DEVELOPMENT OF RETAIL BANKING SERVICES IN THE CONTEXT OF DIGITAL TRANSFORMATION

The article examines retail banking services, their importance and how they are improving in the context of digital transformation. In the article, using the data of 14 commercial banks in Uzbekistan, the number of observations is 280. The dependent variable is the deposit practice of commercial banks, the independent variables are the credit practice of commercial banks, the remote services of commercial banks and the practice of commercial banks with plastic cards, analyzed through several models. The research shows that when we analyze 3 models based on panel data, the Random effects estimator (REE) model econometric equation of the impact of retail banking services development practices in the national economy today is Y=0.59x1+0.08x2+0.22x3-1.66 is the most optimal model. Accordingly, regarding the choice between the Fixed effects estimator (FEE) model and the Random effects estimator (REE) model, the Hausman test is used to determine which model is more suitable. The test compares the estimates from two models and tests whether the difference between them is statistically significant. If the p-value of the test is greater than the significance level (usually 0.05), then the Random effects estimator (REE) model is preferred because it allows for unobserved heterogeneity not accounted for in the Fixed effects estimator (FEE) model. In this case, the p-value of the Hausman test is equal to 0.36, which is greater than 0.05. We use the Random effects estimator (REE) model to analyze the impact of the practice of developing retail banking services in the national economy today based on panel data. We came to the conclusion that it is suitable.