Financial Fraud Detection: A Comparative Study of Quantum Machine Learning Models. (arXiv:2308.05237v1 [quant-ph])

In this research, a comparative study of four Quantum Machine Learning (QML)
models was conducted for fraud detection in finance. We proved that the Quantum
Support Vector Classifier model achieved the highest performance, with F1
scores of 0.98 for fraud and non-fraud classes. Other models like the
Variational Quantum Classifier, Estimator Quantum Neural Network (QNN), and
Sampler QNN demonstrate promising results, propelling the potential of QML
classification for financial applications. While they exhibit certain
limitations, the insights attained pave the …

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