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Machine Learning Models and Data-Balancing Techniques for Credit Scoring: What Is the Best Combination?
16 references·1 citing·25 second hop
Machine Learning Models and Data-Balancing Techniques for Credit Scoring: What Is the Best Combination? (2022)Machine Learning Models and Data-Balancin…Corporate default forecasting with machine learning (2020)Corporate default forecasting…Machine Learning in Banking Risk Management: A Literature Review (2019)Machine Learning in Banking R…A comparative assessment of ensemble learning for credit scoring (2010)A comparative assessment of e…Credit rating by hybrid machine learning techniques (2009)Credit rating by hybrid machi…The Credit Scoring Toolkit (2007)The Credit Scoring ToolkitCredit risk assessment with a multistage neural network ensemble learning approach (2007)Credit risk assessment with a…Credit scoring with a data mining approach based on support vector machines (2006)Credit scoring with a data mi…Credit scoring and rejected instances reassigning through evolutionary computation techniques (2003)Credit scoring and rejected i…Credit Risk (2003)Credit RiskCredit rating analysis with support vector machines and neural networks: a market comparative study (2003)Credit rating analysis with s…Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Benchmarking state-of-the-art…Neural network credit scoring models (2000)Neural network credit scoring…A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers (2000)A survey of credit and behavi…Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Statistical Classification Me…A comparison of neural networks and linear scoring models in the credit union environment (1996)A comparison of neural networ…Multivariate Normality and Forecasting of Business Bankruptcy (1987)Multivariate Normality and Fo…Machine learning techniques for default prediction: an application to small Italian companies (2023)Machine learning techniques f…The Pricing of Options and Corporate Liabilities (1973)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience) (1994)Recent developments in consumer credit risk assessment (2007)A Stochastic Approximation Method (1951)CREDIT SCORING, STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE (2011)Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects (2021)A Discriminant Analysis of Predictors of Business Failure (1972)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Consumer credit-risk models via machine-learning algorithms (2010)Value At Risk: The New Benchmark for Managing Financial Risk (2000)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)A machine learning approach combining expert knowledge with genetic algorithms in feature selection for credit risk assessment (2021)Digital transformation of organizations: what do we know and where to go next? (2021)Machine learning-driven credit risk: a systemic review (2022)The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients (2008)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Integrating learning styles and adaptive e-learning system: Current developments, problems and opportunities (2015)Statistical and machine learning models in credit scoring: A systematic literature survey (2020)Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis (2021)A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010)Machine behaviour (2019)How Profitable Is Capital Structure Arbitrage? (2006)Measuring Default Risk Premia from Default Swap Rates and EDFs (2007)An Empirical Analysis of the Pricing of Collateralized Debt Obligations (2008)
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References

  • 1997Statistical Classification Methods in Consumer Credit Scoring: A Review1,039 cited
  • 2000Neural network credit scoring models1,032 cited
  • 2003Credit rating analysis with support vector machines and neural networks: a market comparative study1,017 cited
  • 2003Benchmarking state-of-the-art classification algorithms for credit scoring903 cited
  • 2006Credit scoring with a data mining approach based on support vector machines805 cited
  • 2000A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers744 cited
  • 2003Credit Risk560 cited
  • 1996A comparison of neural networks and linear scoring models in the credit union environment522 cited
  • 2010A comparative assessment of ensemble learning for credit scoring501 cited
  • 2019Machine Learning in Banking Risk Management: A Literature Review463 cited
  • 1987Multivariate Normality and Forecasting of Business Bankruptcy354 cited
  • 2007Credit risk assessment with a multistage neural network ensemble learning approach310 cited
  • 2003Credit scoring and rejected instances reassigning through evolutionary computation techniques226 cited
  • 2007The Credit Scoring Toolkit196 cited
  • 2009Credit rating by hybrid machine learning techniques

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177 cited
  • 2020Corporate default forecasting with machine learning168 cited
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    • 2023Machine learning techniques for default prediction: an application to small Italian companies19 cited