Risks analyzing of bank’s facilities (Case Study: Private Bank of Noor)

Abstract

The design of a credit risk measurement model in the monetary and banking system will play an important role in increasing profits and optimizing the allocation of banking resources. This paper uses credit regression models (Linear, Logit and Probit) and Z Altman to determine and predict the credit risk of providing facilities to legal entities in a private bank. The variables studied in this research include qualitative variables (company life, collateral, experience of managers, type of company) and financial variables (working capital in total assets, book value of equity to book value of debt, total sales to Total assets, accumulated profits to total assets, profit before interest and taxes on total assets). The results of this research show that the use of validation models, despite all the technical and statistical considerations, can accurately determine the credit status and credit risk of customers. All of the models used exceeded 80% of the correct predictions, which is a significant figure in the real business environment. But in the Logit model, with a slightly better difference than the rest of the models, about 83% of its predictions were correct.