International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064




Downloads: 0 | Views: 25

Informative Article | Finance | India | Volume 12 Issue 7, July 2023 | Rating: 4.5 / 10


Leveraging Machine Learning for Creditworthiness Assessment in Banking

Karthika Gopalakrishnan [3]


Abstract: Credit scoring is a critical aspect of banking operations, facilitating informed lending decisions and risk management. Traditional credit scoring methods, while effective, often exhibit limitations in adaptability and predictive accuracy. This paper explores the role of machine learning (ML) techniques in enhancing credit scoring processes within the banking sector. We begin by elucidating the significance of credit scoring for banks, followed by an analysis of conventional credit scoring methodologies and their associated shortcomings. Subsequently, we delve into the application of ML algorithms to credit scoring, highlighting their potential to address existing limitations and improve predictive performance. Furthermore, we present a case study utilizing a sample dataset to demonstrate the efficacy of ML - based credit scoring models. Finally, we discuss future research directions and potential advancements in the field of credit scoring using ML.


Keywords: Credit scoring, Machine learning, Banking, Predictive modeling, Risk management


Edition: Volume 12 Issue 7, July 2023,


Pages: 2284 - 2288



How to Download this Article?

Type Your Valid Email Address below to Receive the Article PDF Link


Verification Code will appear in 2 Seconds ... Wait

Top