<![CDATA[This study analyzes the impact of digital transformation and artificial intelligence on credit risk management effectiveness, operational efficiency, and data quality in Indonesia's national private banks. Using a quantitative method, the data were analyzed with SmartPLS 3.0 through the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. The sample consists of 100 employees from the credit risk and IT divisions of 20 national private banks that utilize artificial intelligence, selected using stratified random sampling. The findings reveal that digital transformation and artificial intelligence positively influence operational efficiency and data quality, significantly enhancing credit risk management effectiveness. Data quality mediates the relationship between artificial intelligence and credit risk management, while operational efficiency also serves as a strong mediator. This study highlights the importance of digital innovation as an effective strategy for national private banks to strengthen credit risk management through technology.]]>
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