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Rajasekaran, Thangavelu Ananadaraj
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Study on postal life insurance attributes and its growth prediction using machine learning algorithms Rajasekaran, Thangavelu Ananadaraj; Vijayalakshmi, Pichamuthu; Rajendran, Velayutham
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp622-631

Abstract

The oldest insurer in the country, since 1884, is Postal Insurance. For today's livelihood, the citizens of India's life-saving coverage and insurance have become necessary. For customers to overcome difficult situations, life insurance is crucial in creating confidence. This is one of the highlights of the Postal organization. Under postal life insurance (PLI), the volume of new policies is enrolled throughout India, and a supervised machine learning (ML) process for finding the business cluster is carried out based on this data, which is discussed. A ML algorithm that predicts the growth for the future, using a suitable algorithm for accessing the features and process to identify the prediction model, has been developed, which is the main goal of this study. Simulation results show that expected is one of the most important variables used to predict and that both random forest (RF) and logistic regression outperformed the other two models. The RF model is the most effective and fastest in predicting the system's future state, and it shows the highest value for the PLI product.
Co-Authors Rajendran, Velayutham Vijayalakshmi, Pichamuthu