10th International Congress on Information and Communication Technology in concurrent with ICT Excellence Awards (ICICT 2025) will be held at London, United Kingdom | February 18 - 21 2025.
Authors - Ayush Verma, Krisha Patel, Hardikkumar Jayswal, Nilesh Dubey, Dipika Damodar Abstract - Insurance fraud significantly undermines the financial stability of the insurance industry, resulting in billions of dollars lost annually due to fraudulent claims across sectors like healthcare, auto, and property insurance. This paper proposes a robust methodology for detecting insurance fraud through the strategic implementation of ensemble machine learning algorithms, specifically XGBoost and Random Forest. By analyzing extensive datasets that include policyholder demographics, claim histories, and risk factors, we develop predictive models that accurately identify fraudulent activities while minimizing false positives. The effectiveness of our approach is supported by a comprehensive literature review highlighting the performance of various machine learning models in fraud detection, as well as our application of preprocessing techniques and feature selection to enhance model accuracy. Our findings indicate that the integration of advanced AI and ML technologies can revolutionize fraud detection in the insurance sector, offering a more secure and efficient environment for both insurers and policyholders.
