernization, cross-border transfers, automation and measurable risk reduction.
View More
Australia’s Privacy Overhaul: Landmark Reforms in Privacy, Cyber Security & Online Safety
Access the whitepaper and gain insights into Australia’s Privacy Law landscape, CSLP, Social Media Minimum Age Act, and how Securiti helps ensure swift compliance.
View More
Solution Brief: Microsoft Purview + Securiti
Extend Microsoft Purview with Securiti to discover, classify, and reduce data & AI risk across hybrid environments with continuous monitoring and automated remediation. Learn...
Top 7 Data & AI Security Trends 2026 View More
Top 7 Data & AI Security Trends 2026
Discover the top 7 Data & AI security trends for 2026. Learn how to secure AI agents, govern data, manage risk, and scale AI...
View More
Navigating HITRUST: A Guide to Certification
Securiti's eBook is a practical guide to HITRUST certification, covering everything from choosing i1 vs r2 and scope systems to managing CAPs & planning...
The DSPM Architect’s Handbook View More
The DSPM Architect’s Handbook: Building an Enterprise-Ready Data+AI Security Program
Get certified in DSPM. Learn to architect a DSPM solution, operationalize data and AI security, apply enterprise best practices, and enable secure AI adoption...
What's
New