Risk Prediction for New Insurance Using Customer Information

Abstract

Risk management is important for new authenticated customers to identify their correct insurance policy. Therefore, risk prediction of new insurance is a crucial factor in insurance business to classify the applicants. Analyzing the profile of individual applicant manually may take a very long time. By applying predictive modelling techniques may automatically classify risk level based on past data more quickly and accurately in less time and less labor.

Our project uses the data-set containing past customer information including age, height, BMI, family history, insurance history etc. along with the risk level. Hence here Supervised Machine Learning Algorithm is used to predict the risk level of different applicants. We apply Random Forest Algorithm to predict the risk level of new customer automatically.