• Successful completion of the next stage of Archer's QML fraud detection project
• QNN fraud detection model tested and benchmarked using a financial fraud dataset
• Model performed equivalently to best classical models with a low false-positive rate
• Model executed on IQM Garnet, a commercial superconducting quantum computer
• Substantial reduction in technical uncertainty, paving the way for future testing

Archer Materials Limited has successfully completed the next stage of its quantum machine learning (QML) fraud detection project. The project, which aims to develop advanced quantum technologies for financial services, has achieved several key milestones. A quantum neural network (QNN) fraud detection model was tested and benchmarked using a publicly available financial fraud dataset. The model performed well, correctly identifying 118 fraudulent transactions with only one false positive. The model was also executed on IQM Garnet, a commercial superconducting quantum computer, demonstrating its potential for real-world applications. These results have reduced technical uncertainty and established a foundation for further testing on larger quantum systems. The project is part of Archer's strategy to explore practical applications of quantum computing technologies.

Archer aims to develop a full QML prototype by the end of the year, with further testing required before any commercial deployment pathway can be assessed.