Record Details

PREDICTIVE MODEL IN INSURANCE INDUSTRY USING R TOOL

Journal of Research in Commerce & Management

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Title PREDICTIVE MODEL IN INSURANCE INDUSTRY USING R TOOL
 
Creator Sunita Patil,Dr. Smita Chavan, .; 14/2,Yusuf Palace, Mumbai 400 016
 
Subject Churn, Prediction, R Tool, Insurance Industry, Data mining
 
Description Insurance market is growing day by day. Industries are facing a severe loss of profits due to increasing contests hence the loss of customers. They are trying to find the causes of losing customers by measuring customer loyalty to regain the lost customers. The customers leaving the current industry and moving to another insurance industry are called churn. The research paper is using application of data mining technology and R package to predict the results of churn customers on the insurance transaction customer dataset from LIC, AVIVA, MAX LIFE Insurance Company. The R tool has represented the large dataset churn in form of graphs which depicts the outcomes in various unique pattern visualizations. The Churn Factor is used in many functions to depict the various areas or scenarios where churners can be distinguished. The paper is logistic regression, decision tree, Random forest, Support vector machine model building to predict churn customer in insurance sector considering churn factor in account to depict various patterns for churners. R is a powerful statistical programming tool which can represent the dataset graphically with respect to different parameters and it also uses different packages available. Churns can be reduced by analyzing the past history of the potential customers systematically. In the past few years, the fast emerging requirements from both academia and industry has helped R programming language to emerge as one of the necessary tool for visualization, computational statistics and data science.
 
Publisher Abhinav-National Monthly Refereed Journal Of Research In Commerce & Management (Online ISSN 2277-1166)
 
Contributor —
 
Date 2017-12-19
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://abhinavjournal.com/journal/index.php/ISSN-2277-1166/article/view/1616
 
Source Abhinav-National Monthly Refereed Journal Of Research In Commerce & Management (Online ISSN 2277-1166); Vol 6, No 12 (2017): Abhinav-National Monthly Refereed Journal Of Research In Commerce & Management (Online ISSN 2277-1166) UGC approved; 60-65
2277-1166
 
Language eng
 
Relation http://abhinavjournal.com/journal/index.php/ISSN-2277-1166/article/view/1616/pdf_404
 
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