Insights Gleaned from the FPF's Workshop on Privacy-Boosting Technologies
In the realm of cross-border fraud detection and data privacy preservation, Privacy Enhancing Technologies (PETs) have taken centre stage. These cutting-edge solutions are designed to ensure compliance with complex cross-jurisdictional privacy regulations while maintaining operational efficiency and robust fraud detection.
Fully Homomorphic Encryption (FHE)
One such technology is Fully Homomorphic Encryption (FHE), a technique that enables analysis of encrypted data without exposing the raw data itself. Mastercard has successfully implemented FHE in a pilot system, which allows encrypted data, such as International Bank Account Numbers, to be checked for fraud risk across different jurisdictions. This groundbreaking approach supports interoperability between financial institutions and governments while preserving strong privacy protections (sources: [1], [3], [4]).
Differential Privacy
Differential Privacy is another essential PET, particularly valuable in scenarios where companies need to generate useful data summaries or analyse patterns from personal data while complying with data deletion laws like the GDPR. By anonymizing data before deletion, differential privacy preserves privacy without compromising on utility (source: [3]).
Trusted Execution Environments (TEEs)
Trusted Execution Environments (TEEs) are also key players in the PETs landscape. These secure enclaves allow secure data collaboration without raw data exposure, making them ideal for use cases such as advertising data sharing (sources: [2], [4]).
Device Intelligence and Behavioral Analysis
In addition to the above, device intelligence and behavioral analysis play a crucial role in real-time fraud prevention. By analysing device and user behaviour signals, these technologies help detect fraud and provide explainable, actionable insights that prevent unauthorized cross-border access and reduce regulatory risk (sources: [2], [4]).
The Role of Synthetic Data and Regulatory Sandboxes
The development and proof of concept of PETs relies heavily on synthetic data and regulatory sandboxes. These tools are essential for testing and validating the effectiveness of these technologies in real-world scenarios (source: unspecified).
Workshops and Issue Briefs
In April, a workshop was hosted by the Future of Privacy Forum (FPF) and the Mozilla Foundation, featuring technology, legal, and policy experts discussing Privacy Enhancing Technologies (PETs). FPF has also published several issue briefs, including one on "PETs Use Case: Preventing Financial Fraud Across Different Jurisdictions with Fully Homomorphic Encryption" and another on "PETs Use Case: Differential Privacy for End-of-Life Data" (sources: [5], [6]).
Regulatory Challenges
Despite the advancements in PETs, there remains a lack of clear regulatory guidance, necessitating reliance on best practices, trust, and adherence to local laws between/across jurisdictions (source: unspecified).
The Future of PETs
As companies grapple with the high cost and regulatory uncertainty associated with PETs, there is a growing need for more incentives to develop and implement these technologies. However, with continued collaboration and innovation, PETs promise to revolutionize the way we approach cross-border fraud detection and data privacy preservation.
- Fully Homomorphic Encryption (FHE), a technology that enables analysis of encrypted data without exposing the raw data, was successfully implemented by Mastercard in a pilot system for cross-jurisdictional fraud risk checks.
- Differential Privacy, another Privacy Enhancing Technology (PET), is valuable in situations where companies must comply with data deletion laws like the GDPR while generating useful data summaries or analyzing personal data.
- Trusted Execution Environments (TEEs), secure enclaves for secure data collaboration without raw data exposure, are valuable in use cases such as advertising data sharing.
- Device intelligence and behavioral analysis help prevent real-time fraud by detecting fraud using device and user behavior signals, providing explainable and actionable insights.
- The development and testing of PETs rely on synthetic data and regulatory sandboxes, essential tools for validating their effectiveness in real-world scenarios.
- In April, a workshop featuring technology, legal, and policy experts was hosted by the Future of Privacy Forum (FPF) and the Mozilla Foundation to discuss Privacy Enhancing Technologies (PETs).
- Despite advancements in PETs, there remains a lack of clear regulatory guidance, necessitating reliance on best practices, trust, and adherence to local laws between/across jurisdictions. As companies face high costs and regulatory uncertainty associated with PETs, there is a growing need for more incentives to develop and implement these technologies, promising to revolutionize cross-border fraud detection and data privacy preservation.
