levist7/Credit_Risk_Modelling
Credit Risk Modelling | Calculation of PD, LGD, EDA and EL with Machine Learning in Python
This project helps financial institutions and credit analysts assess the risk of borrowers not repaying loans. It takes historical loan data as input and produces a credit scorecard, along with models for Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and Expected Loss (EL). These outputs enable financial professionals to make informed decisions about credit applications and manage their loan portfolios.
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Use this if you need to build and evaluate credit risk models compliant with Basel accords, generating a practical scorecard and calculating potential financial losses from loan defaults.
Not ideal if you are looking for a fully-packaged, plug-and-play software solution for credit risk assessment without any need for technical setup or understanding of the underlying models.
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67
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30
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Mar 15, 2023
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