Modelling bank customer behaviour using feature engineering and classification techniques
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F23%3A39920844" target="_blank" >RIV/00216275:25410/23:39920844 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0275531923000399" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0275531923000399</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ribaf.2023.101913" target="_blank" >10.1016/j.ribaf.2023.101913</a>
Alternative languages
Result language
angličtina
Original language name
Modelling bank customer behaviour using feature engineering and classification techniques
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50206 - Finance
Result continuities
Project
<a href="/en/project/GA19-15498S" target="_blank" >GA19-15498S: Modelling emotions in verbal and nonverbal managerial communication to predict corporate financial risk</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Research in International Business and Finance
ISSN
0275-5319
e-ISSN
1878-3384
Volume of the periodical
65
Issue of the periodical within the volume
April
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
16
Pages from-to
101913
UT code for WoS article
000951433200001
EID of the result in the Scopus database
2-s2.0-85149284943