INTELLIGENT SYSTEM FOR ANALYZING BANK CUSTOMER DATA BASED ON THE INTEGRATION OF BUSINESS INTELLIGENCE AND MACHINE LEARNING METHODS

Abstract

The article presents the development of an intelligent system for analyzing customer data in a commercial bank based on the integration of Business Intelligence technologies and machine learning methods. The research examines architectural principles of analytical banking systems, data mart design approaches, and machine learning algorithms used for assessing customer investment potential. The developed system includes automated data collection and processing, investment scoring models, recommendation models for financial instruments, and visualization of analytical results using Microsoft Power BI. The proposed approach improves analytical accuracy, enhances decision-making quality, and increases the level of personalization of banking services. The practical significance of the research lies in the possibility of implementing the developed solution in banking practice to improve the competitiveness of financial institutions.