A Machine Learning Framework for Credit Risk Mitigation: Assessing the Impact of AI and Blockchain Integration

Credit risk remains one of the most critical challenges in modern financial systems, with rising borrower defaults, fragmented data infrastructures, and increasing regulatory demands threatening the stability of credit markets. Traditional credit risk models primarily reliant on statistical methods such as logistic regression are often limited in their ability to incorporate alternative data sources or adapt to non-linear borrower behavior. Furthermore, the integrity and authenticity of input data have come under scrutiny amid growing concerns about identity fraud, biased decision-making, and opaque lending processes.