Data Mining in Assessing the Risks of Electric Power Enterprises

摘要

The article is devoted to the assessment of the risks of energy enterprises. To assess the risks, the assessment criteria for debtors, areas of energy activity enterprises are indicated. Clustering of energy enterprises was carried out by the level of risks and by performance indicators. Data processing was carried out using the processing wizard in the Deductor Academic system: building a decision tree, neural networks, self-organizing Kohonen maps. Based on the results of the assessment, decisive factors that increase the level of risk were identified