Artificial Intelligence and Big Data in Improving Credit Risk Assessment in Commercial Banks

This article explores the role of Artificial Intelligence (AI) and Big Data in enhancing credit risk assessment within commercial banks. The study emphasizes the global relevance of the topic, as financial institutions worldwide increasingly rely on machine learning and advanced data analytics to strengthen predictive accuracy and transparency in credit scoring (Hjelkrem et al., 2023; Cuadros-Solas et al., 2024). At the same time, international organizations such as the Financial Stability Board (2024) highlight the potential systemic risks associated with AI adoption, including governance and cybersecurity concerns.The paper also examines the Uzbek context, where the rapid growth of digital payments and lending infrastructures (Central Bank of Uzbekistan, 2024) aligns with national development strategies such as the “New Uzbekistan - 2030” Strategy (Presidential Decree PF-158, 2023) and investment management reforms (Resolution PQ–4477, 2019). By integrating AI and Big Data solutions, Uzbekistan seeks to reduce expected credit losses (ECL), improve financial inclusion, and modernize its banking sector in line with global best practices.