A mathematical model for assessing the probability of default of credit organizations in Russia
This article discusses the construction of a mathematical model for assessing the probability of default of credit organizations of the Russian Federation, based on the TAC approach to assessing credit risks, according to information from open sources and analyzes the quality of the constructed model using special metrics. The work shows that using publicly available data it turned out to create an economic and mathematical model for determining the degree of risk of default of credit organizations of the Russian Federation. This model meets, first of all, qualitative characteristics, showing a high level of separation of classes of objects, and secondly, the characteristics of stability and reliability, showing relatively the same indicators in the training and test samples. This model is ready for use, and can also be further improved by increasing the depth of the data, which will identify new or improve existing indicators and characteristics.