A Credit Scoring Model for Farmer Lending Decisions in Rural China

Junxuan Mao, Qianyu Zhu, Cheryl J. Wachenheim and Erik D. Hanson

International Journal of Agricultural Management, 2020, vol. 08, issue 4

Abstract: A cooperative mutual fund is an important cooperative-based financing option for farmers in China. As its farmer-borrowers often do not have formal records, a lending decision generally relies heavily on subjective evaluation. This experienced-based judgment has been relatively accurate but is less useful as seasoned loan officers retire or as growth necessitates hiring novice lenders. A credit scoring model was developed to capture the knowledge of experienced loan officers and thereby assist those more novice. The model evaluates a farmer’s credit standing based on family background, willingness to repay, repayment capacity, and relationships. The analytic hierarchy process is used to determine factor weighting and the model is empirically tested. The model’s predictive accuracy is high, with most error attributed to core indicators in the model that have strong veto power. Therefore, we suggest supplementing the credit scoring model with a crucial indicator negation system.

Keywords: Community/Rural/Urban Development; Financial Economics (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://ageconsearch.umn.edu/record/329832/files/d ... ijam_2020-08-134.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:ijameu:329832

DOI: 10.22004/ag.econ.329832

Access Statistics for this article

More articles in International Journal of Agricultural Management from Institute of Agricultural Management Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().