A new blockchain money laundering detection system developed by University of Birmingham researchers promises faster and more accurate tracking of illicit crypto transactions.
The system, called SynapTrack, was unveiled at the CyberASAP Demo Day in London. As blockchain activity continues to grow rapidly, regulators and financial institutions face increasing pressure to identify suspicious transactions in real time. Therefore, solutions that improve accuracy and reduce manual workload are becoming essential.
Unlike traditional systems, which often generate large volumes of false alerts, SynapTrack aims to streamline detection while improving confidence in results. Consequently, compliance teams can act more quickly and reduce operational bottlenecks.
Photo Credit: University of Birmingham
Blockchain Money Laundering Detection Improves Accuracy
The blockchain money laundering detection capabilities of SynapTrack address a key industry challenge. Currently, many systems produce false positives in up to 40% of flagged cases. As a result, compliance professionals must manually review large volumes of alerts, which slows response times.
However, SynapTrack significantly reduces false positives while maintaining high detection accuracy. In testing, the system analysed real-world data from the 2025 Bybit hack, where $1.5bn in digital assets was stolen. Impressively, it traced the attacker with 98% accuracy.
This improvement allows investigators to prioritise genuine threats. In turn, organisations can respond more effectively to financial crime risks.
Adapting to Evolving Criminal Tactics
Blockchain transactions often span multiple networks, which makes tracing illicit funds more complex. For example, criminals frequently use cross-chain transfers to obscure transaction trails. Because of this, traditional anti-money laundering systems struggle to maintain visibility. At the same time, wider digital security risks are increasing, as highlighted in our coverage of AI-generated password vulnerabilities and their impact on cyber resilience.
SynapTrack addresses this challenge through a self-improving algorithm. It continuously adapts to new laundering techniques and dynamically identifies suspicious patterns. Furthermore, its cross-chain capability enables investigators to follow funds across different blockchain networks.
Importantly, the system integrates with existing compliance workflows. It presents findings through a dashboard without requiring infrastructure changes. Therefore, organisations can deploy the technology quickly and efficiently.
Strengthening the UK’s Cyber and FinTech Innovation
The system was developed by Dr Pascal Berrang and PhD researcher Endong Liu at the University of Birmingham, in collaboration with blockchain developer Nimiq. Together, they combined expertise in cybersecurity, artificial intelligence and blockchain systems.
This innovation reflects broader growth in the UK’s cybersecurity and digital finance ecosystem. Consequently, academic research and commercial innovation are becoming increasingly aligned.
Dr Berrang noted that blockchain adoption has grown rapidly in recent years. While many transactions remain legitimate, the speed and cross-border nature of blockchain also attract criminal activity. Therefore, improving detection systems will play a key role in building trust across the ecosystem.
Towards Safer Blockchain Systems
As blockchain usage expands, the need for effective regulation and monitoring tools will continue to grow. Consequently, systems like SynapTrack could help close gaps in existing anti-money laundering frameworks.
Overall, the development highlights how UK research institutions are contributing to global cybersecurity challenges. By combining AI, blockchain expertise and real-world testing, the project demonstrates how innovation can strengthen financial system integrity.
