A Systematic Review of Banking Economic Value Model: Investment, Credit, Service Quality, and Digitalization
Purpose: This study aims to analyze the impact of AI adoption on the economic value of banks, focusing on AI-based investments, AI in credit processes, service quality, and the moderating role of bank digitalization.
Research Methodology: A qualitative approach through a systematic literature review was applied. A total of 85 relevant studies from journals indexed in ScienceDirect, Emerald, Google Scholar, and Scopus were analyzed to identify factors influencing the economic value of banks.
Results: The findings show that AI-based investments, AI in credit processes, service quality driven by AI, and bank digitalization significantly contribute to enhancing the economic performance of banks. Digitalization through AI strengthens the competitive advantage and operational efficiency of banks.
Conclusions: This study concludes that AI investments, AI-driven credit processes, service quality improvements via AI, and the level of digitalization are critical in increasing the economic value of banks. The findings provide insights for developing banking economic models in the digital era.
Limitations: This study is limited to analyzing AI, credit, service quality, and digitalization in banking. Future research should explore additional factors influencing the economic performance of banks.
Contributions: The study contributes to understanding the role of AI in banking performance, offering guidance for banks in leveraging AI and digitalization to enhance their economic value. Further research is encouraged to examine other potential factors impacting bank performance.
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