Credit scoring is regarded as a core competence of commercial banks during the last few decades. A number of credit scoring models have been developed to evaluate credit risk of new loan applicants and existing loan clients. The main purpose of the present paper is to evaluate credit risk in Egyptian banks using credit scoring models. Three statistical techniques are used: discriminant analysis, probit analysis and logistic regression. The credit scoring task is performed on one bank’s personal loans data-set. The results so far revealed that all proposed models gave a better average correct classification rate than the one currently used. Also both type I and type II errors had been calculated in order to evaluate the misclassification costs.
|Number of pages||18|
|Journal||Banks and Bank Systems|
|Publication status||Published - 3 Apr 2007|