ANALYSIS OF SCIENTIFIC RESEARCH ON MACHINE LEARNING TECHNOLOGIES IN THE FIELD OF FINANCE AND CREDIT IN UZBEKISTAN

Abstract

In recent years, Uzbekistan has witnessed a growing level of scientific activity in the field of applying machine learning methods in the financial sector. Of particular relevance is the area related to credit scoring—automated assessment of borrowers’ creditworthiness using intelligent algorithms. Based on an analysis of publications by Uzbek researchers from 2020 to 2024, several key trends and research approaches can be identified. Modern technologies are exerting an increasing influence on the development of the financial sector. One of the key directions of digital transformation is the implementation of machine learning and artificial intelligence methods for data analysis, risk forecasting, and optimization of business processes. The application of these methods is especially important in the area of credit scoring—systems for assessing customers’ solvency. The use of machine learning makes it possible to improve prediction accuracy, reduce default rates, and accelerate decision-making processes in banks and microfinance institutions.