Can agricultural credit scoring for microfinance institutions be implemented and improved by weather data?
ISSN: 0002-1466
Article publication date: 1 December 2017
Issue publication date: 12 January 2018
Abstract
Purpose
In recent years, the application of credit scoring in urban microfinance institutions (MFIs) became popular, while rural MFIs, which mainly lend to agricultural clients, are hesitating to adopt credit scoring. The purpose of this paper is to explore whether microfinance credit scoring models are suitable for agricultural clients, and if such models can be improved for agricultural clients by accounting for precipitation.
Design/methodology/approach
This study merges two data sets: 24,219 loan and client observations provided by the AccèsBanque Madagascar and daily precipitation data made available by CelsiusPro. An in- and out-of-sample splitting separates model building from model testing. Logistic regression is employed for the scoring models.
Findings
The credit scoring models perform equally well for agricultural and non-agricultural clients. Hence, credit scoring can be applied to the agricultural sector in microfinance. However, the prediction accuracy does not increase with the inclusion of precipitation in the agricultural model. Therefore, simple correlation analysis between weather events and loan repayment is insufficient for forecasting future repayment behavior.
Research limitations/implications
The results should be verified in different countries and climate contexts to enhance the robustness.
Social implications
By applying scoring models to agricultural clients as well, all clients can benefit from an improved risk assessment (e.g. faster decision making).
Originality/value
To the best of the authors’ knowledge, this is the first study investigating the potential of microfinance credit scoring for agricultural clients in general and for Madagascar in particular. Furthermore, this is the first study that incorporates a weather variable into a scoring model.
Keywords
Acknowledgements
The authors would like to thank Dr Calum Turvey and two anonymous referees for helpful comments and suggestions as well as Dr Ron Weber from the KfW for providing the data and his support. The authors further gratefully acknowledge financial support from Deutsche Forschungsgemeinschaft (DFG).
Citation
Römer, U. and Musshoff, O. (2018), "Can agricultural credit scoring for microfinance institutions be implemented and improved by weather data?", Agricultural Finance Review, Vol. 78 No. 1, pp. 83-97. https://doi.org/10.1108/AFR-11-2016-0082
Publisher
:Emerald Publishing Limited
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