TITLE:
Harnessing Machine Learning Emerging Technology in Financial Investment Industry: Machine Learning Credit Rating Model Implementation
AUTHORS:
Chunlan Wang, Mahmut Rustem Sen, Bin Yao, Michal Certik, Koloina A. Randrianarivony
KEYWORDS:
Machine Learning, Credit Rating, Credit Portfolio Management, Random Forest Methodology, Machine Learning Training and Model Validation, Artificial Intelligence
JOURNAL NAME:
Journal of Financial Risk Management,
Vol.10 No.3,
September
18,
2021
ABSTRACT: 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.