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A firefly algorithm modified support vector machine for the credit risk assessment of supply chain finance

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  • Zhang, Hao
  • Shi, Yuxin
  • Yang, Xueran
  • Zhou, Ruiling

Abstract

Nowadays, Supply Chain Finance (SCF) has been developing rapidly since the emergence of credit risk. Therefore, this paper used SVM optimized by the firefly algorithm, which is called firefly algorithm support vector machine (FA-SVM), and applied it to SCF evaluation with a different indicator selection.

Suggested Citation

  • Zhang, Hao & Shi, Yuxin & Yang, Xueran & Zhou, Ruiling, 2021. "A firefly algorithm modified support vector machine for the credit risk assessment of supply chain finance," Research in International Business and Finance, Elsevier, vol. 58(C).
    • Handle: RePEc:eee:riibaf:v:58:y:2021:i:c:s0275531921001033
    DOI: 10.1016/j.ribaf.2021.101482
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    1. Hassan, M. Kabir & Khan, Ashraf & Paltrinieri, Andrea, 2019. "Liquidity risk, credit risk and stability in Islamic and conventional banks," Research in International Business and Finance, Elsevier, vol. 48(C), pages 17-31.
    2. Maldonado, Sebastián & Pérez, Juan & Bravo, Cristián, 2017. "Cost-based feature selection for Support Vector Machines: An application in credit scoring," European Journal of Operational Research, Elsevier, vol. 261(2), pages 656-665.
    3. Bart Baesens & Rudy Setiono & Christophe Mues & Jan Vanthienen, 2003. "Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation," Management Science, INFORMS, vol. 49(3), pages 312-329, March.
    4. Ligang Zhou & Kin Keung Lai & Jerome Yen, 2009. "Credit Scoring Models With Auc Maximization Based On Weighted Svm," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 8(04), pages 677-696.
    5. Wei Gu & Meheli Basu & Zhang Chao & Lirong Wei, 2017. "A Unified Framework for Credit Evaluation for Internet Finance Companies: Multi-Criteria Analysis Through AHP and DEA," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 597-624, May.
    6. Deo, Ravinesh C. & Wen, Xiaohu & Qi, Feng, 2016. "A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset," Applied Energy, Elsevier, vol. 168(C), pages 568-593.
    7. Efsun Kürüm & Kasirga Yildirak & Gerhard-Wilhelm Weber, 2012. "A classification problem of credit risk rating investigated and solved by optimisation of the ROC curve," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(3), pages 529-557, September.
    8. Wuttke, David A. & Blome, Constantin & Henke, Michael, 2013. "Focusing the financial flow of supply chains: An empirical investigation of financial supply chain management," International Journal of Production Economics, Elsevier, vol. 145(2), pages 773-789.
    9. WUTTKE, David A & BLOME, Constantin & HENKE, Michael, 2013. "Focusing the financial flow of supply chains: an empirical investigation of financial supply chain management," LIDAM Reprints CORE 2601, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Lessmann, Stefan & Baesens, Bart & Seow, Hsin-Vonn & Thomas, Lyn C., 2015. "Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research," European Journal of Operational Research, Elsevier, vol. 247(1), pages 124-136.
    11. Cornett, Marcia Millon & McNutt, Jamie John & Strahan, Philip E. & Tehranian, Hassan, 2011. "Liquidity risk management and credit supply in the financial crisis," Journal of Financial Economics, Elsevier, vol. 101(2), pages 297-312, August.
    12. Al-Shammari, Eiman Tamah & Keivani, Afram & Shamshirband, Shahaboddin & Mostafaeipour, Ali & Yee, Por Lip & Petković, Dalibor & Ch, Sudheer, 2016. "Prediction of heat load in district heating systems by Support Vector Machine with Firefly searching algorithm," Energy, Elsevier, vol. 95(C), pages 266-273.
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    3. Jiang, Wenjuan & Wang, Xin, 2024. "Enterprise digital transformation empowers supply Chain stability," Finance Research Letters, Elsevier, vol. 66(C).
    4. Jia, Lei & Li, Jing, 2024. "How does digital collaboration impact supply chain resilience," Finance Research Letters, Elsevier, vol. 66(C).
    5. Zhao, Chunyan & Gan, Zhongxin & Xu, Zhibo, 2024. "Supply chain ESG and non-financial corporate shadow banking: Evidence from China," Finance Research Letters, Elsevier, vol. 66(C).
    6. Yang, Yiqu & Wang, Lingkang & Yang, Dongping, 2024. "The conformity effect of ESG performance in supply chain networks," Finance Research Letters, Elsevier, vol. 65(C).
    7. Hossein Havaeji & Thien-My Dao & Tony Wong, 2023. "Supervised Learning by Evolutionary Computation Tuning: An Application to Blockchain-Based Pharmaceutical Supply Chain Cost Model," Mathematics, MDPI, vol. 11(9), pages 1-19, April.
    8. Xiaoming Zhang & Lean Yu & Hang Yin, 2025. "Domain adaptation-based multistage ensemble learning paradigm for credit risk evaluation," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-28, December.
    9. Meiyan Li & Yingjun Fu, 2022. "Prediction of Supply Chain Financial Credit Risk Based on PCA-GA-SVM Model," Sustainability, MDPI, vol. 14(24), pages 1-21, December.
    10. Li, Zhe & Liang, Shuguang & Pan, Xianyou & Pang, Meng, 2024. "Credit risk prediction based on loan profit: Evidence from Chinese SMEs," Research in International Business and Finance, Elsevier, vol. 67(PA).
    11. Moffo, Ahmadou Mustapha Fonton, 2024. "A machine learning approach in stress testing US bank holding companies," International Review of Financial Analysis, Elsevier, vol. 95(PC).
    12. Lele Zhou & Maowei Chen & Hyangsook Lee, 2022. "Supply Chain Finance: A Research Review and Prospects Based on a Systematic Literature Analysis from a Financial Ecology Perspective," Sustainability, MDPI, vol. 14(21), pages 1-27, November.
    13. Xiufang Li & Zhiwang Zhang & Lingyun Li & Hui Pan, 2024. "Combining Feature Selection and Classification Using LASSO-Based MCO Classifier for Credit Risk Evaluation," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2641-2662, November.

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