China Cross-Border Data Transfer: How to Enable Compliant Data Exchange

Data fuels business growth. It also presents regulatory challenges, especially in China's data privacy landscape. If you're reading this article, you probably want to know about China's cross-border data transfers and how to handle the challenges.

In this blog post, we’ll answer the following questions:

• Why does PIPL make cross-border data transfer more challenging?
  
  
• How do you navigate the China cross-border transfer requirements?
  
  
• How can you use anonymization to make data transfer compliant under PIPL?
  

China is a powerful player in the global market. The demand for technological expertise in China is growing rapidly. This creates a gap between the need for skilled tech professionals and their availability.

This gap increases service costs for multinational corporations (MNCs). It also makes data collaboration across borders more complicated. China's Personal Information Protection Law (PIPL) has complicated the environment. It introduces strict data export restrictions that affect cross-border data flow.

The key factors that make cross-border data flow harder under the PIPL include:

• Stringent data export restrictions: Under the PIPL, all businesses processing, handling, or transferring personal information of Chinese nationals outside the country must get the Chinese government's approval. This process includes a mandatory security assessment, adding layers of bureaucracy and potential delays for companies.
  
  
• Data localization requirements: The PIPL mandates that certain data types be stored within China. Companies are compelled to change their data handling and processing infrastructure. This can result in higher operational costs and more complications.
  
  
• Explicit consent for data transfers: The PIPL emphasizes the need for explicit consent from data subjects for such transfers. Organizations must ensure they have clear, informed consent from individuals. Data being transferred across borders adds an additional layer of complexity.
  
  
• Comprehensive data protection obligations: Companies must adhere to strict data protection obligations, including security measures for data exported, retention policies, and procedures for data breaches. These obligations increase the responsibility and liability of companies in handling personal information.
  
  
• Risk of legal repercussions: Non-compliance with PIPL's provisions can lead to significant penalties. This legal risk often requires extensive changes to the company’s existing data handling practices.
  
  
• Impact on international business operations: The comprehensive and strict nature of PIPL regulations affects how MNCs operate internationally. Companies must adapt their business models and data management strategies to comply with PIPL, impacting their global operations.

Understanding China's data export laws is crucial for MNCs' compliance. Adapting to these laws is also essential for international viability. Despite these challenges, recent developments suggest a potential easing of some conditions of the PIPL ¹.

For example, one of the Chinese data protection authorities, the Cyberspace Administration of China (CAC), has put forward a Draft Rule suggesting exceptions in certain situations.

This includes data not created or obtained from China and personal information of fewer than 10,000 individuals meant to be sent across borders within one year. This evolving scenario offers a hint of simplification in the complex web of international data transfers.

But, understanding the legal stipulations and managing data is essential. MNCs must also use privacy-enhancing technologies to compete globally and follow regulations.

All these regulatory intricacies may pose a significant problem for your company, considering you aim to harness the power of global data collaboration while remaining compliant with stringent laws such as the Personal Information Protection Law (PIPL).

As your global business seeks data utility and global expansion, aligning your practices with the changing regulations is a formidable task. As a result, the need for a solution that balances compliance with data usage efficiency has never been more pressing.

The PIPL in China excludes anonymized personal information from being considered "personal information."

The processing of anonymized personal information is not regulated by PIPL. However, it's important to note that while anonymization removes data from PIPL's oversight, it may still be subject to other regulations like the Data Security Law.

This approach allows businesses to use important data for operations and analytics on a legal basis. It does not violate PIPL's restrictions on cross-border data transfers.

However, achieving true anonymization can be technically challenging and potentially reduce the data's utility.

The process must prevent the re-identification of individuals from anonymized data. It should also maintain enough detail for useful analysis and decision-making. Balancing individual privacy and data usefulness is difficult in data anonymization.

The Anonos Data Embassy platform is an indispensable solution for MNCs aiming to balance data utility with adherence to PIPL.

Consider the transformative power at your fingertips - the ability to convert your original datasets into protected, use-case-specific anonymized outputs known as Variant Twins.

These Variant Twins aren't just anonymized data; they are tailored to your specific use cases while diligently aligning with PIPL's privacy mandates. It's about preserving the analytical value of your data in a way that respects both regulations and your operational needs.

Data Embassy transforms the original data into Variant Twins: Fit-for-purpose, protected transformations of original data, each employing the most suitable privacy-enhancing technology for each data use.

The Data Embassy transforms raw data into secure Variant Twins. It embeds data protection into the data itself. This facilitates unprecedented control and utility while remaining compliant.

Anonymized data can be exported lawfully, enabling data aggregation and analysis. This drives business outcomes while meeting regulatory requirements.

The platform can generate valuable data derivatives. These derivatives cannot be linked to individuals, so they support data-focused tasks like analytics and machine learning. The platform ensures individual privacy with appropriate safeguards.

Variant Twins are designed to ensure anonymity by leveraging:

• Synthetic Data: This technique generates entirely new datasets that statistically mirror the original data without personal or identifying information.
  
  For instance, a healthcare company that wants to engage in a data-sharing project over medical research data with an overseas partner could use synthetic data techniques. They would create a new dataset where all patient records are generated artificially, ensuring they reflect the same trends and patterns as the real data (such as the prevalence of a certain disease, age distribution, etc.) but without any actual patient data. This allows the company to share valuable insights without risking breaches while transferring personal data or violating PIPL regulations.
  
  
  
  Synthetic data retains the statistical properties of the original data without containing any PII.
  
  
• Controllably Relinkable Data: also known as statutory pseudonymization, ³ which allows for data to be relinked with its source only under controlled conditions to ensure that relinking occurs, if at all, only in compliance with legal requirements in-country when necessary for authorized processing.
  
  For example, a financial institution transferring client data for international auditing might replace names and account numbers with unique identifiers. The original identifiers are stored securely within China and can only be accessed under specific, legally permissible conditions, like a court order. This ensures that while the data is usable for necessary processing, it can be relinked to its source only when strictly required.
  
  
  

This twin-pronged approach isn't just about ensuring compliance with PIPL; it's about recognizing and meeting your needs for precision and value in your data. These adequate protection techniques extend beyond mere regulatory checkboxes, empowering your global collaboration efforts, sparking innovation, and enhancing productivity through diverse inputs.

In both scenarios, it's crucial to anonymize the data and evaluate privacy risks thoroughly. To address this need, Data Embassy offers an open-source tool called Anonymeter. This tool allows you to measure the level of data protection by testing the data against various known privacy attacks. The outcome is a provable and measurable privacy assessment, providing a quantifiable assurance of the data's privacy and security levels.

• Linking to value above: Anonymization aligns with the opportunity to harness a global workforce and enhance AI/ML capabilities without compromising on legal obligations.
  
  
• Speed to insight: Anonymization streamlines data analysis, reducing delays caused by compliance checks, thus accelerating the time to insight for businesses.
  
  
• Risk avoidance: By complying with PIPL through anonymization, companies mitigate legal risks and bolster consumer trust.
  
  
• Personal information definition: As per PIPL, anonymized information falls outside the definition of personal information, offering more flexibility in its usage
  
  

Data anonymization emerges as a vital strategy under laws like China's PIPL. By embracing anonymization, your global business can stay compliant with data protection laws. If you’re also looking to launch cross-border data transfer initiatives and capitalize on the opportunities of global data accessibility, get in touch with us.