Can scoring models help microfinance lenders in poor countries as much as they have helped credit-card lenders in rich … microfinance depend on many factors difficult to include in statistical models, I find that inexpensive data does indeed have some … predictive power. In microfinance, computer models will not replace loan officers, but they can flag the highest risks and act as …

This paper presents a scoring model that predicts the risk of drop-out for borrowers at a microfinance lender in … suggest that scoring may help microfinance lenders to detect segments of their clientele (and even specific current clients …

The global financial crisis affected microfinance institutions (MFIs) as lending growth was constrained by scarcer …

This paper is the first to analyze the credit risk of a microfinance institution based on the loan portfolio of a … leading Maghrebian microfinance institution, both in terms of number of clients served and of portfolio size. This allows us … male microfinance clients separately. Results show that loss rates are higher for a male client population than for a …

Microfinance in Mexico has developed at an accelerated pace and the efforts in credit risk management in this sector …

investigate determinants of credit risk for agricultural loans disbursed by a Microfinance Institution (MFI) in Azerbaijan. In …

should aim to provide access for the poor on saving, credit and insurance. Microfinance schemes have been applauded as a … successful best practice in providing access to saving and credit. However, microfinance institutions still have some room for …