CAR INSURANCE RISK PREDICTION USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

Abstract

Car insurance risk prediction is a critical aspect of the insurance industry, helping insurers assess potential claims, optimize premium pricing, and mitigate fraudulent activities. This study explores the application of artificial intelligence (AI) and Machine Learning (ML) techniques, particularly Random Forest classification, to predict car insurance risks using publicly available datasets from Kaggle. By implementing feature extraction and classification methodologies, this research demonstrates the effectiveness of AI-driven predictive models in enhancing risk assessment accuracy and operational efficiency in the insurance sector.