Designing an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0
Ali M. Razaque A. Yoo J. Kabievna U.R. Moldagulova A. Ryskhan S. Zhuldyz K. Kassymova A.
March 2024Multidisciplinary Digital Publishing Institute (MDPI)
Logistics
2024#8Issue 1
Background: 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.
AI in finance , blockchain integration , financial innovation , financial operations , intelligent credit card system , risk management
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Department of Computer Engineering, International Information Technology University, Almaty, 050000, Kazakhstan
Department of Cybersecurity, Information Processing and Storage, Satbayev University, Almaty, 050000, Kazakhstan
School of Computing, Gachon University South Korea, Seongnam-si, 13120, South Korea
Department of Software Engineering, Satbayev University, Almaty, 050000, Kazakhstan
Department of Computer Engineering
Department of Cybersecurity
School of Computing
Department of Software Engineering
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