The Research On Risks Of Granting Credit To Customers In The Logistics Industry

Credit rating of logistics enterprises’ customers is intended to help these enterprises to control risks of granting credit to customers(i.e. risks of customer default). The customer default risk evaluation system has been established in this paper. Usually default risk evaluation systems like in this paper are not tested in models. This paper attempts to use the KMV model, a credit risk measure model wildly adapted to global conditions, to calculate rate of default, in order to achieve the goal of model testing. According to characteristics of models which are based on data from the stock market, we first choose 1301 listed companies as samples by combining the default risk evaluation system of this paper and the credit risk measure method of KMV model, and calculate key variables of the KMV model(default distance, DD and expected default rate, EDF) by the Matlab program, and then get samples’ evaluation results and their expected default rates fitting by linear regression. For in sample test the default risk evaluation system’s accurate rate is up to 76.33%. So by the evaluation system established in this paper, enterprises in the logistics industry can effectively judge the risks of granting credit to their customers.