Abstract
Risk Analysis of Mortgage Loan Default
for Banks is a crucial issue. On one hand, it concerns the quality of the
bank's credit decisions, and on the other hand, it affects the rights of
homebuyers to obtain financial support. In 2008, the U.S. subprime mortgage
crisis sparked a global financial meltdown. What began with the collapse of the
housing market quickly spread throughout the global financial system, resulting
in the failure of numerous banks and a widespread economic recession. Recently,
the banking sector has increasingly leveraged Artificial Intelligence (AI) and
Machine Learning (ML) to enhance decision-making processes, particularly in
assessing the risk of mortgage loan defaults. This paper aims to explore the
application of ML techniques to predict and analyze the risk of default among
bank customers, thereby enabling financial institutions to make more accurate
and informed lending decisions.
Keywords: Mortgage Loan
Default Risk Analysis AI ML K-MANS LTV.