Most areas of human activity, including the economy, require constant improvement. Every year, the volume of information and the speed of its change are rapidly increasing. Processing and managing so much human intelligence is inefficient, and using traditional computing becomes a time-consuming process. Therefore, modern information technologies come to the rescue. Today, various intelligent methods are widely used for data analysis, in particular, neural networks. In order for an enterprise to function more effectively, many statistical methods and models are created, as well as specialized software. However, most methods lack Multi-linearity, it is possible to describe most processions and uniqueness of the stationary solution in systems equations, which makes it not accurate enough. In such cases, the use of neural networks as a method of modeling economic processes is Crucial. The purpose of this study was to highlight the concept of a piece neural network and the principles of its functioning. To investigate the use of neural networks as a method of forecasting and modeling economic refinancing processes, as well as to highlight the main types of software for working with neural networks.