Financial Fraud Detection: A Comparative Study of Quantum Machine Learning Models

Abstract

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 way for future enhancements and optimisation strategies. However, challenges exist, including the need for more efficient Quantum algorithms and larger and more complex datasets. The article provides solutions to overcome current limitations and contributes new insights to the field of Quantum Machine Learning in fraud detection, with important implications for its future development.

arXiv comment30 pages, 15 figures, and 2 tables

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Cited by in corpus (14)

• Enhancing Quantum Support Vector Machines through Variational Kernel Training
• FedQNN: Federated Learning using Quantum Neural Networks
• QFNN-FFD: Quantum Federated Neural Network for Financial Fraud Detection
• QADQN: Quantum Attention Deep Q-Network for Financial Market Prediction
• Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy
• PhishVQC: Optimizing Phishing URL Detection with Correlation Based Feature Selection and Variational Quantum Classifier
• Simulation of a Variational Quantum Perceptron using Grover's Algorithm
• A Privacy-Preserving Federated Framework with Hybrid Quantum-Enhanced Learning for Financial Fraud Detection
• LEP-QNN: Loan Eligibility Prediction using Quantum Neural Networks
• Quantum Portfolio Optimization with Expert Analysis Evaluation
• Comparative Performance Analysis of Quantum Machine Learning Architectures for Credit Card Fraud Detection
• Evaluating Quantum Amplitude Estimation for Pricing Multi-Asset Basket Options
• Towards Quantum-Ready Blockchain Fraud Detection via Ensemble Graph Neural Networks
• IQNN-CS: Interpretable Quantum Neural Network for Credit Scoring