Abstract:

Nowadays, the world economic system is entering the stage of the fourth industrial revolution, based on the large-scale implementation of information and communication technologies. Today there is practically no sector of the economy without the introduction of digital technologies. The use of computer technology led to the creation of a new model of economic development - a digital economy based on the introduction of the most innovative digital technology. In the modern world, there is an active implementation of technologies that provide breakthrough directions in the development of the economy and business. One of the most promising areas in the digital economy is the design and use of artificial neural networks or artificial intelligence. They are capable of managing objects of any complexity, providing a reliable forecast based on the analysis of huge amounts of information. At present, artificial intelligence systems are used in many areas of economic development: in telecommunications companies, industry, and medicine. One of the leaders in the use of artificial neural network technology is the financial sphere. Many financial institutions apply artificial intelligence systems in scoring systems that can provide higher reliability compared to existing systems when assessing a borrower, forecasting cash flow of a credit institution, assessing the adequacy of the level of capital of a banking organization, and many other areas.  The paper discusses aspects of the introduction and use of neural network technology in the financial and economic spheres, conducts a financial analysis of the global and Russian market of artificial neural network technology in the financial sector, analyzes the use of artificial intelligence systems in the financial sphere, and studies the prospects for the development of neural network technology in financial institutions. Particular attention is paid to assess the economic efficiency of the investment project under the design and implementation of innovative digital projects. It is difficult to carry out such an assessment. Therefore, the paper  proposes a model of an efficiency assessment using the example of the introduction of a scoring system with artificial intelligence.