• Lalichetti Anirudh Venu Gopal
• Gorthi Anil Kumar
• Mohammad Habeebulla Arshad
• Godavarti Vinay Kumar
• Aiswarya Lalichetti

Credit risk management is a critical component of the financial industry, allowing financial institutions to effectively evaluate and manage the risks associated with lending and investing. Inadequate credit risk management can result in significant financial losses for financial institutions, businesses, and investors and have broader economic consequences. Therefore, it is essential to have effective credit risk management practices in place to protect against these risks. The literature survey highlights the importance of credit risk management, the development of credit risk models, and the growing use of big data and machine learning in credit risk management. The impact of regulatory frameworks on credit risk management practices is also discussed. However, challenges and limitations associated with credit risk management remain, including the difficulty in accurately predicting credit risk and the need for ongoing research and development. Overall, this research paper contributes to the ongoing conversation around effective risk management practices and their role in promoting financial stability and growth. By providing a comprehensive understanding of credit risk management, we hope to contribute to developing more effective credit risk management practices and enabling more excellent financial stability and growth.

Models implemented- LGD,PD,EAD

"Credit Risk Management using Logistic and Linear Regression", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 4, page no.d68-d71, April-2023, Available :http://www.jetir.org/papers/JETIR2304310.pdf

"Credit Risk Management using Logistic and Linear Regression", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 4, page no. ppd68-d71, April-2023, Available at : http://www.jetir.org/papers/JETIR2304310.pdf