The Impact of Artificial Intelligence on Credit Security in the Iraqi Banking System
Keywords:
Iraqi banking system, Credit security, artificialAbstract
Objective: This study aims to examine the impact of artificial intelligence on credit security in digital-oriented banks within the Iraqi banking system.
Methodology: This applied study employed a correlational design. Data were collected using two standardized five-point Likert-scale questionnaires distributed among 200 employees, managers, and customers of 10 digital-oriented Iraqi banks. Reliability was confirmed using Cronbach’s alpha, and data were analyzed through Pearson correlation and linear regression using SPSS version 26.
Findings: The results revealed a strong and significant positive correlation between artificial intelligence and credit security (r = 0.72, p < 0.01). Regression analysis indicated that artificial intelligence is a significant predictor of credit security (β = 0.42, p < 0.001), explaining 63% of the variance in credit security.
Conclusion: The findings demonstrate that artificial intelligence plays a substantial role in enhancing credit security in Iraqi banks, highlighting its strategic importance for credit risk management and evidence-based banking policy formulation in emerging digital financial systems.
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Copyright (c) 2025 Maan Hadi Hasoon Al-Absi, Maryam Khalili Araghi, Zohreh Hajiha (Author)
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