Archer Materials and CSIRO are developing quantum machine learning models that could transform how organisations spot anomalies in financial data.
What’s happening: Archer Materials has partnered with CSIRO to develop quantum machine learning models designed to detect fraud in financial transactions. The year-long project, running from November 2025 to November 2026, will create prototype quantum models and performance benchmarks using simulated financial datasets.
Why this matters: Quantum machine learning offers potential advantages in reliability, training speed, and feature extraction that could transform fraud detection across finance, healthcare, cybersecurity, and other sectors.
An Australian technology company is joining forces with the nation’s science agency to tackle one of the financial sector’s most persistent challenges using quantum computing.
Archer Materials, a semiconductor developer focused on quantum technology and medical diagnostics, has signed a Research Services Agreement with CSIRO’s data and digital specialist arm to develop a quantum machine learning system for detecting fraud in financial transactions.
The collaboration will run from November 2025 to November 2026, with the project focusing on developing quantum machine learning models to enhance detection of fraudulent activities. Initial outcomes will include prototype quantum models and performance benchmarks tested across simulated financial datasets.
Billion-dollar problem
Fraudulent financial activity represents a major global challenge, costing organisations billions of dollars each year. The scale and sophistication of fraud continues to evolve, requiring increasingly complex detection systems.
Fraud detection demands rapid and accurate identification of anomalies including forged signatures, unauthorised transactions, and identity manipulation. However, traditional systems often operate reactively, proving complex to maintain and limited in their ability to detect sophisticated patterns that indicate fraudulent behaviour.
The collaborative project between Archer and CSIRO aims to develop new and innovative quantum machine learning models capable of detecting fraud in financial transactions. Once these quantum machine learning models are trained, the fraud detection framework will rapidly identify and flag anomalies arising from fraudulent activities.
Quantum advantage
Quantum machine learning has the potential to offer enhanced reliability, training speed advantages, and unique feature extraction capabilities compared to classical computing approaches. These advantages could prove crucial in identifying complex fraud patterns that traditional systems miss.
The project will build upon CSIRO’s existing expertise in quantum machine learning to develop models specifically tailored for financial fraud detection. Hybrid quantum-classical machine learning models that adapt classical neural network architectures for quantum computing form the technical foundation of the approach.
“This partnership with CSIRO represents a significant step in growing Archer’s quantum IP portfolio. Fraud detection is a critical challenge globally, and quantum machine learning offers a transformative way to address it,” said Simon Ruffel, CEO of Archer Materials.
Beyond finance
Whilst the initial focus centres on financial fraud detection, the applications of quantum machine learning extend far beyond the finance sector. The technology being developed could potentially adapt for use in healthcare, energy grid optimisation, manufacturing, autonomous vehicles, defence and aerospace, cybersecurity, and artificial intelligence applications.
This broad applicability underscores the significance of the research, with potential implications for multiple industries facing similar challenges in pattern recognition and anomaly detection.
Year-long development
The 12-month research project represents part of Archer’s broader strategy to commercialise near-term quantum applications with global impact. Rather than focusing solely on long-term theoretical quantum computing applications, the company is pursuing practical implementations that could deliver value in the near future.
The collaboration with CSIRO, Australia’s national science agency, provides Archer access to deep expertise in quantum machine learning research whilst allowing CSIRO to work on practical applications of its quantum research capabilities.
As quantum computing continues its transition from laboratory research to practical applications, partnerships between technology companies and research institutions are becoming increasingly important. The Archer-CSIRO collaboration represents this trend, combining commercial focus with scientific rigour to address real-world challenges.
For the financial sector, which loses billions annually to fraud, the development of more sophisticated detection systems using quantum machine learning could provide a significant competitive advantage. The coming year will reveal whether quantum computing can deliver on its promise to revolutionise fraud detection and potentially transform how organisations protect themselves against increasingly sophisticated fraudulent activities.
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