IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v8y2024i1p33-d1360081.html

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

Author

Listed:
  • Mohsin Ali

    (Department of Computer Engineering, International Information Technology University, Almaty 050000, Kazakhstan)

  • Abdul Razaque

    (Department of Cybersecurity, Information Processing and Storage, Satbayev University, Almaty 050000, Kazakhstan)

  • Joon Yoo

    (School of Computing, Gachon University South Korea, Seongnam-si 13120, Republic of Korea)

  • Uskenbayeva Raissa Kabievna

    (Department of Software Engineering, Satbayev University, Almaty 050000, Kazakhstan)

  • Aiman Moldagulova

    (Department of Software Engineering, Satbayev University, Almaty 050000, Kazakhstan)

  • Satybaldiyeva Ryskhan

    (Department of Cybersecurity, Information Processing and Storage, Satbayev University, Almaty 050000, Kazakhstan)

  • Kalpeyeva Zhuldyz

    (Department of Software Engineering, Satbayev University, Almaty 050000, Kazakhstan)

  • Aizhan Kassymova

    (Department of Software Engineering, Satbayev University, Almaty 050000, Kazakhstan)

Abstract

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.

Suggested Citation

  • Mohsin Ali & Abdul Razaque & Joon Yoo & Uskenbayeva Raissa Kabievna & Aiman Moldagulova & Satybaldiyeva Ryskhan & Kalpeyeva Zhuldyz & Aizhan Kassymova, 2024. "Designing an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0," Logistics, MDPI, vol. 8(1), pages 1-30, March.
    • Handle: RePEc:gam:jlogis:v:8:y:2024:i:1:p:33-:d:1360081
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/8/1/33/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2305-6290/8/1/33/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Purnima Rao & Satish Kumar & Meena Chavan & Weng Marc Lim, 2023. "A systematic literature review on SME financing: Trends and future directions," Journal of Small Business Management, Taylor & Francis Journals, vol. 61(3), pages 1247-1277, May.
    2. Niklas Bussmann & Paolo Giudici & Dimitri Marinelli & Jochen Papenbrock, 2021. "Explainable Machine Learning in Credit Risk Management," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 203-216, January.
    3. Zhe Cao & Xianwei Shi, 2021. "A systematic literature review of entrepreneurial ecosystems in advanced and emerging economies," Small Business Economics, Springer, vol. 57(1), pages 75-110, June.
    4. Chen, Yan & Bellavitis, Cristiano, 2020. "Blockchain disruption and decentralized finance: The rise of decentralized business models," Journal of Business Venturing Insights, Elsevier, vol. 13(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hans Rawhouser & Silvio Vismara & Nir Kshetri, 2024. "Blockchain and vulnerable entrepreneurial ecosystems," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 36(1-2), pages 10-35, January.
    2. Wolfgang Drobetz & Lars Hornuf & Paul P. Momtaz & Niclas Schermann, 2025. "Token-Based Crowdfunding: Investor Choice and the Optimal Timing of Initial Coin Offerings," Entrepreneurship Theory and Practice, , vol. 49(1), pages 232-282, January.
    3. Dangxing Chen, 2023. "Can I Trust the Explanations? Investigating Explainable Machine Learning Methods for Monotonic Models," Papers 2309.13246, arXiv.org.
    4. Sujeeth Ungratwar & Dipasha Sharma & Satish Kumar, 2025. "Mapping the digital banking landscape: a multi-dimensional exploration of fintech, digital payments, and e-wallets, with insights into current scenarios and future research," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-22, December.
    5. Remy Jonkam Oben & Aliya Zhakanova Isiksal, 2026. "Decentralized finance portfolio optimization: assessing green and brown investments before, during, and after COVID-19," Economic Change and Restructuring, Springer, vol. 59(2), pages 1-51, April.
    6. Su, Dan & Zhang, Lijun & Peng, Hua & Saeidi, Parvaneh & Tirkolaee, Erfan Babaee, 2023. "Technical challenges of blockchain technology for sustainable manufacturing paradigm in Industry 4.0 era using a fuzzy decision support system," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    7. Saurabh A. Lall & Li-Wei Chen & Dyana P. Mason, 2023. "Digital platforms and entrepreneurial support: a field experiment in online mentoring," Small Business Economics, Springer, vol. 61(2), pages 631-654, August.
    8. Syed Tariq Anwar, 2025. "Entrepreneurial ecosystems, evolutionary growth and global expansion," Journal of International Entrepreneurship, Springer, vol. 23(2), pages 528-558, June.
    9. Mansoureh Beheshti Nejad & Seyed Mahmoud Zanjirchi & Seyed Mojtaba Hosseini Bamakan & Negar Jalilian, 2024. "Blockchain Adoption in Operations Management: A Systematic Literature Review of 14 Years of Research," Annals of Data Science, Springer, vol. 11(4), pages 1361-1389, August.
    10. Mahmoona Khalil & Kausar Fiaz Khawaja & Muddassar Sarfraz, 2022. "The adoption of blockchain technology in the financial sector during the era of fourth industrial revolution: a moderated mediated model," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2435-2452, August.
    11. Li, Sen & Chen, Yan, 2024. "Governing decentralized autonomous organizations as digital commons," Journal of Business Venturing Insights, Elsevier, vol. 21(C).
    12. Matina Magkou, 2024. "A creative hub for creative hubs or the emergence of a translocal entrepreneurial ecosystem for cultural entrepreneurs [Un centro creativo para centros creativos, o la emergencia de un ecosistema emprendedor translocal para emprendedores culturale," Post-Print hal-05026549, HAL.
    13. Yousaf, Imran & Jareño, Francisco & Tolentino, Marta, 2023. "Connectedness between Defi assets and equity markets during COVID-19: A sector analysis," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    14. Moyra Marval, 2025. "International linkages between entrepreneurial ecosystems: understanding the role of corporate accelerators," Small Business Economics, Springer, vol. 65(3), pages 1407-1426, October.
    15. Pastwa, Anna M. & Shrestha, Prabal & Thewissen, James & Torsin, Wouter, 2021. "Unpacking the black box of ICO white papers: a topic modeling approach," LIDAM Discussion Papers LFIN 2021018, Université catholique de Louvain, Louvain Finance (LFIN).
    16. Ahmet Faruk Aysan & Nawaz Farrukh, 2021. "China's Transition to a Digital Currency: Does It Threaten Dollarization?," Working Papers hal-03364939, HAL.
    17. Bastos, João A. & Matos, Sara M., 2022. "Explainable models of credit losses," European Journal of Operational Research, Elsevier, vol. 301(1), pages 386-394.
    18. Li, Dan & Sun, Yanyang, 2025. "The impact of inclusive lending support on the performance of small and micro enterprises: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 353-370.
    19. Tang, Pan & Tang, Tiantian & Lu, Chennuo, 2024. "Predicting systemic financial risk with interpretable machine learning," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    20. Bahrawar Said & Muhammad Wajid Raza & Adamu Jibir & Jawad Hussain, 2026. "Entrepreneurial finance in the context of COVID-19 and post-pandemic challenges: a bibliometric and content analysis," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 16(1), pages 1-23, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlogis:v:8:y:2024:i:1:p:33-:d:1360081. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.