Summary
Focus
The increasing use of digital payments, smartphones and data-driven technologies makes privacy a critical issue in the public policy discussion of digital money. We explore how technology can address these concerns, offering a comprehensive evaluation of privacy-enhancing technologies for large-scale payment systems.
Contribution
We systematically analyse the trade-offs involved in implementing privacy-enhancing technologies. Unlike previous studies that often treat privacy and transparency as mutually exclusive, we investigate more sophisticated approaches that can balance both objectives. We introduce a detailed taxonomy of privacy solutions, covering both technology-based and institution-based approaches.
Our analysis includes privacy metrics and technologies such as zero-knowledge proofs, homomorphic encryption, multi-party computation, anonymity-enhanced signatures, tamper-resistant hardware, trusted computing and metrics like k-anonymity and differential privacy.
Findings
We highlight the inherent trade-offs between privacy, auditability and performance in digital payment systems. For example, zero-knowledge proofs can verify information without revealing it, offering strong privacy protection. However, current metrics and technologies are still computationally intensive and can slow down system performance substantially. We emphasise the importance of both "hard privacy" (achieved through cryptographic methods and user-controlled data) and "soft privacy" (enforced through institutional controls and data protection policies). While some technological solutions for hard privacy show significant promise, further development is necessary to overcome current performance challenges. We conclude by examining a hybrid approach that combines hard and soft privacy measures to develop robust, scalable and privacy-preserving digital payment systems.
Abstract
How can technology enhance privacy in digital payment systems? This paper presents a systematic evaluation of the interests of privacy-conscious users, commercial data holders, and law enforcement. We classify privacy-enhancing designs along the dimensions of privacy versus auditability, as well as soft institution-based versus hard technology-based solutions. We map existing technologies into this taxonomy and assess them. Sophisticated techniques allow having both hard privacy and limited transparency by employing hard-coded rules that dictate which data remains inaccessible. On balance, there is promise in novel concepts like modern zero-knowledge-proofs, but current technologies also suffer from limitations in terms of security and computational capacity. More technological development is needed in this area. Additionally, efforts could focus on technological development that augments such hard privacy with technologically-enforced access control and systems minimizing the amount of data that is being stored, render abuse transparent and make data holders accountable.
JEL classification: E42, G23, G28, O32
Keywords: privacy, privacy-enhancing technology, payments, BigTech, fintech, regulation, smart contracts, zero-knowledge proofs, applied cryptography, digital money, digital currency, stablecoins
