Bank Customer Retention Prediction And Customer Ranking Based On Deep Neural Networks
Indhuja
, Dr A.P.JAGADEESAN Ph.D
Churn Prediction, Logistic regression, Decision Tree, random forest, Artificial Neural Network.
Retention of customers is a major concern in any industry. Customer churn is an important metrics that gives hard truth about the retention percentage of customers. A detailed study about the existing models for predicting the customer churn is made and a new model based on Artificial Neural Network is proposed to find the customer churn in banking domain. The proposed model is compared with the existing machine learning models. Logistic regression, Decision Tree and random forest mechanisms are the baseline models that are used for comparison, the performance metrics that were compared are accuracy, precision, recall and F1 score. It has been observed that the artificial neural network model performs well than the logistic regression model and decision tree model. But when the results are compared with the random forest model considerable difference is not noted. The proposed model differs from the existing models in a way that it can rank the customers in the order in which they would leave the organization.
"Bank Customer Retention Prediction And Customer Ranking Based On Deep Neural Networks", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 9, page no.444 - 449, September-2020, Available :https://ijsdr.org/papers/IJSDR2009072.pdf
Volume 5
Issue 9,
September-2020
Pages : 444 - 449
Paper Reg. ID: IJSDR_192500
Published Paper Id: IJSDR2009072
Downloads: 000347208
Research Area: Engineering
Country: Dindigul, TamilNadu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
