This paper aims at predicting businesses’ past due in service accounts as well as determining the variables that impact the likelihood of repayment. Two binary classification approaches, logistic regression and the decision tree, were conducted and compared. Both approaches have very good performances with respect to the accuracy. However, the decision tree only uses 10 predictors and reaches a...

Theories rationalizing joint liability lending are rich in implications for repayment rates. We exploit this fact to test four diverse models. We show that the models’ repayment implications do not always coincide. For example, higher correlation of output and borrowers’ ability to act cooperatively can raise or lower repayment, depending on the model. Data from Thai borrowing groups suggest th...

This paper introduces a dynamic model of the stochastic repayment behavior exhibited by delinquent credit-card accounts. Based on this model, we construct a dynamic collectability score (DCS) which estimates the account-specific probability of collecting a given portion of the outstanding debt over any given time horizon. The model integrates a variety of information sources, including historic...

How do borrowers respond to improvements a lender’s ability to punish defaulters? We implemented a randomized field experiment in Malawi examining the impact of fingerprinting of borrowers, which improves the lender’s ability to withhold future loans from individuals who have previously defaulted. Study participants were smallholder farmers applying for agricultural input loans, and were random...

It is well known that some XML elements correspond to objects (in the sense of object-orientation) and others do not. The question we consider in this paper is what benefits we can derive from paying attention to such object semantics, particularly for the problem of keyword queries. Keyword queries against XML data have been studied extensively in recent years, with several lowest-common-ances...