The main objective of this venture was to develop a comprehensive scoring process for bank customers, coupled with a machine learning model. In an era where financial decisions are increasingly powered by data, banks and other financial institutions are constantly seeking innovative and reliable ways to assess the creditworthiness and value of their clients. The task here involved creating a robust mechanism for scoring bank customers, thereby assisting the bank in making more informed and strategic financial decisions.
- Python
- Boruta==0.3
- numpy==1.24.3
- pandas==1.5.3
- scipy== 1.10.1
- seaborn==0.12.2
- missingno==0.4.2
- scikit-learn==0.24.2
- imblearn==0.0
- scipy==1.5.2
- xgboost==1.4.0
- optbinning==0.17.2
- matplotlib==3.7.1
- xlsxwriter==3.0.6
- openpyxl==3.0.9
- statsmodels==0.13.2
- varclushi==0.1.0
- shap==0.41.0