Variational Quantum Algorithms in Anomaly Detection, Fraud Indicator Identification, Credit Scoring, and Stock Price Prediction

The quantum processors’ performance is predicted to surpass the application of variational quantum algorithms in finance has proven to be instrumental in addressing crucial challenges. From enhancing security through anomaly detection and fraud indicator identification to optimizing credit scoring and improving stock price prediction, VQAs demonstrate their versatility and potential to revolutionize the financial industry’s analytical capabilities. As quantum computing continues to advance, the integration of VQAs is expected to play an increasingly pivotal role in shaping the future of financial technology. In this paper, we review variational quantum algorithms in anomaly detection and fraud indicator systems, credit scoring, and stock price prediction.