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Does reject inference really improve the performance of application scoring models?
0 references·16 citing·52 second hopsampled
Does reject inference really improve the performance of application scoring models? (2004)Does reject inference really improve the …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 graph-based semi-supervised reject inference framework considering imbalanced data distribution for consumer credit scoring (2021)A graph-based semi-supervised…Deep generative models for reject inference in credit scoring (2020)Deep generative models for re…Cost-sensitive learning for profit-driven credit scoring (2020)Cost-sensitive learning for p…A new approach in reject inference of using ensemble learning based on global semi-supervised framework (2020)A new approach in reject infe…Using Bayesian networks to perform reject inference (2019)Using Bayesian networks to pe…A rejection inference technique based on contrastive pessimistic likelihood estimation for P2P lending (2018)A rejection inference techniq…A new approach for reject inference in credit scoring using kernel-free fuzzy quadratic surface support vector machines (2018)A new approach for reject inf…Credit Invisibles and the Unscored (2016)Credit Invisibles and the Uns…Selection bias in credit scorecard evaluation (2013)Selection bias in credit scor…Company failure prediction with limited information: newly incorporated companies (2013)Company failure prediction wi…Credit scoring for microfinance: is it worth it? (2011)Credit scoring for microfinan…Reject inference in survival analysis by augmentation (2009)Reject inference in survival …Enterprise risk management: small business scorecard analysis (2009)Enterprise risk management: s…Credit scoring, augmentation and lean models (2005)Credit scoring, augmentation …The balanced scorecard : measures that drive performance (1992)Enterprise resource planning: A taxonomy of critical factors (2002)Alignment: Using the Balanced Scorecard to Create Corporate Synergies (2006)Analysis of SCOR’s approach to supply chain risk management (2014)Enterprise risk management in international construction firms: drivers and hindrances (2015)Effects of Firm Characteristics on Enterprise Risk Management: Case Study of Chinese Construction Firms Operating in Singapore (2016)Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)The Microfinance Revolution (2001)Basel Committee On Banking Supervision (2010)Is There a Trade-off between Financial Performance and Outreach in South Asian Microfinance Institutions? (2014)A social and environmental approach to microfinance credit scoring (2015)Does microfinance foster the development of its clients? A bibliometric analysis and systematic literature review (2022)An Overview of Consumer Data and Credit Reporting (2003)Changes in U.S. Family Finances from 2004 to 2007: Evidence from the Survey of Consumer Finances (2009)Changes in U.S. Family Finances from 2007 to 2010: Evidence from the Survey of Consumer Finances (2012)The Effects of the Massachusetts Health Reform on Household Financial Distress (2016)What Determines Consumer Financial Distress? Place- and Person-Based Factors (2020)Invisible Primes: Fintech Lending with Alternative Data (2021)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending (2012)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)A Novel Reject Inference Model Using Outlier Detection and Gradient Boosting Technique in Peer-to-Peer Lending (2019)Application of Instance-Based Entropy Fuzzy Support Vector Machine in Peer-To-Peer Lending Investment Decision (2019)Improving Credit Risk Prediction in Online Peer-to-Peer (P2P) Lending Using Feature selection with Deep learning (2019)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)Screening Peers Softly: Inferring the Quality of Small Borrowers (2015)Machine learning models for credit analysis improvements: Predicting low-income families’ default (2019)A conservative approach for online credit scoring (2021)An econometric analysis of the bank credit scoring problem (1989)A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers (2000)Predicting mortgage default using convolutional neural networks (2018)A CWGAN-GP-based multi-task learning model for consumer credit scoring (2022)Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art (2024)Sample selection bias in credit scoring models (2003)Recent developments in consumer credit risk assessment (2007)Reject inference in credit scoring using Semi-supervised Support Vector Machines (2017)Assessing and predicting small industrial enterprises’ credit ratings: A fuzzy decision-making approach (2022)Credit risk evaluation: a comprehensive study (2022)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Profit scoring for credit unions using the multilayer perceptron, XGBoost and TabNet algorithms: Evidence from Peru (2022)Cost-sensitive stacking ensemble learning for company financial distress prediction (2024)Credit scoring using multi-task Siamese neural network for improving prediction performance and stability (2024)A Coefficient of Agreement for Nominal Scales (1960)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)
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Cited by

  • 2011Credit scoring for microfinance: is it worth it?102 cited
  • 2009Enterprise risk management: small business scorecard analysis91 cited
  • 2018A new approach for reject inference in credit scoring using kernel-free fuzzy quadratic surface support vector machines63 cited
  • 2020Deep generative models for reject inference in credit scoring53 cited
  • 2016Credit Invisibles and the Unscored52 cited
  • 2018A rejection inference technique based on contrastive pessimistic likelihood estimation for P2P lending48 cited
  • 2020Cost-sensitive learning for profit-driven credit scoring45 cited
  • 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
  • 2019Using Bayesian networks to perform reject inference38 cited
  • 2013Company failure prediction with limited information: newly incorporated companies27 cited
  • 2009Reject inference in survival analysis by augmentation25 cited
  • 2005Credit scoring, augmentation and lean models23 cited
  • 2022A Framework of Global Credit-Scoring Modeling Using Outlier Detection and Machine Learning in a P2P Lending Platform

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21 cited
  • 2013Selection bias in credit scorecard evaluation21 cited
  • 2020A new approach in reject inference of using ensemble learning based on global semi-supervised framework20 cited