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Reject inference in consumer credit scoring with nonignorable missing data
6 references·7 citing·44 second hop
Reject inference in consumer credit scoring with nonignorable missing data (2012)Reject inference in consumer credit scori…Consumer credit-risk models via machine-learning algorithms (2010)Consumer credit-risk models v…Economic benefit of powerful credit scoring (2005)Economic benefit of powerful …Does reject inference really improve the performance of application scoring models? (2003)Does reject inference really …Bank lending policy, credit scoring and value-at-risk (2003)Bank lending policy, credit s…A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers (2000)A survey of credit and behavi…An econometric analysis of the bank credit scoring problem (1989)An econometric analysis of th…Interpretable selective learning in credit risk (2023)Interpretable selective learn…RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring (2022)RMT-Net: Reject-aware Multi-T…Reject inference in credit scoring using a three-way decision and safe semi-supervised support vector machine (2022)Reject inference in credit sc…A Framework of Global Credit-Scoring Modeling Using Outlier Detection and Machine Learning in a P2P Lending Platform (2022)A Framework of Global Credit-…A CWGAN-GP-based multi-task learning model for consumer credit scoring (2022)A CWGAN-GP-based multi-task l…A graph-based semi-supervised reject inference framework considering imbalanced data distribution for consumer credit scoring (2021)A graph-based semi-supervised…A new approach in reject inference of using ensemble learning based on global semi-supervised framework (2020)A new approach in reject infe…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 comparative assessment of ensemble learning for credit scoring (2010)The Estimation of Choice Probabilities from Choice Based Samples (1977)Predicting criminal recidivism using ‘split population’ survival time models (1989)Testing for Liquidity Constraints in Euler Equations with Complementary Data Sources (1998)A stochastic frontier model with correction for sample selection (2009)Credit Scoring and Its Applications (2002)Enterprise risk management: small business scorecard analysis (2009)Credit scoring for microfinance: is it worth it? (2011)Credit Scoring and Its Applications (2017)Statistical Challenges of Administrative and Transaction Data (2018)Credit Rationing in Markets with Imperfect Information (1981)Costly Monitoring, Loan Contracts, and Equilibrium Credit Rationing (1987)Inside the Black Box: The Credit Channel of Monetary Policy Transmission (1995)A COMPARISON OF DATA MINING TECHNIQUES FOR CREDIT SCORING IN BANKING: A MANAGERIAL PERSPECTIVE (2009)Looking behind mortgage delinquencies (2016)A review of credit scoring research in the age of Big Data (2018)The Measurement of Observer Agreement for Categorical Data (1977)Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Counterfactual Fairness (2017)On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services (2018)Empirical Asset Pricing via Machine Learning (2020)The relationship between default prediction and lending profits: Integrating ROC analysis and loan pricing (2004)A literature review on the application of evolutionary computing to credit scoring (2012)The financing of innovative SMEs: A multicriteria credit rating model (2015)A novel tree-based dynamic heterogeneous ensemble method for credit scoring (2020)A Coefficient of Agreement for Nominal Scales (1960)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)A recent review on optimisation methods applied to credit scoring models (2023)Consumer credit risk: Individual probability estimates using machine learning (2013)Credit scoring using the clustered support vector machine (2014)Technology credit scoring model with fuzzy logistic regression (2016)A spatial–temporal graph-based AI model for truck loan default prediction using large-scale GPS trajectory data (2024)Credit risk prediction based on causal machine learning: Bayesian network learning, default inference, and interpretation (2024)Louvain community-based label assignment for reject inference in peer-to-peer lending (2025)Credit scoring with a data mining approach based on support vector machines (2006)A Deep Learning Approach for Credit Scoring Using Feature Embedded Transformer (2022)The EU General Data Protection Regulation (GDPR) (2017)How can consumers without credit history benefit from the use of information processing and machine learning tools by financial institutions? (2024)
this work references cited by second hop

References

  • 2010Consumer credit-risk models via machine-learning algorithms861 cited
  • 2000A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers744 cited
  • 1989An econometric analysis of the bank credit scoring problem284 cited
  • 2003Bank lending policy, credit scoring and value-at-risk149 cited
  • 2005Economic benefit of powerful credit scoring135 cited
  • 2003Does reject inference really improve the performance of application scoring models?88 cited

Cited by

  • 2021A graph-based semi-supervised reject inference framework considering imbalanced data distribution for consumer credit scoring41 cited
  • 2022Reject inference in credit scoring using a three-way decision and safe semi-supervised support vector machine40 cited
  • 2023Interpretable selective learning in credit risk31 cited
  • 2022A CWGAN-GP-based multi-task learning model for consumer credit scoring28 cited
  • 2022A Framework of Global Credit-Scoring Modeling Using Outlier Detection and Machine Learning in a P2P Lending Platform21 cited
  • 2020A new approach in reject inference of using ensemble learning based on global semi-supervised framework20 cited
  • 2022RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring17 cited

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