EFFECT OF FIRM AGE IN CREDIT SCORING MODEL FOR SMALL SIZED FIRMS

Abstract

A number of Japanese banks have utilized credit scoring models to manage their debtors' credit risk. It is common to utilize a logistic regression model in order to calculate credit scores of small sized firms with twenty or less employees, linked to the correlations between financial indicators and default occurrence. However, the levels of the correlations of small sized firms are lower than those of medium or large sized firms, since the most of small sized firms are run by owner's family members, and deficits incurred from their businesses are compensated with the private assets of owner. Hence, the accuracy ratio of the credit scoring model for small sized firms is not as high as we expected. Hibiki, Ogi and Toshiro (2010) suggested the use of “firm age” as a variable in the model, and analyzed it by using a data set of more than 480 thousand Japanese small sized firms for the period from 2004 to 2007. The result is that they reveal the default occurrence rate measured by the firm age can be expressed by the cubic function, and confirm the introduction of the cubic function into the model as one of variables which improves the accuracy ratio for small sized firms. However, the robustness of our model is not sufficiently confirmed because only four-year data was available. In this paper, we extended the data period from 2004 to 2011, and analyzed it by using a data set of more than a million Japanese small sized firms. The result confirms that our model is sufficiently robust. In addition, we are able to reveal that (i) the effect of firm age is robust in terms of time series, (ii) we can use the cubic function of the firm age as a proxy variable of the private assets of owner.