Influence of Artificial Intelligence Application on the Operational Efficiency of Commercial Banks
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https://doi.org/10.65166/tzazy288关键词:
Artificial Intelligence Application, Operational Efficiency, Commercial Banks, Process Automation, Cost Efficiency, Transaction Accuracy摘要
This study examined the influence of artificial intelligence application on the operational efficiency of commercial banks in China. Specifically, it assessed the extent of AI application in terms of customer service and engagement, fraud detection and security, and decision-making and strategy; evaluated operational efficiency in terms of process automation, cost efficiency, and transaction accuracy; tested the relationship between AI application and operational efficiency; and identified which AI application dimensions significantly influenced specific operational efficiency indicators. Using a descriptive-correlational research design, the study gathered data from 250 commercial banking institutions selected through stratified sampling. A self-structured questionnaire was used as the primary research instrument, with reliability testing confirming acceptable to excellent internal consistency across the measured constructs. Data were analyzed using weighted mean, rank, Spearman’s rho correlation, and multiple linear regression. Findings showed that AI application was generally recognized across all three dimensions, with decision-making and strategy receiving the highest assessment. Operational efficiency was also rated favorably across process automation, cost efficiency, and transaction accuracy, with cost efficiency emerging as the strongest operational efficiency dimension. Correlation results revealed highly significant positive relationships between AI application and all operational efficiency indicators. Regression results further indicated that customer service and engagement and decision-making and strategy significantly influenced process automation, while AI-related service, security, and strategic decision-making functions contributed to cost efficiency and transaction accuracy. The study concludes that AI application serves as an important driver of operational efficiency in commercial banking, particularly when deployed not only as a customer-facing tool but also as a strategic, risk-control, and process-improvement mechanism. The findings support the development of an integrated AI deployment plan aimed at strengthening automation, cost control, transaction reliability, and data-driven banking operations.
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