In the banking sector of Lithuania, the necessity to apply statistical scoring models has especially increased after the transposition of the New Capital Adequacy Directive into the national legal acts. According to them, banks are allowed to apply their own statistical models to calculate capital adequacy. However, banks‘ internal data are not allways sufficient for developing internal statistical models. The need to apply statistical scoring models increases not only for banks, but also for other institutions that grant credits. Until now, only several authors in Lithuania have proposed their own statistical scoring models for corporates; however, these models were developed using very small data samples and are suitable for specific types of companies for which they were developed only. The model proposed in this article solves these problems because it is appropriate for assessment of all companies, it is not industry-specific and has been developed using a large data sample. The objective of this study was to develop a logistic regression scoring model for assessment of corporates, using data of the external register JSC Creditinfo Lietuva1. In the proposed model, there are 19 variables characterizing all the features of a company: size, locality, age, economic sector, financial condition, past due payments, negative facts and claims from external debt collection institutions.
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