Credit risk management of commercial banks in Iran; Using logistic model

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The observed crisis and profitability decreases in banking system are mainly because of the inefficiency in credit risk control and that's why, utilization of customers' ranking system is the most important tool that is required for managing and controlling the risk. The goal of the study was to present an applied model for credit scoring of real entity customers of banks with reliance on statistical information of credit customers of Parsian Bank in Iran. For this purpose the logistic regression model is used to analyze credit ranking and financial scoring of bank’s customers based on their previous and current data record like; job stability, collaterals, income and some other main indicators for estimating non-default probability of facilities offered to each customer. The results of the model estimation showed that non-default probability of facilities have positive relation with variables amount of collaterals received from customer, monthly income amount of the customer, the status of applicant for taking facilities such as place of residence (be owner or tenant of the applicant), the age of applicant for taking facilities, occupational status of the applicant as stability and educational level of the applicant for taking facilities and have negative relation with amount of paid facilities to the customer and payback duration of granted facilities to the applicant. Key words: Risk management, credit risk, commercial bank, logistic regression.