References

• 2018Study on a prediction of P2P network loan default based on the machine learning LightGBM and XGboost algorithms according to different high dimensional data cleaning444 cited
• 2018Application of eXtreme gradient boosting trees in the construction of credit risk assessment models for financial institutions320 cited
• 2018Information gain directed genetic algorithm wrapper feature selection for credit rating300 cited
• 2018Fintech Credit Markets Around the World: Size, Drivers and Policy Issues281 cited
• 2019A Bolasso based consistent feature selection enabled random forest classification algorithm: An application to credit risk assessment211 cited
• 2016Classifiers consensus system approach for credit scoring202 cited
• 2018Digitalisation and Big Data Mining in Banking132 cited
• 2018Enterprise credit risk evaluation based on neural network algorithm120 cited
• 2020Credit Risk Assessment based on Gradient Boosting Decision Tree94 cited
• 2019Rule-based credit risk assessment model using multi-objective evolutionary algorithms77 cited
• 2021Company bankruptcy prediction framework based on the most influential features using XGBoost and stacking ensemble learning47 cited
• 2017Credit Risk Management27 cited
• 2019Credit Risk and Financial Performance of the Jordanian Commercial Banks: A Panel Data Analysis26 cited

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