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Credit rating and microfinance lending decisions based on loss given default (LGD)

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  • Shi, Baofeng
  • Zhao, Xue
  • Wu, Bi
  • Dong, Yizhe

Abstract

This paper proposes a credit rating model that considers the impact of key macroeconomic variables on commercial banks' credit decisions and loss given default (LGD). The findings provide additional insight into the phenomena that under some circumstances a higher credit rating may lead to a higher LGD. The empirical analysis is based on actual bank data from 2,044 farmers in China. The theoretical analysis and empirical verification provides key insights into regulatory and commercial bank credit policy in a developing country setting, while helping to alleviate financing problems of small and micro credit entities.

Suggested Citation

  • Shi, Baofeng & Zhao, Xue & Wu, Bi & Dong, Yizhe, 2019. "Credit rating and microfinance lending decisions based on loss given default (LGD)," Finance Research Letters, Elsevier, vol. 30(C), pages 124-129.
  • Handle: RePEc:eee:finlet:v:30:y:2019:i:c:p:124-129
    DOI: 10.1016/j.frl.2019.03.033
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    References listed on IDEAS

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    1. Castillo, José A. & Mora-Valencia, Andrés & Perote, Javier, 2018. "Moral hazard and default risk of SMEs with collateralized loans," Finance Research Letters, Elsevier, vol. 26(C), pages 95-99.
    2. Patrick Bolton & Xavier Freixas & Joel Shapiro, 2012. "The Credit Ratings Game," Journal of Finance, American Finance Association, vol. 67(1), pages 85-112, February.
    3. Qi, Min & Zhao, Xinlei, 2011. "Comparison of modeling methods for Loss Given Default," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2842-2855, November.
    4. Yao, Xiao & Crook, Jonathan & Andreeva, Galina, 2015. "Support vector regression for loss given default modelling," European Journal of Operational Research, Elsevier, vol. 240(2), pages 528-538.
    5. Fahmida E. Moula & Chi Guotai & Mohammad Zoynul Abedin, 2017. "Credit default prediction modeling: an application of support vector machine," Risk Management, Palgrave Macmillan, vol. 19(2), pages 158-187, May.
    6. Robert A. Jarrow & Stuart M. Turnbull, 2008. "Pricing Derivatives on Financial Securities Subject to Credit Risk," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 17, pages 377-409, World Scientific Publishing Co. Pte. Ltd..
    7. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    8. Loterman, Gert & Brown, Iain & Martens, David & Mues, Christophe & Baesens, Bart, 2012. "Benchmarking regression algorithms for loss given default modeling," International Journal of Forecasting, Elsevier, vol. 28(1), pages 161-170.
    9. Araujo, Aloisio & da Silva, Pietro & Faro, José Heleno, 2016. "Ambiguity aversion in the long run: “To disagree, we must also agree”," Journal of Economic Theory, Elsevier, vol. 165(C), pages 242-256.
    10. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    11. Bai, Chunguang & Shi, Baofeng & Liu, Feng & Sarkis, Joseph, 2019. "Banking credit worthiness: Evaluating the complex relationships," Omega, Elsevier, vol. 83(C), pages 26-38.
    12. 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.
    13. Boudreault, Mathieu & Gauthier, Geneviève & Thomassin, Tommy, 2014. "Contagion effect on bond portfolio risk measures in a hybrid credit risk model," Finance Research Letters, Elsevier, vol. 11(2), pages 131-139.
    14. Baofeng Shi & Bin Meng & Hufeng Yang & Jing Wang & Wenli Shi, 2018. "A Novel Approach for Reducing Attributes and Its Application to Small Enterprise Financing Ability Evaluation," Complexity, Hindawi, vol. 2018, pages 1-17, January.
    15. Leow, Mindy & Mues, Christophe, 2012. "Predicting loss given default (LGD) for residential mortgage loans: A two-stage model and empirical evidence for UK bank data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 183-195.
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    Citations

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    Cited by:

    1. Chai, Nana & Shi, Baofeng & Hua, Yiting, 2023. "Loss given default or default status: Which is better to determine farmers’ credit ratings?," Finance Research Letters, Elsevier, vol. 53(C).
    2. 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.
    3. Christian Kurniawan & Xiyu Deng & Adhiraj Chakraborty & Assane Gueye & Niangjun Chen & Yorie Nakahira, 2022. "A Learning and Control Perspective for Microfinance," Papers 2207.12631, arXiv.org, revised Dec 2022.
    4. Pranith Kumar Roy & Krishnendu Shaw, 2021. "A multicriteria credit scoring model for SMEs using hybrid BWM and TOPSIS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    5. Jiangming Ma & Di Gao, 2023. "The Impact of Sustainable Supply-Chain Partnership on Bank Loans: Evidence from Chinese-Listed Firms," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    6. Maria Patricia Durango‐Gutiérrez & Juan Lara‐Rubio & Andrés Navarro‐Galera, 2023. "Analysis of default risk in microfinance institutions under the Basel III framework," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1261-1278, April.

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    More about this item

    Keywords

    China; Credit rating; Lending decision; Credit risk; Loss given default (LGD);
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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