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The paper presents a developed neural network model of interaction between entrepreneurship enterprises and financial system. A hypothesis that a neural network makes it possible to simulate the interaction between complex systems and develop a profit forecast for enterprises in the real sector of the economy under risk has been put forward and proved.

The paper presents analysis of the Russian Federation's monetary policy. The Central Bank's key rate is an important parameter. It is hypothesized that the key rate (KR) could be predicted by means of artificial intelligence, a perceptron, the input of which is generated by neural-network quantization. Applying the results of such "smart" analysis to predicting the CBR key rate seems appropriate.