Validating Model and Risk Forecasting for Leasing Customers (Case Study: Iran Khodro Leasing Company)

Abstract

Nowadays, leasing industry is recognized as one of the strategic options in economic development. Leasing companies have a great profitability and are faced to the most risks. Credit risk, business risk, residual value risk and exchange risk are some of important risk in leasing companies. Among them, credit risk is the most important. Subsequently, making logic relationship between risk and return is the essential element to devote optimally resources and to guarantee profitability leasing companies. In this paper, on the basis individual costumers data extracted from Leasing Iran Khodro Company database (since1381-1384) and using tow sample t-student test, and determinant coefficient, we found five variables as factors affect credit risk. They include, net monthly costumer income, loan time, loan amount, net monthly guarantor income and experience. In addition, we apply tow credit risk models (Logit & Probit) for leasing loans. The results of Wald, Log likelihood and Wilk΄S Lambda tests indicate that the efficiency in Logit model (%98.39) is more than Probit model (%97.44).

Keywords

• leasing-risk
• risk management
• credit risk
• logit and probit model