The relevance is due to the fact that in a “turbulent” economy, there is an increase in volatility in the parameters of the balanced profit of the Russian real economy, while the artificial intelligence systems applied to predict financial risk using the VaR method is important. ![]() A hypothesis that the “decision tree” neural network enables obtaining a forecast of the extent of loss resulting from the financial risk has been put forward and proved. The article deals with the AI neural network for predicting financial risk in the real economy of Russia. The investigation applied monograph and analytical methods, artificial intelligence, design-constructive procedure, data quantization, “decision tree”, as well as analysis, modeling, study and generalization. The theoretical foundations of the VaR-method for the risk index calculation have been considered.
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