PREDICTING THE INSURANCE CLAIM BY EACH USER USING MACHINE LEARNING ALGORITHMS

Authors

  • Seshu Kumar Vandrangi Doctoral Research Fellow, Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Persiaran UTP, 32610 Seri Iskandar, Perak, Malaysia

Keywords:

Data pre-processing, Artificial Neural Networks, Capital, Random Forest Regressors, Logistic Regression

Abstract

Today, data will play a critical role and become a significant wealth creator in the insurance sector. The insurance sector is very significant in today's travel industry. Insurance companies now have more information than ever before. There have been three key eras in the insurance sector over the last 700 years. The manual era lasted from the 15th century to the 1960s, the system age from the 1960s to the 2000s, and now the digital age. H. 2001-20X0. In all three periods, the ultimate corporate objective has been pushed by
the core insurance industry's conviction in data analytics to accept evolving technologies in order to enhance its route and concentrate capital. That's all. Inadequate analytical models and algorithms to serve insurance businesses is a big concern in advanced analytics. Only machines are capable of overcoming this obstacle. In this paper, insurance data based on some features are trained and tested over Artificial Neural Networks, Random Forest Regressors, Logistic Regression and predict the charges based on features for predicting the insurance claim.

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Published

2024-09-24

Issue

Section

Articles