{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T12:00:02Z","timestamp":1772107202595,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T00:00:00Z","timestamp":1771977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Program for the Philosophy and Social Sciences Research of Higher Learning Institutions of Shanxi","award":["2024W066"],"award-info":[{"award-number":["2024W066"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>The complexity of internal control in commercial banks continues to increase, and relevant reports exhibit notable lag and template issues. In response to the demand to transform unstructured disclosures into actionable insights, this study proposes an \u201caugmented Business Intelligence (BI) framework\u201d that integrates a text-based internal control quality assessment system, a dual-validation process, and the resulting Intelligent Internal Control Decision Support System (IIC-DSS). By combining large language models and neural-symbolic models of regulatory prototypes, a quality evaluation system for internal control based on complex text is constructed using a mixed probability mechanism to reduce interference from defensive disclosures. A dual validation process is designed with Partial Least Squares Structural Equation Modeling (PLS-SEM). PLS-SEM verification confirms the construct validity of this evaluation system, while XGBoost verification indicates that internal control quality has incremental predictive ability for asset quality deterioration. The IIC-DSS uses SHapley Additive exPlanations (SHAP) to explain XGBoost outputs, quantifying the marginal contribution of each control factor to the predicted risk. Overall, this study advances internal-control measurement by establishing a neural-symbolic, text-to-indicator representation within an augmented BI architecture and empirically demonstrating its utility in improving predictive power for bank asset quality deterioration and in enhancing decision transparency via explainable AI.<\/jats:p>","DOI":"10.3390\/systems14030234","type":"journal-article","created":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T10:33:02Z","timestamp":1772101982000},"page":"234","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["From Unstructured Text to Automated Insights: An Explainable AI Approach to Internal Control in Banking Systems"],"prefix":"10.3390","volume":"14","author":[{"given":"Ya","family":"Liu","sequence":"first","affiliation":[{"name":"China School of Banking and Finance, University of International Business and Economics, Beijing 100105, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0647-0420","authenticated-orcid":false,"given":"Xinqiu","family":"Li","sequence":"additional","affiliation":[{"name":"China School of Banking and Finance, University of International Business and Economics, Beijing 100105, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Congli","family":"Su","sequence":"additional","affiliation":[{"name":"School of Public Finance and Economics, Shanxi University of Finance and Economics, Taiyuan 030012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3213","DOI":"10.1016\/j.jbankfin.2011.10.020","article-title":"Risk management, corporate governance, and bank performance in the financial crisis","volume":"36","author":"Aebi","year":"2012","journal-title":"J. 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