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A hybrid interpretable credit card users default prediction model based on RIPPER
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A hybrid interpretable credit card users default prediction model based on RIPPER (2018)A hybrid interpretable credit card users …Enhancing accuracy and interpretability of ensemble strategies in credit risk assessment. A correlated-adjusted decision forest proposal (2015)Enhancing accuracy and interp…A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring (2015)A hybrid data mining model of…Selection of Support Vector Machines based classifiers for credit risk domain (2014)Selection of Support Vector M…Credit scoring using the clustered support vector machine (2014)Credit scoring using the clus…Classification Restricted Boltzmann Machine for comprehensible credit scoring model (2014)Classification Restricted Bol…Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2013)Predicting financial distress…Two-level classifier ensembles for credit risk assessment (2012)Two-level classifier ensemble…Computational time reduction for credit scoring: An integrated approach based on support vector machine and stratified sampling method (2012)Computational time reduction …Credit card churn forecasting by logistic regression and decision tree (2011)Credit card churn forecasting…A comparative assessment of ensemble learning for credit scoring (2010)A comparative assessment of e…Subagging for credit scoring models (2009)Subagging for credit scoring …Credit Risk Management: Basic Concepts, Financial Risk Components, Rating Analysis, Models, Economic and Regulatory Capital (2009)Credit Risk Management: Basic…The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients (2008)The comparisons of data minin…Recent developments in consumer credit risk assessment (2007)Recent developments in consum…Neural network credit scoring models (2000)Neural network credit scoring…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Applied Statistical Decision Theory (1962)Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)A comparative study on base classifiers in ensemble methods for credit scoring (2016)Forecasting stock market crisis events using deep and statistical machine learning techniques (2018)Machine learning techniques for credit risk evaluation: a systematic literature review (2020)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)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)Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress (1985)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)A comparative study of classifier ensembles for bankruptcy prediction (2014)A novel heterogeneous ensemble credit scoring model based on bstacking approach (2017)The Pricing of Options and Corporate Liabilities (1973)CREDIT SCORING, STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE (2011)Machine Learning in Financial Crisis Prediction: A Survey (2011)A review of trade credit literature: Opportunities for research in operations (2013)Financial Ratios As Predictors of Failure (1966)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Mining corporate annual reports for intelligent detection of financial statement fraud – A comparative study of machine learning methods (2017)Systematic review of bankruptcy prediction models: Towards a framework for tool selection (2017)Deep learning for financial applications : A survey (2020)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)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Credit scoring with a data mining approach based on support vector machines (2006)Zero defections: quality comes to services. (1990)Valuing Customers (2004)The Effects of Customer Satisfaction, Relationship Commitment Dimensions, and Triggers on Customer Retention (2005)Machine-Learning Techniques for Customer Retention: A Comparative Study (2018)Incorporating textual information in customer churn prediction models based on a convolutional neural network (2019)A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers (2000)Using neural network ensembles for bankruptcy prediction and credit scoring (2007)Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction (2018)A XGBOOST RISK MODEL VIA FEATURE SELECTION AND BAYESIAN HYPER-PARAMETER OPTIMIZATION (2019)An Empirical Comparison of Machine-Learning Methods on Bank Client Credit Assessments (2019)Machine Learning in Banking Risk Management: A Literature Review (2019)A Review on Fairness in Machine Learning (2022)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
  • 2000Neural network credit scoring models1,032 cited
  • 2008The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients881 cited
  • 2010A comparative assessment of ensemble learning for credit scoring501 cited
  • 2007Recent developments in consumer credit risk assessment472 cited
  • 2013Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches394 cited
  • 2014Credit scoring using the clustered support vector machine269 cited
  • 2011Credit card churn forecasting by logistic regression and decision tree225 cited
  • 2009Subagging for credit scoring models213 cited
  • 2015A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring178 cited
  • 2014Selection of Support Vector Machines based classifiers for credit risk domain142 cited
  • 2012Two-level classifier ensembles for credit risk assessment119 cited
  • 2015Enhancing accuracy and interpretability of ensemble strategies in credit risk assessment. A correlated-adjusted decision forest proposal109 cited
  • 2012Computational time reduction for credit scoring: An integrated approach based on support vector machine and stratified sampling method

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105 cited
  • 2014Classification Restricted Boltzmann Machine for comprehensible credit scoring model100 cited
  • 2009Credit Risk Management: Basic Concepts, Financial Risk Components, Rating Analysis, Models, Economic and Regulatory Capital91 cited
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