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Assessing naïve Bayes as a method for screening credit applicants
8 references·7 citing·40 second hop
Assessing naïve Bayes as a method for screening credit applicants (2009)Assessing naïve Bayes as a method for scr…Good practice in retail credit scorecard assessment (2005)Good practice in retail credi…Credit scoring and rejected instances reassigning through evolutionary computation techniques (2003)Credit scoring and rejected i…Credit Scoring and Its Applications (2002)Credit Scoring and Its Applic…Modelling consumer credit risk (2001)Modelling consumer credit riskCredit scoring using neural and evolutionary techniques (2000)Credit scoring using neural a…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 k-Nearest-Neighbour Classifier for Assessing Consumer Credit Risk (1996)A k-Nearest-Neighbour Classif…Best practices for responsible machine learning in credit scoring (2025)Best practices for responsibl…Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art (2024)Advancing credit risk modelli…A recent review on optimisation methods applied to credit scoring models (2023)A recent review on optimisati…Machine Learning Fairness is Computationally Difficult and Algorithmically Unsatisfactorily Solved (2021)Machine Learning Fairness is …Ten-year evolution on credit risk research: a systematic literature review approach and discussion (2020)Ten-year evolution on credit …Business Bankruptcy Prediction Based on Survival Analysis Approach (2014)Business Bankruptcy Predictio…An application of locally linear model tree algorithm with combination of feature selection in credit scoring (2013)An application of locally lin…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)Credit scoring with a data mining approach based on support vector machines (2006)A comparative assessment of ensemble learning for credit scoring (2010)Neural Networks: A New Tool for Predicting Thrift Failures* (1992)Neural network credit scoring models (2000)Hybrid mining approach in the design of credit scoring models (2005)An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring (2007)Credit rating by hybrid machine learning techniques (2009)A comparison of neural networks and linear scoring models in the credit union environment (1996)Credit-scoring models in the credit-union environment using neural networks and genetic algorithms (1997)A survey of the issues in consumer credit modelling research (2005)A credit scoring model for Vietnam's retail banking market (2007)A literature review on the application of evolutionary computing to credit scoring (2012)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Forecasting Bankruptcy More Accurately: A Simple Hazard Model (2001)Applying Survival Analysis to Telecom Churn Data (2019)On logit and artificial neural networks in corporate distress modelling for Zimbabwe listed corporates (2022)Exploring the effects of urban rail on the survival of nearby businesses (2025)A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior (1980)PREDICTING BANKRUPTCY FOR FIRMS IN FINANCIAL DISTRESS (1990)A comparative study on base classifiers in ensemble methods for credit scoring (2016)Predicting and Deterring Default with Social Media Information in Peer-to-Peer Lending (2017)Machine learning techniques for credit risk evaluation: a systematic literature review (2020)The journal coverage of Web of Science and Scopus: a comparative analysis (2015)Equality of Opportunity in Supervised Learning (2016)Guidance on Conducting a Systematic Literature Review (2017)Recent developments in consumer credit risk assessment (2007)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects (2021)Credit scoring for profitability objectives (2009)Classification methods applied to credit scoring: Systematic review and overall comparison (2016)Approaches for credit scorecard calibration: An empirical analysis (2017)Time will tell: behavioural scoring and the dynamics of consumer credit assessment (2001)The impact of sample bias on consumer credit scoring performance and profitability (2005)The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients (2008)Consumer credit-risk models via machine-learning algorithms (2010)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)
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References

  • 1997Statistical Classification Methods in Consumer Credit Scoring: A Review1,039 cited
  • 2000A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers744 cited
  • 2002Credit Scoring and Its Applications669 cited
  • 1996A k-Nearest-Neighbour Classifier for Assessing Consumer Credit Risk286 cited
  • 2003Credit scoring and rejected instances reassigning through evolutionary computation techniques226 cited
  • 2000Credit scoring using neural and evolutionary techniques151 cited
  • 2005Good practice in retail credit scorecard assessment117 cited
  • 2001Modelling consumer credit risk76 cited

Cited by

  • 2024Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art42 cited
  • 2014Business Bankruptcy Prediction Based on Survival Analysis Approach37 cited
  • 2023A recent review on optimisation methods applied to credit scoring models20 cited
  • 2013An application of locally linear model tree algorithm with combination of feature selection in credit scoring17 cited
  • 2020Ten-year evolution on credit risk research: a systematic literature review approach and discussion16 cited
  • 2025Best practices for responsible machine learning in credit scoring13 cited

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  • 2021Machine Learning Fairness is Computationally Difficult and Algorithmically Unsatisfactorily Solved13 cited