أساليب كمية مقترحة لقياس مخاطر التعثر في البنوك الاسلامية: حالة الجزائر

Résumé: Abstract: This study aims to develop a scoring model that enables Islamic banks operating in Algeria to predict the default of borrowers, which can further aid the credit decision making process. To achieve this objective the researcher formed a database from a set of independent variables. This data has been subjected to the process of statistical analysis using SPSS in order to ensure the suitability of this data to the application of two statistical modeling techniques used in the default risk measurement such as discriminant analysis and artificial neural network. the Results of the study has shown that The accuracy rate of final prediction using ANN technique is found to be 100%, while the accuracy rates of the discriminant analysis technique is found to be 73.3 %. Keywords: default risks; discriminant analysis; artificial neural network; Islamic banks.

Publié dans la revue: مجلة الإبتكار والتسويق