A Case Study of Predicting Banking Customers Behaviour by Using Data Mining

Xujuan Zhou, Ghazal Bargshady, Moloud Abdar, Xiaohui Tao, Raj Gururajan, K. C. Chan

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

1 Citation (Scopus)

Abstract

Data Mining (DM) is a technique that examines information stored in large database or data warehouse and find the patterns or trends in the data that are not yet known or suspected. DM techniques have been applied to a variety of different domains including Customer Relationship Management CRM). In this research, a new Customer Knowledge Management (CKM) framework based on data mining is proposed. The proposed data mining framework in this study manages relationships between banking organizations and their customers. Two typical data mining techniques-Neural Network and Association Rules-are applied to predict the behavior of customers and to increase the decision-making processes for recalling valued customers in banking industries. The experiments on the real world dataset are conducted and the different metrics are used to evaluate the performances of the two data mining models. The results indicate that the Neural Network model achieves better accuracy but takes longer time to train the model.

Original languageEnglish
Title of host publicationBESC 2019 - 6th International Conference on Behavioral, Economic and Socio-Cultural Computing, Proceedings
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-6
Number of pages6
ISBN (Electronic)9781728147628
ISBN (Print)9781728147635
DOIs
Publication statusPublished - Oct 2019
Externally publishedYes
Event6th International Conference on Behavioral, Economic and Socio-Cultural Computing, BESC 2019 - Beijing, China
Duration: 28 Oct 201930 Oct 2019

Publication series

NameBESC 2019 - 6th International Conference on Behavioral, Economic and Socio-Cultural Computing, Proceedings

Conference

Conference6th International Conference on Behavioral, Economic and Socio-Cultural Computing, BESC 2019
Country/TerritoryChina
CityBeijing
Period28/10/1930/10/19

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