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dc.contributor.authorShah, Faiza
dc.contributor.authorLiu, Yumin
dc.contributor.authorAnwar, Aamir
dc.contributor.authorShah, Yasir
dc.contributor.authorAlroobaea, Roobaea
dc.contributor.authorHussain, Saddam
dc.contributor.authorSajid Ullah, Syed
dc.identifier.citationShah, F., Liu, Y., Anwar, A., Shah, Y., Alroobaea, R., Hussain, S. & Sajid Ullah, S. (2022). Machine Learning: The Backbone of Intelligent Trade Credit-Based Systems. Security and Communication Networks, Artikkel 7149902.en_US
dc.description.abstractTechnology has turned into a significant differentiator in the money and traditional recordkeeping systems for the financial industry. To depict two customers as potential investors, it is mandatory to give the complex innovation that they anticipate and urge to purchase. In any case, it is difficult to keep on top of and be a specialist in each of the new advancements that are accessible. By reappropriating IT administrations, monetary administrations firms can acquire prompt admittance to the most recent ability and direction. Financial systems, along with machine learning (ML) algorithms, are vital for critical concerns like secure financial transactions and automated trading. These are the key to the provision of financial decisions for investors and stakeholders for the firms which are working with the trade credit (TC) approach, in Small and Medium Industries (SMEs). Huge and very sensitive data is processed in a limited time. The trade credit is a reason for more financial gains. The impact of TC with predictive machine learning algorithms is the reason why intelligent and safe revenue generation is the main target of the proposed study. That is, the combination of financial data and technology (FinTech) domains is a potential reason for sales growth and ultimately more profit.en_US
dc.publisherWiley and Hindawien_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleMachine Learning: The Backbone of Intelligent Trade Credit-Based Systemsen_US
dc.title.alternativeMachine Learning: The Backbone of Intelligent Trade Credit-Based Systemsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.rights.holder© 2022 The Author(s)en_US
dc.subject.nsiVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550en_US
dc.source.journalSecurity and Communication Networksen_US
dc.relation.projectTaif University Researchers Supporting Project no. TURSP-2020/36en_US

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal