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The digitalization of the banking sector, which consists of the use of digital tools in banking services, takes banks and other financial institutions to a new level of development. The most important component of digital technologies is intelligent model that reduce the role of people in making various decisions in any banking activity. Risk assessment in the provision of banking services to a client is the most important business process of any commercial bank. The problem of assessing the quality of the borrower in the context of digitalization of the activities of financial institutions goes to a different level, as traditional sources of customer data become insufficient. As part of this work, it is proposed to build a digital model for assessing the class of the borrower, on the one hand, based on fuzzy management technologies, and on the other, on data mining using the SAP cloud system. The proposed model allows you to rank borrowers by quality, distributing them by class. The article shows the economic efficiency of the constructed integrated model based on the data of the commercial bank of the Republic of Tajikistan.

proceedings of the 2nd international scientific and practical conference “modern management trends and the digital economy: from regional development to global economic growth” (mtde 2020)

Intelligent Risk Assessment of Banking Services in the Transition to a Digital Economy Using the Example of Banks in Tajikistan