MODERN APPROACHES TO OPTIMIZING AND ENHANCING THE EFFICIENCY OF REGIONAL BANKS IN UZBEKISTAN

Аннотация

This article examines modern approaches to optimizing and enhancing the efficiency of regional banks in Uzbekistan. The study analyzes factors such as digitalization, ecosystem models, risk assessment methods, and financial inclusion. Practical examples from Uzbek banking practices are provided to demonstrate their contributions to regional economies. The results indicate that the introduction of AI, blockchain, and targeted products plays a decisive role in improving the competitiveness of banks. By combining regulatory reforms and technological innovations, thesocio-economic potential ofregional banks can bestrengthened. Keywords:regional banks, optimization, efficiency, digitalization, financial ecosystem, credit risks,AI, blockchain, Uzbekistan. Introduction. During Uzbekistan’s economic reforms, regional banks have played a crucial role in shaping the financial infrastructure of provinces, supporting small and medium- sized businesses, and providing accessible services to the population. As of 2023, 12 regional banks operate inthe country, accounting for 25% of the total banking system’s assets. However, global digitalization trends, intensified competition from major banks (e.g., Sberbank, Alif Bank), and rising customer demands compel regional credit institutions to rethink their operational strategies. For instance, while mobile banking users have tripled over the past five years, only 40% of regional banks have fully implemented digital platforms, highlighting issues such as inadequate technological infrastructureand ashortage ofskilled personnel. State programs aimed at expanding financial inclusion (e.g., the “Youth – Our Future” initiative) have created new opportunities for regional banks. However, improving their efficiency requires innovative approaches, enhanced risk management mechanisms, and personalized customer solutions. The purpose of this study is to identify modern methods (e.g., AI, blockchain, ecosystems) to expand the capabilities of regional banks in Uzbekistan, analyze their practical implications based on financial reports and expert interviews, and propose future development directions. The relevance of this research lies in the need to strengthen the role of regional banks in balanced economic development and adapt digitalization to local economic conditions. Research methodology. This study employs a mixed methodology combining qualitativeand quantitativeanalyses: 1. QualitativeAnalysis: Reviewed reports from the Central Bank of Uzbekistan, the Ministry of Finance, and the “Association ofRegional Banks”(2020–2023). Conducted case studies of five regional banks (e.g., Qishloq Qurilish Bank, Agrobank) toexaminesuccessful practices such as digital microcredit systems and agro-ecosystems. page1691 INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE ISSN:2692-5206,ImpactFactor:12,23 AmericanAcademicpublishers,volume05,issue05,2025 Journal: https://www.academicpublishers.org/journals/index.php/ijai Held 15 semi-structured interviews with bank executives and financial experts to identify technological barriers andfuture trends. 2. QuantitativeAnalysis: Compared financial indicators such as NPL (non-performing loans), ROI (return on investment), and digital service adoption rates using statistical data. Analyzed balance sheets of Asaka Bank and Hamkorbank (2021–2023) to assess the impact ofdigitalization onrevenue streams. 3. ComparativeAnalysis: Benchmarked Uzbek practices against international models (e.g., India’s NABARD, Germany’s Sparkassen system). Data sources included scientific literature, official statistics, and expert evaluations. Limitations include restricted access to certain banks’ financial reports and a lack of long-term datafor evaluating new technologies. Analysis and results. A detailed analysis of Uzbekistan’s regional banks reveals multifaceted challenges: technological lag, inefficient resource allocation, and low adaptability tomacroeconomic factors. For example: High Agricultural Credit Risks: Qishloq Qurilish Bank reported a 15% NPL ratio for agricultural loans in 2023,doublethat ofmajorurban banks (e.g., Sberbank: 7%) andexceeding IMF standards (5%). Causes include: Seasonal and climate-dependent agriculture: 30% of cotton-focused loans face delayed repayments dueto climatechange. Weak monitoring systems: 80% of loans rely on paper documentation, hindering real- timerisk assessment. Lack of AI-driven credit scoring: Only 25% of regional banks use AI-based risk models; others depend ontraditionalmethods (guarantors, collateral). Technological Lag: Mobile banking: Agrobank’s app supports only basic functions (account viewing, transfers), whileAlif Bank offers advanced features likeautomated loan approvals. ATM distribution: Rural areas like Fergana have 2 ATMs per 10,000 people, compared to8in Tashkent, limitingcashless transactions. Customer-CentricWeaknesses: Standardized products: Hamkorbank’s microcredit programs lack customization for farmers’seasonal nee