Imagine logging into your cryptocurrency exchange platform one morning only to find the website down, your funds gone, and no one to answer your questions. This nightmare has been a harsh reality for thousands of traders, with nearly 500 cryptocurrency exchanges having already failed. A new study from the University of Vaasa, Finland, sheds light on the risk factors in cryptocurrency exchanges.
In his study, published in the valued Journal of International Financial Markets, Institutions & Money, Assistant Professor Niranjan Sapkota analyses data from 845 cryptocurrency exchanges to investigate why nearly half of these exchanges have collapsed since 2014 and how to predict such defaults. He identifies several key indicators including transparency, centralisation, territorial access, fee structures, coin listings, referral schemes, etc., offering valuable insights into mitigating risks in this evolving market.
When transparency becomes a double-edged sword
Centralised exchanges in developed, transparent, and well-regulated countries, such as United States and Singapore are often perceived as the safest. According to the study, they are surprisingly fragile. This fragility arises from pressures such as stringent regulations, high compliance costs, and advanced infrastructures that fraudsters can exploit for illicit activities. In contrast, developing nations, where cryptocurrency adoption remains under policy debate, face fewer such challenges.
– Even more strikingly, exchanges that allow U.S. customers to trade experience higher probability of default compared to those that restrict U.S. clients, Sapkota adds.
All in all, centralised exchanges, which manage wallet custody on behalf of users similar to how traditional banks manage accounts, have a higher risk of default than decentralised exchanges (DEXs), where users retain self-custody of their assets and conduct transactions directly on the blockchain. DEXs have a 31.2% lower probability of failure compared to centralised platforms, as their distributed structure mitigates risks related to fraud, operational mismanagement, and liquidity crises.
Warning signs: high fees, limited coin listings and poor ratings
According to the study, high withdrawal fees often signal financial instability. Defaulted exchanges charged withdrawal fees on average 1.5 times higher than operational ones.
Furthermore, exchanges offering a wide variety of cryptocurrencies and maintaining high user ratings are more likely to survive. A diverse range of cryptocurrencies attracts a larger user base and ensures steady revenue streams whereas high user ratings typically reflect strong operational practices. The study also indicated that exchanges with referral incentives are less likely to default.
– So, next time a friend shares a legitimate crypto exchange referral link, don't dismiss it as mere bonus hunting, says Dr. Sapkota.
Robust results for creating a safer crypto ecosystem
This cutting-edge research bridges a critical knowledge gap in the emerging field of cryptocurrency exchange risk, offering the knowledge needed to approach the market with greater confidence, and actionable solutions for more secure blockchain-based digital asset trading platforms.
The study also highlights the effectiveness of traditional statistical methods, such as logit and probit models, in predicting cryptocurrency exchange bankruptcies, achieving an accuracy rate of approximately 81%. Cutting-edge machine learning techniques, including Random Forest, Support Vector Machine, and Stacked Ensemble, validate these findings.
– Policy makers can leverage these findings to design policies that protect users and strengthen market stability. Investors and traders can learn to spot critical red flags – such as poor ratings, excessive withdrawal fees, limited coin offerings, centralised exchanges, and U.S. client access – to avoid unreliable platforms and safeguard investments, Sapkota explains the applications of his research.
Further information
Sapkota, N. (2025) The Crypto Collapse Chronicles: Decoding Cryptocurrency Exchange Defaults. Journal of International Financial Markets, Institutions & Money. Vol. 99, article 102093.
https://doi.org/10.1016/j.intfin.2024.102093
Contact information
Niranjan Sapkota, Assistant Professor of Finance, University of Vaasa
+358 46 84 18 558