An Implementation of Quantum Machine Learning Technique to Determine Insurance Claim Fraud
Subodh Nath Pushpak, Sarika Jain · 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) · 2022
Quantum Machine Learning (QML) is an upcoming and active research field that uses quantum computing concepts for machine learning. This paper presents QML techniques for detecting fraud in housing insurance claims. Insurance fraud detection is challenging as the patterns may be complex. Therefore, various techniques and methods are employed to identify suspicious claims and prevent business losses due to these fraudulent claims. This paper explores Quantum Support Vector Machine (QSVM) techniques and feature engineering, feature selection, and parameter tweaking to identify fraudulent housing insurance claims. In addition, it compares Quantum SVM with classical SVM. Finally, this paper focuses on detecting property insurance claims fraud by using machine learning techniques.