Implementing a Data Mining Solution Approach to Identify the Valuable Customers for Facilitating Electronic Banking

Dublin Core

Title

Implementing a Data Mining Solution Approach to Identify the Valuable Customers for Facilitating Electronic Banking

Subject

Customer classification
Boosting
C4.5 decision tree
Neural network
KNN

Description

Nowadays, the banking system is known as one of the inherent sectors of customer relationship management systems. Its main advantage is to redesign a more responsive organization to satisfy the customers. The banking system aims to improve the structure of organizations to provide a better customer service through a set of automated and integrated processes. The final goal is to collect and reprocess the personal information of customers. To handle this dilemma, a number of new techniques in data mining provide a powerful tool to explore customers’ information regarding a set of data and tools for customer relationship management. Accordingly, the customers’ classification and coordination of banking system are the main challenging issues of today's world. These reasons motivate the attempts of this study to apply a composition of neural network by considering the C4.5 decision tree and the k-closest neighbor method as a variant of core boosting methodology with maximal strategy. To validate the proposed solution approach, a case study of Ansar Bank in Iran is utilized. From the results, it is observed that the proposed method provides a competitive output with the rate of 95% for the customers’ classification. It also outperforms other existing methods with the rate of C4.5 decision tree, neural network, Naive Bayes and KNN with the rate of 1.04%. The main finding of this research is to propose an algorithm with the error rate of 1.9% and error squared of 0.72% as the best performance among other methods from the literature.

Creator

Sebt, Mohammad Vahid
Komijani, Elahe
Ghasemi, Shiva S.

Source

International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 15 (2020); pp. 157-174
1865-7923

Publisher

International Association of Online Engineering (IAOE), Vienna, Austria

Date

2020-09-11

Rights

Copyright (c) 2020 Mohammad Vahid Sebt, Elahe Komijani, Shiva S. Ghasemi

Relation

Format

application/pdf

Language

eng

Type

info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article

Identifier

Citation

Mohammad Sebt Vahid, Elahe Komijani and Shiva Ghasemi S., Implementing a Data Mining Solution Approach to Identify the Valuable Customers for Facilitating Electronic Banking, International Association of Online Engineering (IAOE), Vienna, Austria, 2020, accessed November 7, 2024, https://igi.indrastra.com/items/show/1793

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