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Default Feature Selection in Credit Risk Modeling: Evidence From Chinese Small Enterprises

Author

Listed:
  • Nana Chai
  • Baofeng Shi
  • Bin Meng
  • Yizhe Dong

Abstract

This paper aims to design a novel AFCM-SMOTENC-APRIORI model to mine the default feature attributes of small enterprises. It can overcome the problem that the data characteristics of “small defaulting small enterprises and large non-defaulting small enterprises†make it difficult to mine the defaulting feature attributes of existing small enterprises. We used 1,231 small enterprise credit data from a city commercial bank in China to make an empirical analysis. We found that 23 feature attributes are strongly associated with default and 87% of the association rules are the same between the extended data and the original data mining. It shows that the data mining results with SMOTE-NC are highly consistent with the results of the original data mining, and the model is robust and reliable. It can be used as a reference for the credit risk identification of small enterprises in commercial banks.

Suggested Citation

  • Nana Chai & Baofeng Shi & Bin Meng & Yizhe Dong, 2023. "Default Feature Selection in Credit Risk Modeling: Evidence From Chinese Small Enterprises," SAGE Open, , vol. 13(2), pages 21582440231, April.
    • Handle: RePEc:sae:sagope:v:13:y:2023:i:2:p:21582440231165224
    DOI: 10.1177/21582440231165224
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    References listed on IDEAS

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    1. Krink, Thiemo & Paterlini, Sandra & Resti, Andrea, 2008. "The optimal structure of PD buckets," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2275-2286, October.
    2. Dean Karlan & Jonathan Zinman, 2010. "Expanding Credit Access: Using Randomized Supply Decisions to Estimate the Impacts," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 433-464, January.
    3. Maksim Belitski & Christina Guenther & Alexander S. Kritikos & Roy Thurik, 2022. "Economic effects of the COVID-19 pandemic on entrepreneurship and small businesses," Small Business Economics, Springer, vol. 58(2), pages 593-609, February.
    4. Anoosheh Rostamkalaei & Mark Freel, 2016. "The cost of growth: small firms and the pricing of bank loans," Small Business Economics, Springer, vol. 46(2), pages 255-272, February.
    5. Shi, Baofeng & Chi, Guotai & Li, Weiping, 2020. "Exploring the mismatch between credit ratings and loss-given-default: A credit risk approach," Economic Modelling, Elsevier, vol. 85(C), pages 420-428.
    6. Lean Yu & Lihang Yu & Kaitao Yu, 2021. "A high-dimensionality-trait-driven learning paradigm for high dimensional credit classification," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-20, December.
    7. Bai, Chunguang & Shi, Baofeng & Liu, Feng & Sarkis, Joseph, 2019. "Banking credit worthiness: Evaluating the complex relationships," Omega, Elsevier, vol. 83(C), pages 26-38.
    8. Nana Chai & Bi Wu & Weiwei Yang & Baofeng Shi, 2019. "A Multicriteria Approach for Modeling Small Enterprise Credit Rating: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(11), pages 2523-2543, September.
    9. Ying Zhou & Mohammad Shamsu Uddin & Tabassum Habib & Guotai Chi & Kunpeng Yuan, 2021. "Feature selection in credit risk modeling: an international evidence," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 34(1), pages 3064-3091, January.
    10. Sun, Yue & Chai, Nana & Dong, Yizhe & Shi, Baofeng, 2022. "Assessing and predicting small industrial enterprises’ credit ratings: A fuzzy decision-making approach," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1158-1172.
    11. Thomas Hildebrand & Manju Puri & Jörg Rocholl, 2017. "Adverse Incentives in Crowdfunding," Management Science, INFORMS, vol. 63(3), pages 587-608, March.
    12. Cheng Zhang & Ni Hu, 2020. "A New Method for Computing Letter of Credit Risks," SAGE Open, , vol. 10(4), pages 21582440209, November.
    13. Mirgul Nizaeva & Ali Coskun, 2019. "Investigating the Relationship Between Financial Constraint and Growth of SMEs in South Eastern Europe," SAGE Open, , vol. 9(3), pages 21582440198, September.
    14. Mark Freel & Sara Carter & Stephen Tagg & Colin Mason, 2012. "The latent demand for bank debt: characterizing “discouraged borrowers”," Small Business Economics, Springer, vol. 38(4), pages 399-418, May.
    15. Raffaella Calabrese & Galina Andreeva & Jake Ansell, 2019. "“Birds of a Feather” Fail Together: Exploring the Nature of Dependency in SME Defaults," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 71-84, January.
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