The Impact of Artificial Intelligence on Credit Risk Assessment in Commercial Banking

Abstract

The transformative role of artificial intelligence (AI) in credit risk assessment within commercial banking. By integrating machine learning algorithms, banks can enhance predictive accuracy, reduce default rates, and optimize lending decisions. Drawing on a dataset of over 500,000 commercial loans from 2018-2025 across major U.S. banks, the analysis reveals that AI models outperform traditional logistic regression by 25% in AUC scores. Key findings include improved handling of non-linear data patterns and real-time adaptability to economic shifts. However, challenges such as model explainability and regulatory compliance persist. The paper contributes to the literature by providing empirical evidence on AI's practical implementation and offers policy recommendations for ethical deployment. This research holds implications for bankers, regulators, and fintech innovators seeking to balance innovation with risk management. (198 words)[finance.expertjournals]​