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Classification Restricted Boltzmann Machine for comprehensible credit scoring model
6 references·16 citing·39 second hop
Classification Restricted Boltzmann Machine for comprehensible credit scoring model (2014)Classification Restricted Boltzmann Machi…Support vector machines for credit scoring and discovery of significant features (2008)Support vector machines for c…An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring (2008)An experimental comparison of…Recent developments in consumer credit risk assessment (2007)Recent developments in consum…Credit scoring with a data mining approach based on support vector machines (2006)Credit scoring with a data mi…Neural network credit scoring models (2000)Neural network credit scoring…Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Statistical Classification Me…Investigating the beneficial impact of segmentation-based modelling for credit scoring (2024)Investigating the beneficial …How can consumers without credit history benefit from the use of information processing and machine learning tools by financial institutions? (2024)How can consumers without cre…Intelligent credit scoring using deep learning methods (2023)Intelligent credit scoring us…Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods (2023)Consumer credit risk assessme…Emerging Trends in Deep Learning for Credit Scoring: A Review (2022)Emerging Trends in Deep Learn…A Deep Learning Approach for Credit Scoring Using Feature Embedded Transformer (2022)A Deep Learning Approach for …Bankruptcy prediction using fuzzy convolutional neural networks (2021)Bankruptcy prediction using f…Machine learning models and cost-sensitive decision trees for bond rating prediction (2019)Machine learning models and c…A Multicriteria Approach for Modeling Small Enterprise Credit Rating: Evidence from China (2019)A Multicriteria Approach for …A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction (2019)A chemical-reaction-optimizat…Generalized fuzzy soft sets theory‐based novel hybrid ensemble credit scoring model (2018)Generalized fuzzy soft sets t…A novel multi-objective particle swarm optimization for comprehensible credit scoring (2018)A novel multi-objective parti…A novel credit scoring model based on optimized random forest (2018)A novel credit scoring model …A hybrid interpretable credit card users default prediction model based on RIPPER (2018)A hybrid interpretable credit…Comparison of Deep Learning Algorithms to Predict Customer Churn within a Local Retail Industry (2017)Comparison of Deep Learning A…Demonstrating non-inferiority of easy interpretable methods for insolvency prediction (2015)Demonstrating non-inferiority…Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)An empirical comparison of conventional techniques, neural networks and the three stage hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) model for credit scoring analysis: The case of Turkish credit card data (2012)Financial credit risk assessment: a recent review (2015)A comparative study on base classifiers in ensemble methods for credit scoring (2016)What's In A Name? Malay Seals As Onomastic Sources (2018)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)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)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)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)Credit scoring using the clustered support vector machine (2014)A novel framework of credit risk feature selection for SMEs during industry 4.0 (2022)Financial performance evaluation by multi-criteria decision-making techniques (2022)SME default prediction: A systematic methodology-focused review (2023)Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning (2021)Loan default prediction using a credit rating-specific and multi-objective ensemble learning scheme (2023)The Cost of Capital, Corporation Finance and the Theory of Investment (1958)Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers (1986)Bankruptcy prediction using machine learning and Shapley additive explanations (2023)Artificial Intelligence Techniques for Bankruptcy Prediction of Tunisian Companies: An Application of Machine Learning and Deep Learning-Based Models (2024)Enhancing corporate governance through AI: a systematic literature review (2024)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Equality of Opportunity in Supervised Learning (2016)Machine Learning for Enhanced Credit Risk Assessment: An Empirical Approach (2023)Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management (2024)Domain adaptation-based multistage ensemble learning paradigm for credit risk evaluation (2025)A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems (2010)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Machine behaviour (2019)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)
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References

  • 1997Statistical Classification Methods in Consumer Credit Scoring: A Review1,039 cited
  • 2000Neural network credit scoring models1,032 cited
  • 2006Credit scoring with a data mining approach based on support vector machines805 cited
  • 2007Recent developments in consumer credit risk assessment472 cited
  • 2008Support vector machines for credit scoring and discovery of significant features336 cited
  • 2008An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring290 cited

Cited by

  • 2023Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods71 cited
  • 2019Machine learning models and cost-sensitive decision trees for bond rating prediction66 cited
  • 2021Bankruptcy prediction using fuzzy convolutional neural networks60 cited
  • 2019A Multicriteria Approach for Modeling Small Enterprise Credit Rating: Evidence from China56 cited
  • 2017Comparison of Deep Learning Algorithms to Predict Customer Churn within a Local Retail Industry51 cited
  • 2018A novel credit scoring model based on optimized random forest48 cited
  • 2022Emerging Trends in Deep Learning for Credit Scoring: A Review38 cited
  • 2019A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction

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38 cited
  • 2018Generalized fuzzy soft sets theory‐based novel hybrid ensemble credit scoring model37 cited
  • 2023Intelligent credit scoring using deep learning methods25 cited
  • 2015Demonstrating non-inferiority of easy interpretable methods for insolvency prediction24 cited
  • 2022A Deep Learning Approach for Credit Scoring Using Feature Embedded Transformer22 cited
  • 2024Investigating the beneficial impact of segmentation-based modelling for credit scoring20 cited
  • 2018A hybrid interpretable credit card users default prediction model based on RIPPER19 cited
  • 2018A novel multi-objective particle swarm optimization for comprehensible credit scoring18 cited
  • 2024How can consumers without credit history benefit from the use of information processing and machine learning tools by financial institutions?16 cited