IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v342y2024i1d10.1007_s10479-023-05662-2.html
   My bibliography  Save this article

Credit rating prediction with supply chain information: a machine learning perspective

Author

Listed:
  • Long Ren

    (University of International Business and Economics)

  • Shaojie Cong

    (University of International Business and Economics)

  • Xinlong Xue

    (University of International Business and Economics)

  • Daqing Gong

    (Beijing Jiaotong University)

Abstract

In this paper, we adopt an ensemble machine learning framework—a Light Gradient Boosting Machine (LightGBM) and develop an algorithmic credit rating prediction model by innovatively incorporating firms’ extra supply chain information both from suppliers and customers. By utilizing data from listed firms in North America from 2006 to 2020, our results find that the accuracy of the prediction improves by incorporating supply chain information in the previous year, compared to the inclusion of supply chain information in the current year. Besides, we identify the most important factors the stakeholders should pay attention to. Interestingly, we show that the models utilizing the current year’s information perform better after the strike of the COVID-19, indicating that the epidemics may have accelerated the spread of credit risk along the supply chain. Furthermore, supplier information is found to be more valuable than customer information in predicting the focal firm’s credit rating. A comparison of our framework with the existing methods vindicates the robustness of our main results.

Suggested Citation

  • Long Ren & Shaojie Cong & Xinlong Xue & Daqing Gong, 2024. "Credit rating prediction with supply chain information: a machine learning perspective," Annals of Operations Research, Springer, vol. 342(1), pages 657-686, November.
    • Handle: RePEc:spr:annopr:v:342:y:2024:i:1:d:10.1007_s10479-023-05662-2
    DOI: 10.1007/s10479-023-05662-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-023-05662-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-023-05662-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nelly Oelze & Stefan Ulstrup Hoejmose & Andre Habisch & Andrew Millington, 2016. "Sustainable Development in Supply Chain Management: The Role of Organizational Learning for Policy Implementation," Business Strategy and the Environment, Wiley Blackwell, vol. 25(4), pages 241-260, May.
    2. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
    3. Dallin M. Alldredge & Yinfei Chen & Steve Liu & Lan Luo, 2021. "The effect of credit rating downgrades along the supply chain," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 21(1), pages 1-31, December.
    4. Gang Li & Gang Yu & Shouyang Wang & Hong Yan, 2017. "Bullwhip and anti-bullwhip effects in a supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(18), pages 5423-5434, September.
    5. Pastore, Erica & Alfieri, Arianna & Zotteri, Giulio, 2019. "An empirical investigation on the antecedents of the bullwhip effect: Evidence from the spare parts industry," International Journal of Production Economics, Elsevier, vol. 209(C), pages 121-133.
    6. Zhaoqian Liu & Mengmeng Wang, 2022. "Improving Circular Supply Chain Performance through Green Innovations: The Moderating Role of Economic Policy Uncertainty," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    7. Parisa Golbayani & Dan Wang & Ionut Florescu, 2020. "Application of Deep Neural Networks to assess corporate Credit Rating," Papers 2003.02334, arXiv.org.
    8. Xie, Xuemei & Huo, Jiage & Zou, Hailiang, 2019. "Green process innovation, green product innovation, and corporate financial performance: A content analysis method," Journal of Business Research, Elsevier, vol. 101(C), pages 697-706.
    9. Chang, Jung-Hsien & Hung, Mao-Wei & Tsai, Feng-Tse, 2015. "Credit contagion and competitive effects of bond rating downgrades along the supply chain," Finance Research Letters, Elsevier, vol. 15(C), pages 232-238.
    10. Iftikhar, Anas & Purvis, Laura & Giannoccaro, Ilaria, 2021. "A meta-analytical review of antecedents and outcomes of firm resilience," Journal of Business Research, Elsevier, vol. 135(C), pages 408-425.
    11. Ali, Mohsin & Alam, Nafis & Rizvi, Syed Aun R., 2020. "Coronavirus (COVID-19) — An epidemic or pandemic for financial markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    12. Cucinelli, Doriana & Battista, Maria Luisa Di & Marchese, Malvina & Nieri, Laura, 2018. "Credit risk in European banks: The bright side of the internal ratings based approach," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 213-229.
    13. Ding, Wenzhi & Levine, Ross & Lin, Chen & Xie, Wensi, 2021. "Corporate immunity to the COVID-19 pandemic," Journal of Financial Economics, Elsevier, vol. 141(2), pages 802-830.
    14. Yang, Heejin & Ahn, Hee-Joon & Kim, Maria H. & Ryu, Doojin, 2017. "Information asymmetry and investor trading behavior around bond rating change announcements," Emerging Markets Review, Elsevier, vol. 32(C), pages 38-51.
    15. Jing Wu & Zhaocheng Zhang & Sean X. Zhou, 2022. "Credit Rating Prediction Through Supply Chains: A Machine Learning Approach," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1613-1629, April.
    16. Liu, Yuanyuan & Li, Jing & Liu, Guanchun & Lee, Chien-Chiang, 2021. "Economic policy uncertainty and firm’s cash holding in China: The key role of asset reversibility," Journal of Asian Economics, Elsevier, vol. 74(C).
    17. Ritesh Ojha & Abhijeet Ghadge & Manoj Kumar Tiwari & Umit S. Bititci, 2018. "Bayesian network modelling for supply chain risk propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5795-5819, September.
    18. Huimin Liu & Yupeng Shi & Xuze Yang & Wentao Zhang, 2023. "The Role of Business Environment and Digital Government in Mitigating Supply Chain Vulnerability—Evidence from the COVID-19 Shock," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    19. Chrysovalantis Gaganis & Panagiota Papadimitri & Menelaos Tasiou, 2021. "A multicriteria decision support tool for modelling bank credit ratings," Annals of Operations Research, Springer, vol. 306(1), pages 27-56, November.
    20. Hyunseob Kim & Howard Kung, 2017. "The Asset Redeployability Channel: How Uncertainty Affects Corporate Investment," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 245-280.
    21. Lulin Xu & Zhongwu Li, 2021. "A New Appraisal Model of Second-Hand Housing Prices in China’s First-Tier Cities Based on Machine Learning Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 617-637, February.
    22. Yu-Shan Chen & Shyh-Bao Lai & Chao-Tung Wen, 2006. "The Influence of Green Innovation Performance on Corporate Advantage in Taiwan," Journal of Business Ethics, Springer, vol. 67(4), pages 331-339, September.
    23. Tom Lahti & Joakim Wincent & Vinit Parida, 2018. "A Definition and Theoretical Review of the Circular Economy, Value Creation, and Sustainable Business Models: Where Are We Now and Where Should Research Move in the Future?," Sustainability, MDPI, vol. 10(8), pages 1-19, August.
    24. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
    25. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    26. Olaf Weber & Roland W. Scholz & Georg Michalik, 2010. "Incorporating sustainability criteria into credit risk management," Business Strategy and the Environment, Wiley Blackwell, vol. 19(1), pages 39-50, January.
    27. Kisgen, Darren J., 2019. "The impact of credit ratings on corporate behavior: Evidence from Moody's adjustments," Journal of Corporate Finance, Elsevier, vol. 58(C), pages 567-582.
    28. Tang, Leo & Li, Pei, 2021. "Are investors fixated on credit ratings? Reinterpreting the municipal bond recalibration," Finance Research Letters, Elsevier, vol. 38(C).
    29. Zhibin (Ben) Yang & Göker Ayd{i}n & Volodymyr Babich & Damian R. Beil, 2009. "Supply Disruptions, Asymmetric Information, and a Backup Production Option," Management Science, INFORMS, vol. 55(2), pages 192-209, February.
    30. Zongyu Mu & Yuangang Zheng & Hao Sun, 2021. "Cooperative Green Technology Innovation of an E-Commerce Sales Channel in a Two-Stage Supply Chain," Sustainability, MDPI, vol. 13(13), pages 1-28, July.
    31. Panos Kouvelis & Wenhui Zhao, 2018. "Who Should Finance the Supply Chain? Impact of Credit Ratings on Supply Chain Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 20(1), pages 19-35, February.
    32. Senay Agca & Volodymyr Babich & John R. Birge & Jing Wu, 2022. "Credit Shock Propagation Along Supply Chains: Evidence from the CDS Market," Management Science, INFORMS, vol. 68(9), pages 6506-6538, September.
    33. Liping Song & Yingluo Yan & Fengmin Yao, 2020. "Closed-Loop Supply Chain Models Considering Government Subsidy and Corporate Social Responsibility Investment," Sustainability, MDPI, vol. 12(5), pages 1-27, March.
    34. Ken Hung & Hui Wen Cheng & Shih-shen Chen & Ying-Chen Huang, 2013. "Factors that Affect Credit Rating: An Application of Ordered Probit Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 94-108, December.
    35. Joo, M. Hashemi & Parhizgari, A.M., 2021. "A behavioral explanation of credit ratings and leverage adjustments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(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. Helmut Wasserbacher & Martin Spindler, 2024. "Credit Ratings: Heterogeneous Effect on Capital Structure," Papers 2406.18936, arXiv.org.
    2. Zhaoqian Liu & Mengmeng Wang, 2022. "Improving Circular Supply Chain Performance through Green Innovations: The Moderating Role of Economic Policy Uncertainty," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    3. Şenay Ağca & John R. Birge & Zi'ang Wang & Jing Wu, 2023. "The impact of COVID‐19 on supply chain credit risk," Production and Operations Management, Production and Operations Management Society, vol. 32(12), pages 4088-4113, December.
    4. Xie, Xiaofeng & Shi, Xinyu & Gu, Jing & Xu, Xun, 2023. "Examining the Contagion Effect of Credit Risk in a Supply Chain under Trade Credit and Bank Loan Offering," Omega, Elsevier, vol. 115(C).
    5. Jing Wu & Zhaocheng Zhang & Sean X. Zhou, 2022. "Credit Rating Prediction Through Supply Chains: A Machine Learning Approach," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1613-1629, April.
    6. Dinh, K. & Kleimeier, S., 2006. "Credit scoring for Vietnam's retail banking market : implementation and implications for transactional versus relationship lending," Research Memorandum 012, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    7. Xueyang Wang & Xiumei Sun & Haotian Zhang & Chaokai Xue, 2022. "Digital Economy Development and Urban Green Innovation CA-Pability: Based on Panel Data of 274 Prefecture-Level Cities in China," Sustainability, MDPI, vol. 14(5), pages 1-21, March.
    8. Ballester, Laura & González-Urteaga, Ana & Shen, Long, 2024. "Green bond issuance and credit risk: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 94(C).
    9. Kalaivani Jayaraman & Sreenivasan Jayashree & Magiswary Dorasamy, 2023. "The Effects of Green Innovations in Organizations: Influence of Stakeholders," Sustainability, MDPI, vol. 15(2), pages 1-13, January.
    10. Duong, Huu Nhan & Khalifa, Mariem & Sheikhbahaei, Ali & Sualihu, Mohammed Aminu, 2024. "Corporate noncompliance: Do corporate violations affect bank loan contracting?," Journal of Banking & Finance, Elsevier, vol. 166(C).
    11. Liang, Shangkun & Niu, Yuhao & Yang, Dan & Liu, Xuejuan, 2023. "Dividend payouts under a societal crisis: Financial constraints or signaling?," International Review of Financial Analysis, Elsevier, vol. 88(C).
    12. Lkhagvadorj Munkhdalai & Tsendsuren Munkhdalai & Oyun-Erdene Namsrai & Jong Yun Lee & Keun Ho Ryu, 2019. "An Empirical Comparison of Machine-Learning Methods on Bank Client Credit Assessments," Sustainability, MDPI, vol. 11(3), pages 1-23, January.
    13. Qihang Zhang & Jie Jiang, 2025. "The Role of Green Innovation Appropriability and Firm Performance: Evidence from the Chinese Manufacturing Industry," Sustainability, MDPI, vol. 17(2), pages 1-25, January.
    14. Xinwei Li & Wenjuan Zeng & Mao Xu, 2022. "The Moderating Role of IT Capability on Green Innovation and Ambidexterity: Towards a Corporate Sustainable Development," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    15. Marco-Lajara, B. & Úbeda-García, M. & Zaragoza-Sáez, P. & Manresa-Marhuenda, E., 2023. "The impact of international experience on firm economic performance. The double mediating effect of green knowledge acquisition & eco-innovation," Journal of Business Research, Elsevier, vol. 157(C).
    16. Muhammad Ishtiaq Ishaq & Huma Sarwar & Junaid Aftab & Simona Franzoni & Ali Raza, 2024. "Accomplishing sustainable performance through leaders' competencies, green entrepreneurial orientation, and innovation in an emerging economy: Moderating role of institutional support," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 1515-1532, February.
    17. Dumitrescu, Elena & Hué, Sullivan & Hurlin, Christophe & Tokpavi, Sessi, 2022. "Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1178-1192.
    18. Ouyang, Puman & Zhong, Ligang, 2023. "Asset redeployability and dividend payout policy," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 91-105.
    19. Hang Wu & Yiying Qu, 2021. "How Do Firms Promote Green Innovation through International Mergers and Acquisitions: The Moderating Role of Green Image and Green Subsidy," IJERPH, MDPI, vol. 18(14), pages 1-16, July.
    20. Hussein A. Abdou & John Pointon, 2011. "Credit Scoring, Statistical Techniques And Evaluation Criteria: A Review Of The Literature," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(2-3), pages 59-88, April.

    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:spr:annopr:v:342:y:2024:i:1:d:10.1007_s10479-023-05662-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.