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  <doi_batch_id>aspg-1-4527-1792188515</doi_batch_id>
  <timestamp>20261016220835</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <journal>
   <journal_metadata language="en">
    <full_title>American Journal of Business and Operations Research</full_title>
    <abbrev_title>AJBOR</abbrev_title>
    <issn media_type="print">2770-0216</issn>
    <issn media_type="electronic">2692-2967</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2026</year>
    </publication_date>
    <journal_volume>
     <volume>14</volume>
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    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Strategic Priorities for Ensuring Commercial Bank Liquidity: A Business Intelligence and Data Analytics Approach to the Banking System of Uzbekistan</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Azizjon</given_name>
      <surname>Kholmatov</surname>
      <affiliations>
       <institution>
        <institution_name>Independent researcher at Tashkent International University, Tashkent, Uzbekistan</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>This study identifies strategic priorities for ensuring the liquidity of commercial banks in Uzbekistan through a business data analytics framework that combines regulatory liquidity indicators with a structural analysis of bank funding. Using aggregate data published by the Central Bank of Uzbekistan and the International Monetary Fund for 2020–2025, the paper develops a descriptive, diagnostic, and scenario-based analytics pipeline comprising ratio analysis, a logarithmic decomposition of the loan-to-deposit ratio, a currency-specific funding-gap measure, a deposit run-off sensitivity test, and constant-growth scenarios. The results show that short-term buffers are ample: at the end of 2025 the liquidity coverage ratio stood at 207.5 percent, the net stable funding ratio at 119.9 percent, and high-quality liquid assets at 21 percent of total assets, enough to cover 1.96 times the outflows of a severe run-off scenario. The structural position is weaker. Loans still exceed deposits by 186.7 trillion soums, about 80 percent of this gap is denominated in foreign currency, and the gap is concentrated in state-owned banks. Scenario arithmetic indicates that the loan-to-deposit ratio declines only marginally unless deposit growth exceeds credit growth by a sustained margin. Seven priorities follow, ranging from stable deposit mobilisation and currency-matched funding to the risk-sensitive calibration of liquidity requirements, market and safety-net infrastructure, and bank-level liquidity analytics. The study shows how business intelligence built on publicly reported data can support evidence-based liquidity decisions by bank managers and supervisors.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2026</year>
    </publication_date>
    <pages>
     <first_page>43</first_page>
     <last_page>51</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">4527</item_number>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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     <doi>10.54216/AJBOR.140207</doi>
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