HingiCredit (Makerere University)

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Big Ideas LogoFinancial institutions face a big challenge when offering agricultural financial credit. They have inefficient mechanisms to evaluate a farmer’s credit worthiness in relation to the sector-specific risks such as production, price and market risks. Most financial institutions do not have reliable credit risk analysis models to guide them in best evaluating farmers. Without a proper method or approach to credit risk analysis, farmers face the risk of being denied the credit they require because of the potentially inaccurate credit risk scores generated for them. Financial institutions also stand the risk of making losses when they give loans basing on the potentially inaccurate credit risk scores. HingiCredit will provide an automated credit risk analysis system that can be used to assess the credit-worthiness of farmers requesting loans from financial institutions. HingiCredit will reflect the risk factors that influence production and market and as a result will match farmers to financial institutions that are willing to provide the loans within the calculated risk.

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Blum Center for Developing Economies
The University of California, Berkeley
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