Modelling bank customer behaviour using feature engineering and classification techniques

Mohammad Zoynul Abedin, Petr Hajek, Taimur Sharif, Md. Shahriare Satu and Md. Imran Khan

Research in International Business and Finance, 2023, vol. 65, issue C

Abstract: This study investigates customer behaviour and activity in the banking sector and uses various feature transformation techniques to convert the behavioural data into different data structures. Feature selection is then performed to generate feature subsets from the transformed datasets. Several classification methods used in the literature are applied to the original and transformed feature subsets. The proposed combined knowledge mining model enable us to conduct a benchmark study on the prediction of bank customer behaviour. A real bank customer dataset, drawn from 24,000 active and inactive customers, is used for an experimental analysis, which sheds new light on the role of feature engineering in bank customer classification. This paper’s detailed systematic analysis of the modelling of bank customer behaviour can help banking institutions take the right steps to increase their customers’ activity.

Keywords: Customer behaviour; Data mining; Feature transformation; Feature selection; Classification techniques (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0275531923000399
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:65:y:2023:i:c:s0275531923000399

DOI: 10.1016/j.ribaf.2023.101913

Access Statistics for this article

Research in International Business and Finance is currently edited by T. Lagoarde Segot

More articles in Research in International Business and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().