Prediction of Health Insurance Price using Machine Learning Algorithms

In the realm of health insurance pricing prediction, this research leverages advanced machine learning techniques, including linear regression and neural networks, to uncover pivotal insights. Smoking habits emerged as a major driver of elevated insurance charges, emphasizing the financial impact of this behavior on policyholders. Age also played a critical role, highlighting the progressive nature of healthcare costs as individual’s age. These findings offer invaluable guidance for insurers and individuals. Additionally, by providing transparent linear regression models and the predictive power of neural networks this research equips the industry with practical tools to enhance pricing accuracy in a dynamic healthcare landscape.