STATISTICAL ANALYSIS AND ECONOMIC IMPACT OF SOCIAL PROGRAMMES AND PREFERENTIAL LENDING PRACTICES IMPLEMENTED BY COMMERCIAL BANKS

This article presents a comprehensive statistical analysis and economic impact assessment of social programmes and preferential lending practices implemented by commercial banks in Uzbekistan. Drawing on data from the Central Bank of Uzbekistan, the Agency of Statistics, and the Ministry of Poverty Reduction and Employment, the study quantifies the volume, structure, and outreach dynamics of bank-administered social programmes over the period 2019–2023. The article identifies three principal channels through which preferential lending generates economic impact: household income augmentation, employment creation, and the reduction of extreme poverty incidence among targeted beneficiaries. A regression-based analysis confirms a statistically significant positive association between the volume of subsidised credit and the number of newly created jobs at the regional level. SWOT analysis reveals that while the mahalla institutional framework constitutes a distinctive comparative advantage for Uzbekistan’s social banking model, deficiencies in monitoring infrastructure and uneven regional bank penetration constrain overall programme effectiveness. The findings support policy recommendations directed at standardising impact measurement, extending preferential product lines to women and youth, and integrating digital credit-scoring technologies to reduce transaction costs for the most vulnerable households.本文针对乌兹别克斯坦商业银行推行的社会帮扶计划与优惠信贷实践，开展了全面的统计分析与经济影响评估。本研究依托乌兹别克斯坦中央银行、国家统计署以及减贫与就业部提供的数据，量化分析了2019至2023年间商业银行管理的社会帮扶计划的规模、结构及服务覆盖范围的动态变化。本文明确了优惠信贷产生经济影响的三大核心路径：提升家庭收入、创造就业岗位，以及降低目标受益群体的极端贫困发生率。基于回归模型的分析证实，在区域层面，贴息信贷规模与新增就业岗位数量之间存在显著的正向统计关联。SWOT分析显示，尽管马哈拉（mahalla）制度框架为乌兹别克斯坦的社会银行模式构建了独特的比较优势，但监测基础设施存在短板、区域银行覆盖不均等问题，制约了整体计划的实施成效。本研究结论为多项政策建议提供了实证支撑：统一影响评估标准、向女性与青年群体拓展优惠信贷产品线，以及集成数字化信贷评分技术以降低最弱势家庭的交易成本。