Insurance Approval Analysis using Machine Learning Algorithms - Vinay, CH. Lakshman; Sagar, G. Vijay; Ajay, M; Hussain, SK; Padma, Bh (International Journal of Computer Sciences and Engineering, 2020)
Risk Management is important for insurance industry to ensure the eligibility of a new customer for approval. Insurance companies need to analyze the existing customer’s information such as income, assets, occupation, premium payment records to decide whether a new customer is qualified for an insurance policy. This paper focuses on forecasting the eligibility of the new customers for insurance approval by performing classification on a real time insurance company dataset using three Machine Learning algorithms such as Decision Tree Induction, Naive Bayes Classification and K- Nearest Neighbor algorithms. These algorithms are examined against their classifier accuracy after implementation and the algorithm that demonstrates the best accuracy is chosen for predicting the new customer.