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A New Efficient Credit Scoring Model For Personal Loan Using Data Mining Technique For Sustainability Management

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dc.contributor.authorRabihah Md. Sumen_US
dc.contributor.authorWaidah Ismailen_US
dc.contributor.authorZul Hilmi Abdullahen_US
dc.contributor.authorNurul Fathihin Mohd Noor Shahen_US
dc.date.accessioned2024-05-29T02:27:28Z
dc.date.available2024-05-29T02:27:28Z
dc.date.issued2022
dc.date.submitted2023-3-29
dc.descriptionVolume 17 Number 5, May 2022:Page (60-76)en_US
dc.description.abstractCredit scoring models are used in decision-making processes to produce an accurate prediction of an applicant’s creditworthiness. A five-step credit scoring model for personal loans was developed using the seven-step credit scoring model by Siddiqi. It uses real data provided by a bank. This study aims to remove the unnecessary complexity of the credit scoring process. The five-step credit scoring model consists of data massaging, factor analysis, data mining modelling, credit scoring and post-modelling. To ensure accuracy, factors that were significant in determining the creditworthiness of applicants were used in the model, which are the type of installment, age, monthly expenses, job sector, payment method and income-to-finance ratio. Furthermore, by presenting a systematic and structured step for developing a credit scoring model, this study contributed to the research on credit scoring. Based on the findings of this study, banks may use this model to create their own credit scoring model to assess the creditworthiness of personal loan applicants. By managing risks with this model, banks can create a long-term solution for credit system management and aid in the decision-making processen_US
dc.identifier.doi10.46754/jssm.2022.05.005
dc.identifier.epage76
dc.identifier.issn1823-8556
dc.identifier.issue5
dc.identifier.spage60
dc.identifier.urihttps://jssm.umt.edu.my/wp-content/uploads/sites/51/2022/06/Article-5-JSSM-Volume-17-Number-5-May-2022.pdf
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/10695
dc.identifier.volume17
dc.language.isoenen_US
dc.publisherUMTen_US
dc.relation.ispartofJournal of Sustainability Science and Managementen_US
dc.subjectCredit scoring, data mining, personal loan.en_US
dc.titleA New Efficient Credit Scoring Model For Personal Loan Using Data Mining Technique For Sustainability Managementen_US
dc.typeArticleen_US
dspace.entity.typePublication

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