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Credit Risk Prediction Based on Machine Learning Methods
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Credit Risk Prediction Based on Machine Learning Methods (2019)Credit Risk Prediction Based on Machine L…Effective Credit Risk Prediction Using Ensemble Classifiers With Model Explanation (2024)Effective Credit Risk Predict…Credit Risk Prediction using Ensemble Machine Learning Algorithms (2023)Credit Risk Prediction using …Credit risk analysis using boosting methods (2023)Credit risk analysis using bo…FAIR: Fair adversarial instance re-weighting (2022)FAIR: Fair adversarial instan…Exploitation of Machine Learning Algorithms for Detecting Financial Crimes Based on Customers’ Behavior (2022)Exploitation of Machine Learn…Application of Machine Learning Techniques for Credit Risk Management: A Survey (2022)Application of Machine Learni…Improved credit scoring model using XGBoost with Bayesian hyper-parameter optimization (2021)Improved credit scoring model…A Credit Risk Model with Small Sample Data Based on G-XGBoost (2021)A Credit Risk Model with Smal…Big Data's Disparate Impact (2014)Certifying and Removing Disparate Impact (2015)Equality of Opportunity in Supervised Learning (2016)Algorithm Fairness in AI for Medicine and Healthcare (2021)The Fairness of Credit Scoring Models (2021)Interpreting Unfairness in Graph Neural Networks via Training Node Attribution (2023)Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)Extreme Learning Machine Enhanced Gradient Boosting for Credit Scoring (2022)A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior (1980)International Economic Review (2010)Consumer credit risk: Individual probability estimates using machine learning (2013)Mining the customer credit using classification and regression tree and multivariate adaptive regression splines (2004)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Machine learning models and bankruptcy prediction (2017)Credit Risk Analysis Using Machine and Deep Learning Models (2018)A study on predicting loan default based on the random forest algorithm (2019)Loan default prediction using decision trees and random forest: A comparative study (2021)Machine learning in financial forecasting: A U.S. review: Exploring the advancements, challenges, and implications of AI-driven predictions in financial markets (2024)Consumer credit-risk models via machine-learning algorithms (2010)A benchmark of machine learning approaches for credit score prediction (2020)Financial Inclusion in Emerging Economies: The Application of Machine Learning and Artificial Intelligence in Credit Risk Assessment (2021)Success Prediction using Random Forest, CatBoost, XGBoost and AdaBoost for Kickstarter Campaigns (2019)A Comparative Assessment of Credit Risk Model Based on Machine Learning ——a case study of bank loan data (2020)Credit Risk Assessment based on Gradient Boosting Decision Tree (2020)Beyond Code and Algorithms: Navigating Ethical Complexities in Artificial Intelligence (2024)Two credit scoring models based on dual strategy ensemble trees (2011)A new deep learning ensemble credit risk evaluation model with an improved synthetic minority oversampling technique (2020)An Improved Ensemble Method With Data Resampling for Credit Risk Prediction (2025)
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Cited by

  • 2023Credit Risk Prediction using Ensemble Machine Learning Algorithms41 cited
  • 2022FAIR: Fair adversarial instance re-weighting40 cited
  • 2022Exploitation of Machine Learning Algorithms for Detecting Financial Crimes Based on Customers’ Behavior40 cited
  • 2024Effective Credit Risk Prediction Using Ensemble Classifiers With Model Explanation34 cited
  • 2021A Credit Risk Model with Small Sample Data Based on G-XGBoost21 cited
  • 2023Credit risk analysis using boosting methods20 cited
  • 2021Improved credit scoring model using XGBoost with Bayesian hyper-parameter optimization20 cited
  • 2022Application of Machine Learning Techniques for Credit Risk Management: A Survey14 cited

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