Risk Management in DeFi: Analyses of the Innovative Tools and Platforms for Tracking DeFi Transactions

Abstract

Decentralized Finance (DeFi) is a recent advancement of the cryptocurrency ecosystem, giving plenty of opportunities for financial inclusion, innovation, and growth domains by providing services such as lending, borrowing, and trading without traditional intermediaries. However, inadequate regulatory oversight and technological vulnerabilities raise pressing concerns around market manipulation, fraud, and regulatory compliance, exposing a clear research gap in effective DeFi risk management. This paper addresses this gap by proposing a utility-based framework to evaluate six leading DeFi tracking platforms - Chainalysis, Elliptic, Nansen, Dune Analytics, DeBank, and Etherscan - focusing on two critical metrics: transaction accuracy and real-time responsiveness. Applying a mixed methods approach that combines a quantitative survey (n = 138) with qualitative interviews (n = 12), we identified critical platform features and found significant differences across these platforms with respect to compliance features, advanced analytics, and user experience. We used a utility-based model that links accuracy and responsiveness metrics, allowing us to adjust differing priorities and risk management needs for users. The results show the need for balanced, user-centric solutions that accommodate regulatory, technological efficiency and affordability requirements. Our study contributes to the growing knowledge base by providing a structured evaluation model and empirical insights, offering clear directions for practitioners, platform developers, and policymakers aiming to strengthen the DeFi ecosystem.

Publication DOI: https://doi.org/10.3390/jrfm18010038
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences
College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Cyber Security Innovation (CSI) Research Centre
Aston University (General)
Funding Information: This research was funded by the Innovate UK CyberASAP grant 10139989.
Additional Information: Copyright © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords: risk management,Decentralised finance,blockchain,Cryptocurrencies,AI,machine learning,AML,transaction tracking
Publication ISSN: 1911-8074
Data Access Statement: The data supporting this study’s findings are available from the corresponding author when it is a reasonable request.
Last Modified: 31 Mar 2025 07:27
Date Deposited: 17 Jan 2025 15:40
Full Text Link:
Related URLs: https://www.mdp ... 11-8074/18/1/38 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2025-01-16
Accepted Date: 2025-01-14
Authors: Adamyk, Bogdan (ORCID Profile 0000-0001-5136-3854)
Benson, Vladlena (ORCID Profile 0000-0001-5940-0525)
Adamyk, Oksana
Liashenko, Oksana

Download

[img]

Version: Published Version

License: Creative Commons Attribution

| Preview

Export / Share Citation


Statistics

Additional statistics for this record