Scientific Journal of KubSAU

Destabilization of the economic situation in Russia at the end of 2014 and in early 2015 has influenced small and medium businesses (SMB) landing at first. One of the most important reason of high lending risks and, as a result, high lending rates is absence of reliable information systems for assessment of SMB enterprise default according to total analysis of their financial activities. Thus nowadays the reliable assessment of SMB enterprises solvency is the fundamental scientific problem, which one is highly actual for each credit organization because the bankruptcy of a credit institution is depended on it. At the same time high competition at the landing market leads to necessity of individual credit conditions existing, which takes into account borrower’s and lender’s benefits. In the present work the creating of reliable information and analytical systems for assessment of SMB company default method is suggested. This one is based on integration of probabilistic and statistical classification analysis methods (discriminant analysis, logistic regression, and classification trees), heuristic procedures (neural network) and interactive shell of the system using cloud technology. By the authors, there was solved the problem of small data amount, exception anomalous values and discrepancy normal distribution of sample by the generation of enterprises financial activity model database

In the present work Russian enterprises non-payment risk method is suggested. This one is based on methods of classification analysis in the case of financial indices patterns of the enterprise are known. The STATISTICA VISUAL BASIC (SVB) programm-module was created for automatisation of classificaton process