CBDCs vs. Cryptocurrencies: Comparative Analysis of Privacy Approaches Using NLP

Abstract

Central Bank Digital Currencies (CBDCs) and cryptocurrencies differ significantly in terms of privacy and regulatory compliance. While cryptocurrencies provide strong anonymity, CBDCs cannot follow the same design. As state-issued digital currencies, they must embed regulatory compliance directly into their architecture while potentially incorporating Privacy-Enhancing Technologies (PETs) to protect user data. This paper provides an overview of how different PETs are used in CBDCs and cryptocurrencies. Using Natural Language Processing (NLP) on a corpus of 177 documents covering four major CBDCs (DCash, eNaira, JAM-DEX, Sand Dollar) and four cryptocurrencies (Bitcoin, Ethereum, Monero, Zcash), we analyse how privacy concepts and PETs are framed. Findings reveal that cryptocurrencies embed privacy at a technical level, while CBDCs treat PETs mainly as conceptual compliance tools, highlighting distinct paradigms in privacy implementation.