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Designing an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0

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dc.contributor.authorAli, Mohsin-
dc.contributor.authorRazaque, Abdul-
dc.contributor.authorYoo, Joon-
dc.contributor.authorKabievna, Uskenbayeva Raissa-
dc.contributor.authorMoldagulova, Aiman-
dc.contributor.authorRyskhan, Satybaldiyeva-
dc.contributor.authorZhuldyz, Kalpeyeva-
dc.contributor.authorKassymova, Aizhan-
dc.date.accessioned2024-04-25T11:30:19Z-
dc.date.available2024-04-25T11:30:19Z-
dc.date.issued2024-03-
dc.identifier.issn2305-6290-
dc.identifier.issn2305-6290-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/91041-
dc.description.abstractBackground: The modern credit card system is critical, but it has not been fully examined to meet the unique financial needs of a constantly changing number of manufacturers and importers. Methods: An intelligent credit card system integrates the features of artificial intelligence and blockchain technology. The decentralized and unchangeable ledger of the Blockchain technology significantly reduces the risk of fraud while maintaining real-time transaction recording. On the other hand, the capabilities of AI-driven credit assessment algorithms enable more precise, effective, and customized credit choices that are specifically tailored to meet the unique financial profiles of manufacturers and importers. Results: Several metrics, including predictive credit risk, fraud detection, credit assessment accuracy, default rate comparison, loan approval rate comparison, and other important metrics affecting the credit card system, have been investigated to determine the effectiveness of modern credit card systems when using Blockchain technology and AI. Conclusion: The study of developing an intelligent scoring system for crediting manufacturers and importers of goods in Industry 4.0 can be enhanced by incorporating user adoption. The changing legislation and increasing security threats necessitate ongoing monitoring. Scalability difficulties can be handled by detailed planning that focuses on integration, data migration, and change management. The research may potentially increase operational efficiency in the manufacturing and importing industries.-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleDesigning an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0-
dc.typeArticle-
dc.identifier.wosid001192907700001-
dc.identifier.doi10.3390/logistics8010033-
dc.identifier.bibliographicCitationLOGISTICS-BASEL, v.8, no.1-
dc.description.isOpenAccessY-
dc.identifier.scopusid2-s2.0-85188889792-
dc.citation.titleLOGISTICS-BASEL-
dc.citation.volume8-
dc.citation.number1-
dc.type.docTypeArticle-
dc.publisher.location스위스-
dc.subject.keywordAuthorintelligent credit card system-
dc.subject.keywordAuthorblockchain integration-
dc.subject.keywordAuthorAI in finance-
dc.subject.keywordAuthorfinancial innovation-
dc.subject.keywordAuthorrisk management-
dc.subject.keywordAuthorfinancial operations-
dc.subject.keywordPlusARTIFICIAL-INTELLIGENCE-
dc.subject.keywordPlusFRAUD-
dc.relation.journalResearchAreaBusiness & Economics-
dc.relation.journalResearchAreaOperations Research & Management Science-
dc.relation.journalWebOfScienceCategoryManagement-
dc.relation.journalWebOfScienceCategoryOperations Research & Management Science-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClassesci-
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