THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CREDIT RISK ASSESSMENT AND BUSINESS MODEL TRANSFORMATION IN THE FINANCIAL SECTOR

The adoption of Artificial Intelligence (AI) in the financial sector is fundamentally transforming credit risk assessment and reshaping business models. This paper explores the impact of AI-driven technologies on credit evaluation, highlighting the shift from traditional, human-based credit scoring systems to machine learning algorithms capable of analyzing vast amounts of structured and unstructured data. By incorporating non-traditional data sources, AI offers a more inclusive and accurate assessment of borrower risk, potentially expanding access to credit for underbanked populations. Furthermore, AI's ability to detect fraud and automate decision-making processes leads to increased operational efficiency for financial institutions. However, the implementation of AI also introduces ethical challenges, including concerns about algorithmic transparency and bias. The paper addresses these issues, proposing that a balance between technological innovation and regulatory oversight is crucial for fostering responsible AI use in lending. Moreover, AI is transforming business models in the financial sector by enabling personalized product offerings and streamlining operational costs, positioning financial institutions to compete more effectively in a rapidly evolving marketplace. This study concludes by discussing future trends, such as the integration of AI with blockchain technologies and the increasing collaboration between traditional banks and fintech firms. These developments are expected to further drive innovation and redefine the landscape of credit risk management.