小企業向け信用スコアリングモデルにおける業歴関数の頑健性と経営者の個人資産額との関係性

Abstract

Since the 2000s, a number of Japanese banks have utilized credit scoring models to manage their debtors' credit risk. There are various types of credit scoring models. It is common to utilize the logistic regression model in order to calculate credit scores of small sized firms with 20 or less employees, linked to the correlations between financial indicators and default occurrence. However, such 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 the family, which are not described in the companies' financial statements. Hibiki, Ogi and Toshiro (2010) suggested Firm Age as the proxy variable in the model, and analyzed the correlation between firm age and default occurrence calculated using a data set of more than 480,000 Japanese small sized firms for the period from 2004 to 2007, owned by Japan Finance Corporation. However, the robustness of the model was not sufficiently confirmed owing to the short span of data being analyzed. In this paper, we extend the data period from 2004 to 2011, and analyze the correlation calculated from the data set of more than 1,000,000 Japanese small sized firms to validate the robustness of the logistic regression model from a practical perspective. In accordance with Hibiki, Ogi and Toshiro (2010), the results show that i) the default occurrence rate can be expressed by the cubic function of the firm age, and ii) the introduction of cubic function of the firm age into the model as a variable improves the accuracy ratio for small sized firms. Moreover, we confirm that the model is robust, and we can enhance the potential for practical use of the model on sound banking.