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A data driven ensemble classifier for credit scoring analysis
15 references·16 citing·28 second hop
A data driven ensemble classifier for credit scoring analysis (2009)A data driven ensemble classifier for cre…Using neural network ensembles for bankruptcy prediction and credit scoring (2007)Using neural network ensemble…Using Bayesian networks for bankruptcy prediction: Some methodological issues (2006)Using Bayesian networks for b…Credit scoring with a data mining approach based on support vector machines (2006)Credit scoring with a data mi…Hybrid mining approach in the design of credit scoring models (2005)Hybrid mining approach in the…Predicting corporate failure: empirical evidence for the UK (2004)Predicting corporate failure:…Neural network ensemble strategies for financial decision applications (2004)Neural network ensemble strat…Credit scoring and rejected instances reassigning through evolutionary computation techniques (2003)Credit scoring and rejected i…Bayesian network classifiers for identifying the slope of the customer lifecycle of long-life customers (2003)Bayesian network classifiers …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…A comparison of neural networks and linear scoring models in the credit union environment (1996)A comparison of neural networ…Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience) (1994)Corporate distress diagnosis:…Neural Networks: A New Tool for Predicting Thrift Failures* (1992)Neural Networks: A New Tool f…Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Managerial Applications of Ne…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods (2023)Consumer credit risk assessme…A Hybrid XGBoost-MLP Model for Credit Risk Assessment on Digital Supply Chain Finance (2022)A Hybrid XGBoost-MLP Model fo…Multi-classification assessment of bank personal credit risk based on multi-source information fusion (2021)Multi-classification assessme…Majority voting ensemble with a decision trees for business failure prediction during economic downturns (2021)Majority voting ensemble with…A Comparative Performance Assessment of Ensemble Learning for Credit Scoring (2020)A Comparative Performance Ass…A Multi-Stage Self-Adaptive Classifier Ensemble Model With Application in Credit Scoring (2019)A Multi-Stage Self-Adaptive C…A dynamic credit risk assessment model with data mining techniques: evidence from Iranian banks (2019)A dynamic credit risk assessm…Dynamic ensemble classification for credit scoring using soft probability (2018)Dynamic ensemble classificati…Predicting creditworthiness in retail banking with limited scoring data (2016)Predicting creditworthiness i…Classification methods applied to credit scoring: Systematic review and overall comparison (2016)Classification methods applie…A new hybrid ensemble credit scoring model based on classifiers consensus system approach (2016)A new hybrid ensemble credit …Enhancing accuracy and interpretability of ensemble strategies in credit risk assessment. A correlated-adjusted decision forest proposal (2015)Enhancing accuracy and interp…Selection of Support Vector Machines based classifiers for credit risk domain (2014)Selection of Support Vector M…Credit rating with a monotonicity-constrained support vector machine model (2014)Credit rating with a monotoni…An Overview of Personal Credit Scoring: Techniques and Future Work (2012)An Overview of Personal Credi…An Artificial Neural Network Approach for Credit Risk Management (2011)An Artificial Neural Network …Limited-dependent and qualitative variables in econometrics (1983)How effective are neural networks at forecasting and prediction? A review and evaluation (1998)A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010)Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)The Pricing of Options and Corporate Liabilities (1973)Recent developments in consumer credit risk assessment (2007)A comparative assessment of ensemble learning for credit scoring (2010)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)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Statistical and machine learning models in credit scoring: A systematic literature survey (2020)ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)The effects of government ownership on bank lending (2003)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)Financial Ratios As Predictors of Failure (1966)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy (2010)Bankruptcy prediction using terminal failure processes (2014)Systematic review of bankruptcy prediction models: Towards a framework for tool selection (2017)Forecasting with artificial neural networks: (1998)Application of data mining techniques in customer relationship management: A literature review and classification (2008)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Machine behaviour (2019)Managerial incentives and risk-taking☆ (2005)How does financial reporting quality relate to investment efficiency? (2009)
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References

  • 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY14,869 cited
  • 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions1,121 cited
  • 1994Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)1,059 cited
  • 2000Neural network credit scoring models1,032 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
  • 1992Neural Networks: A New Tool for Predicting Thrift Failures*533 cited
  • 1996A comparison of neural networks and linear scoring models in the credit union environment522 cited
  • 2007Using neural network ensembles for bankruptcy prediction and credit scoring514 cited
  • 2004Predicting corporate failure: empirical evidence for the UK429 cited
  • 2004Neural network ensemble strategies for financial decision applications332 cited
  • 2003Credit scoring and rejected instances reassigning through evolutionary computation techniques226 cited
  • 2005Hybrid mining approach in the design of credit scoring models196 cited
  • 2006Using Bayesian networks for bankruptcy prediction: Some methodological issues

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170 cited
  • 2003Bayesian network classifiers for identifying the slope of the customer lifecycle of long-life customers161 cited
  • Cited by

    • 2016A new hybrid ensemble credit scoring model based on classifiers consensus system approach161 cited
    • 2020A Comparative Performance Assessment of Ensemble Learning for Credit Scoring152 cited
    • 2014Selection of Support Vector Machines based classifiers for credit risk domain142 cited
    • 2018Dynamic ensemble classification for credit scoring using soft probability118 cited
    • 2015Enhancing accuracy and interpretability of ensemble strategies in credit risk assessment. A correlated-adjusted decision forest proposal109 cited
    • 2019A dynamic credit risk assessment model with data mining techniques: evidence from Iranian banks106 cited
    • 2011An Artificial Neural Network Approach for Credit Risk Management100 cited
    • 2014Credit rating with a monotonicity-constrained support vector machine model89 cited
    • 2022A Hybrid XGBoost-MLP Model for Credit Risk Assessment on Digital Supply Chain Finance71 cited
    • 2023Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods71 cited
    • 2016Classification methods applied to credit scoring: Systematic review and overall comparison68 cited
    • 2012An Overview of Personal Credit Scoring: Techniques and Future Work66 cited
    • 2019A Multi-Stage Self-Adaptive Classifier Ensemble Model With Application in Credit Scoring65 cited
    • 2021Majority voting ensemble with a decision trees for business failure prediction during economic downturns63 cited
    • 2021Multi-classification assessment of bank personal credit risk based on multi-source information fusion59 cited
    • 2016Predicting creditworthiness in retail banking with limited scoring data54 cited