Articlegold2018

A Classification Based Model to Assess Customer Behavior in Banking Sector

11 citations0/0 files storedEngineering Technology & Applied Science Research

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Customer churn and segmentation Data Mining and Machine Learning Applications Financial Distress and Bankruptcy Prediction

Abstract

A customer relationship management system is used to manage company relationships with current and possible customers. Following a thorough review of contemporary literature, different data mining techniques employed in different types of business, corporate sectors and organizations are analyzed. A model that would be helpful to identify customers’ behavior in the banking sector is then proposed. Three classifiers, k-NN, decision tree and artificial neural networks are used to predict customer behavior and are assessed in order to determine which classifier performs better for predicting customer behavior in the banking sector.

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2009Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty 2011Estimating customer lifetime value based on RFM analysis of customer purchase behavior: Case study 2015An Efficient CRM-Data Mining Framework for the Prediction of Customer Behaviour 2012CRM strategies for a small-sized online shopping mall based on association rules and sequential patterns 2014Bank Direct Marketing Analysis of Data Mining Techniques 2012Customer data mining for lifestyle segmentation 2012Predicting customer profitability during acquisition: Finding the optimal combination of data source and data mining technique 2010Facilitating cross-selling in a mobile telecom market to develop customer classification model based on hybrid data mining techniques

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