为工业 4.0 中的商品制造商和进口商设计智能评分系统

Logistics Pub Date : 2024-03-20 DOI:10.3390/logistics8010033
Mohsin Ali, Abdul Razaque, Joon Yoo, Uskenbayeva Raissa Kabievna, A. Moldagulova, Satybaldiyeva Ryskhan, Kalpeyeva Zhuldyz, Aizhan Kassymova
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引用次数: 0

摘要

背景:现代信用卡系统至关重要,但尚未对其进行充分研究,以满足数量不断变化的制造商和进口商的独特财务需求。方法:智能信用卡系统集成了人工智能和区块链技术的特点。区块链技术的去中心化和不可更改的账本大大降低了欺诈风险,同时保持了实时交易记录。另一方面,人工智能驱动的信用评估算法的功能可实现更精确、有效和定制化的信用选择,专门针对制造商和进口商的独特财务状况进行定制。结果:研究了多个指标,包括预测信用风险、欺诈检测、信用评估准确性、违约率比较、贷款批准率比较以及影响信用卡系统的其他重要指标,以确定现代信用卡系统在使用区块链技术和人工智能时的有效性。结论在工业 4.0 中为货物制造商和进口商开发智能评分系统的研究,可以通过纳入用户采用情况而得到加强。不断变化的立法和日益增加的安全威胁要求持续监控。可扩展性方面的困难可通过侧重于集成、数据迁移和变更管理的详细规划来解决。这项研究有可能提高制造和进口行业的运营效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0
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.
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