Optimized algorithm for Credit Scoring

Using DEA for Classification in Credit Scoring

Credit scoring is a kind of binary classification problem that contains important information for manager to make a decision in particularly in banking authorities. Obtained scores provide a practical credit decision for a loan officer to classify clients to reject or accept for payment loan. For this sake, in this paper a data envelopment analysis- discriminant analysis (DEA-DA) approach is us...

Credit Scoring for Microenterprise Lenders

using genetic algorithm in optimizing decision trees for credit scoring of banks customers

decision trees as one of the data mining techniques, is used in credit scoring of bank customers. the main problem is the construction of decision trees in that they can classify customers optimally. this paper proposes an appropriate model based on genetic algorithm for credit scoring of banks customers in order to offer credit facilities to each class. genetic algorithm can help in credit sco...

using dea for classification in credit scoring

credit scoring is a kind of binary classification problem that contains important information for manager to make a decision in particularly in banking authorities. obtained scores provide a practical credit decision for a loan officer to classify clients to reject or accept for payment loan. for this sake, in this paper a data envelopment analysis- discriminant analysis (dea-da) approach is us...

153-2008: SAS/OR®: Rigorous Constrained Optimized Binning for Credit Scoring

Credit scoring can be defined as a statistical modeling technique used to assign risk to credit applicants or to existing credit accounts. We present a new process that enhances the formulation and solution approach in the SAS® system during the so-called “binning” phase by exploiting SAS/OR optimization capabilities to approach the problem from a mathematically rigorous perspective. Usually, a...