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The role of credit scoring models, weather index-based insurance, and asymmetric information in agricultural microfinance

Subject Area Agricultural Economics, Agricultural Policy, Agricultural Sociology
Term from 2014 to 2021
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 249506740
 
Many studies have shown that the microfinance approach based on cash-flow analyses is a time-consuming and thus cost-intensive assessment of the credit default risks of credit applicants. In contrast, credit scoring models, which entail automated identification of credit default risks, may reduce the costs of (agricultural) microfinance. In addition, the inclusion of weather variables into an agriculture-specific scoring model seems like a promising approach to devise credit scoring models for this clientele in particular. Indeed, weather index-based insurance, which has been intensively discussed in recent years, can diminish the comparably high weather-related credit default risk of agricultural microfinance. Lastly, another important issue in microfinance remains the prevention of asymmetric information. Yet, the effect of asymmetric information on credit default has never been investigated directly.Bearing in mind that there exist only few studies on credit scoring models, index-based insurance and asymmetric information in agricultural microfinance, the project pursues the following objectives:1. Evaluating the potential of credit scoring models (including weather risks) in agricultural microfinance2. Analyzing the influence of weather variables on credit granting and credit default risk in agricultural microfinance, as well as the related risk-reducing potential of weather index-based insurance3. Measuring the effect of asymmetric information on credit defaultThus, the research project provides important findings for the further development of microcredit for agricultural enterprises, and more particularly for the so far poor development of the financial system in the rural areas of developing countries.
DFG Programme Research Grants
 
 

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