Ben Charoenwong, Robert M. Kirby, Jonathan Reiter
We examine which decentralized finance architectures enable meaningful regulation by combining financial and computational theory. We show via deduction that a decentralized and permissionless Turing-complete system cannot provably comply with regulations concerning anti-money laundering, know-your-client obligations, some securities restrictions and forms of exchange control. Any system that claims to follow regulations must choose either a form of permission or a less-than-Turing-complete update facility. Compliant decentralized systems can be constructed only by compromising on the richness of permissible changes. Regulatory authorities must accept new tradeoffs that limit their enforcement powers if they want to approve permissionless platforms formally. Our analysis demonstrates that the fundamental constraints of computation theory have direct implications for financial regulation. By mapping regulatory requirements onto computational models, we characterize which types of automated compliance are achievable and which are provably impossible. This framework allows us to move beyond traditional debates about regulatory effectiveness to establish concrete boundaries for automated enforcement. © The Author(s) 2025.
INSEAD, Asia Campus, Singapore, 138676, Singapore; Kahlert School of Computing, University of Utah, Salt Lake City, 84112, United States; ChainArgos, Research, Singapore, 179094, Singapore
Research at a Glance
Register to unlock
Topics & SDG Alignment
Register to unlock
Collaboration
Register to unlock
Author Profile (Selected)
Register to unlock
References Overview
Register to unlock
Journal & Source
Register to unlock
Metadata & Integrity
Register to unlock