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dc.contributor.authorAbdou, H.A.*
dc.contributor.authorMitra, S.*
dc.contributor.authorFry, John*
dc.contributor.authorElamer, Ahmed A.*
dc.date.accessioned2019-03-22T11:38:04Z
dc.date.available2019-03-22T11:38:04Z
dc.date.issued2019-08-15
dc.identifier.citationAbdou HA, Mitra S, Fry J et al (2019) Would two-stage scoring models alleviate bank exposure to bad debt? Expert Systems with Applications. 128: 1-13.en_US
dc.identifier.urihttp://hdl.handle.net/10454/16908
dc.descriptionYesen_US
dc.description.abstractThe main aim of this paper is to investigate how far applying suitably conceived and designed credit scoring models can properly account for the incidence of default and help improve the decision-making process. Four statistical modelling techniques, namely, discriminant analysis, logistic regression, multi-layer feed-forward neural network and probabilistic neural network are used in building credit scoring models for the Indian banking sector. Notably actual misclassification costs are analysed in preference to estimated misclassification costs. Our first-stage scoring models show that sophisticated credit scoring models, in particular probabilistic neural networks, can help to strengthen the decision-making processes by reducing default rates by over 14%. The second-stage of our analysis focuses upon the default cases and substantiates the significance of the timing of default. Moreover, our results reveal that State of residence, equated monthly instalment, net annual income, marital status and loan amount, are the most important predictive variables. The practical implications of this study are that our scoring models could help banks avoid high default rates, rising bad debts, shrinking cash flows and punitive cost-cutting measures.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.1016/j.eswa.2019.03.028en_US
dc.rights© 2019 The Authors. Published by Elsevier Ltd. Under a Creative Commons license - https://creativecommons.org/licenses/by/4.0/.en_US
dc.subjectCrediten_US
dc.subjectIndian banksen_US
dc.subjectNeural networksen_US
dc.subjectActual misclassification costsen_US
dc.subjectTiming of defaulten_US
dc.titleWould two-stage scoring models alleviate bank exposure to bad debt?en_US
dc.status.refereedYesen_US
dc.date.Accepted2019-03-15
dc.date.application2019-03-15
dc.typeArticleen_US
dc.type.versionPublished versionen_US
refterms.dateFOA2019-03-22T11:38:04Z


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