Using Big Data to compare classification models for household credit rating in Kuwait

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dc.contributor.authorAlbarrak, Najla
dc.contributor.authorAlsanousi, Hessa
dc.contributor.authorMoulitsas, Irene
dc.contributor.authorFilippone, Salvatore
dc.date.accessioned2021-09-10T13:19:14Z
dc.date.available2021-09-10T13:19:14Z
dc.date.issued2021-03-13
dc.description.abstractCredit rating risks have become the main indicator of bank performance. They are the reflection of the current status of the bank and an important milestone for future planning. An effective credit assessment can better anticipate expected losses and will minimize unexpected losses from accumulating. In an oil country such as Kuwait, advancements in technology as well as the big data available within banks about customers can lead to a built-in credit assessment model. This built-in model can work to help in-household credit scoring at the decision of a financial institution’s management. Compared to the current ‘black box’ rating models, we did a comparison between different classification models for two types of banking: conventional and Islamic. The classification models are as follows: Logistic Regression, Fine Decision Tree, Linear Support Vector Machines, Kernel Naïve Bayes, and RUSBoosted. Sufficiently, the last could be used to classify banks household customers and determine their default cases. Keywords - Classification Models, Conventional Banking, Credit Rating, Household Customers, Islamic Bankingen_UK
dc.identifier.citationAlbarrak N, Alsanousi H, Moulitsas I, Filippone S. (2020) Using Big Data to compare classification models for household credit rating in Kuwait. International Journal of Soft Computing and Artificial Intelligence, Volume 8, Issue 2, November 2020, pp. 1-7en_UK
dc.identifier.issn2321-404X
dc.identifier.urihttp://iraj.doionline.org/dx/IJSCAI-IRAJ-DOIONLNE-17674
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/17069
dc.language.isoenen_UK
dc.publisherInderscienceen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectClassification Modelsen_UK
dc.subjectConventional Bankingen_UK
dc.subjectCredit Ratingen_UK
dc.subjectHousehold Customersen_UK
dc.subjectIslamic Bankingen_UK
dc.titleUsing Big Data to compare classification models for household credit rating in Kuwaiten_UK
dc.typeArticleen_UK

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