Artificial Intelligence (AI) in activating bank credit leads to better decision making when analyzing customer data, finding out whether they’re credit worthy, saving banks the risks that come with inappropriate credit deploys. AI accelerates the processing of the loan, the accuracy is improved, and the evaluation is fairer. This makes banking credit systems more efficient, customer satisfied, and help to shift public banking credit systems into a smarter and data driven model. This study samples 60 banking professionals from the USA and China having major banks as the basis for the impact of AI on activating bank credit. Research using a comparative approach develops an AI implementation performance by employing credit rate, repayment rate, loss rate, turnover rate and profitability before and after AI implementation. The results of using regression models and ANOVA test confirm that there are significant positive correlations between AI usages and improved banking outcomes. The analysis of key variables such as efficiency, accuracy, profitability and risk management proved that AI stands out as a strong predictor of credit performance. AI brings its results to the assessment of credit, reduces default rates and speeds up the processing of loans.
Keywords: Artificial Intelligence (AI), Bank credit, Profitability, Repayment Rate, Risk Assessment, credit rate
