Decentralised Finance’s timocratic governance: The distribution and exercise of tokenised voting rights

Barbereau, Tom; Smethurst, Reilly; Papageorgiou, Orestis; Sedlmeir, Johannes; Fridgen, Gilbert

doi:10.1016/j.techsoc.2023.102251

Cited by 14 publications

(1 citation statement)

References 45 publications

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“…The promises of what, in principle, should be an equitable and disintermediated, consensus-based management system stand in contrast to reality. For example, it is not uncommon for a small number of agents to hold the bulk of governance tokens, either due to market dynamics or as a result of abusing certain operational practices (flash loans) 14 (Barbereau, Smethurst, Papageorgiou, Sedlmeir and Fridgen, 2023).…”

Section: Defi Risksmentioning

confidence: 99%

Decentralised finance: the latest generation of crypto-assets

Gorjon

2023

Economic Bulletin

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Rationale This article is intended as an introduction to the world of decentralised finance (DeFi). To this end, the focus is to explain, in a simplified manner, its key characteristics and most common use cases, along with the main risks. Takeaways •DeFi is one of the latest developments in the crypto-asset space and also the segment where most of the recent bouts of sector turmoil have taken place. It is a complex, but still largely endogenous, ecosystem and therefore its interaction with the real economy is limited. •DeFi is actually less decentralised than it purports to be. Its real benefits are limited, while the potential risks are considerable. Although the risks are not substantially different from those in the traditional financial sector, their drivers, speed of propagation and scale can differ entirely, compromising the authorities’ room to manoeuvre. •Although the policy and regulatory effort is, for now, focused on traditional crypto-assets, there is a growing debate as to what mix of measures would best contribute to mitigating the risks of DeFi. More specific action in this regard is expected in the years ahead.

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Section: Defi Risksmentioning

confidence: 99%

Decentralised finance: the latest generation of crypto-assets

Gorjon

2023

Economic Bulletin

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Detecting anomalous cryptocurrency transactions: An AML/CFT application of machine learning-based forensics

et al. 2023

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In shaping the Internet of Money, the application of blockchain and distributed ledger technologies (DLTs) to the financial sector triggered regulatory concerns. Notably, while the user anonymity enabled in this field may safeguard privacy and data protection, the lack of identifiability hinders accountability and challenges the fight against money laundering and the financing of terrorism and proliferation (AML/CFT). As law enforcement agencies and the private sector apply forensics to track crypto transfers across ecosystems that are socio-technical in nature, this paper focuses on the growing relevance of these techniques in a domain where their deployment impacts the traits and evolution of the sphere. In particular, this work offers contextualized insights into the application of methods of machine learning and transaction graph analysis. Namely, it analyzes a real-world dataset of Bitcoin transactions represented as a directed graph network through various techniques. The modeling of blockchain transactions as a complex network suggests that the use of graph-based data analysis methods can help classify transactions and identify illicit ones. Indeed, this work shows that the neural network types known as Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT) are a promising AML/CFT solution. Notably, in this scenario GCN outperform other classic approaches and GAT are applied for the first time to detect anomalies in Bitcoin. Ultimately, the paper upholds the value of public–private synergies to devise forensic strategies conscious of the spirit of explainability and data openness.

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