Performance Analysis of Machine Learning models for Credit Delinquency Prediction

• Published in: International Journal of Advanced Research in Science, Communication and Technology pp. 301 - 307
• Main Authors: Muktha Priya K S, Sunitha G P
• Format: Journal Article
• Language: English
• Published: 30.06.2022
• ISSN: 2581-9429; 2581-9429
• DOI: 10.48175/IJARSCT-5454

The activities of lending loan to those who are in the financial distress are implemented by the financial institutions like bank. The area which is becoming significant in the analysis of monetary risk is credit risk assessment. The distinct dataset's credit risk is considered using multiple machine learning methods. The review of all credit risk databases should be used to draw a conclusion on when to grant the loan to the particular customer or disapprove the individual's application, which is a complex job. The paper evaluates an in-depth inspection of the individual’s credit dataset or check by the consumer. This study investigated various risk assessment methodologies that are used in the evaluation of credit datasets. Using trained ml algorithms, it is possible to find correlations between consumer preferences and characterize them for early action.