Credit risk ratings consist of assessing the
creditworthiness of the issuer and gauge the risks associated with buying its
debt. Any delay in updating the credit risk ratings could have a severe impact
on the financial system such as the financial crisis in 2008. This paper
discusses a case that leverages emerging technology and breakthrough cognitive
analytics in the financial industry. It specifically describes the design and
implementation of a predictive modeling case based on the Machine Learning
Approach and its application in credit risk forecasting and portfolio
management. Using big data and Machine Learning, it is possible to improve
credit risk analysis and forecasting by allowing the algorithms to search for
patterns using large sets of data.