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A hierarchical attention-based feature selection and fusion method for credit risk assessment
13 references·0 citing·51 second hop
A hierarchical attention-based feature selection and fusion method for credit risk assessment (2024)A hierarchical attention-based feature se…Multi-view representation learning with Kolmogorov-Smirnov to predict default based on imbalanced and complex dataset (2022)Multi-view representation lea…Online peer-to-peer lending: A review of the literature (2021)Online peer-to-peer lending: …Mining Semantic Soft Factors for Credit Risk Evaluation in Peer-to-Peer Lending (2020)Mining Semantic Soft Factors …Machine learning techniques for credit risk evaluation: a systematic literature review (2020)Machine learning techniques f…Profit-based credit scoring based on robust optimization and feature selection (2019)Profit-based credit scoring b…A multi-objective approach for profit-driven feature selection in credit scoring (2019)A multi-objective approach fo…Credit Risk Analysis Using Machine and Deep Learning Models (2018)Credit Risk Analysis Using Ma…Cost-based feature selection for Support Vector Machines: An application in credit scoring (2017)Cost-based feature selection …Financial credit risk assessment: a recent review (2015)Financial credit risk assessm…Comparative study of classifier ensembles for cost-sensitive credit risk assessment (2015)Comparative study of classifi…Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending (2012)Judging Borrowers by the Comp…Credit Risk Management in Banks: Hard Information, Soft Information and Manipulation (2006)Credit Risk Management in Ban…Feature Selection for Financial Credit-Risk Evaluation Decisions (1999)Feature Selection for Financi…Property Rights and the Nature of the Firm (1990)Firms, Contracts, and Financial Structure (1995)Information Production and Capital Allocation: Decentralized versus Hierarchical Firms (2002)Financial distress cost of Italian small and medium enterprises (2017)Lending Technologies, Banking Relationships, and Firms’ Access to Credit in Italy: The Role of Firm Size (2017)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)Forecasting bank failures and stress testing: A machine learning approach (2018)Integration of unsupervised and supervised machine learning algorithms for credit risk assessment (2019)Multi-class misclassification cost matrix for credit ratings in peer-to-peer lending (2020)Credit Scoring and Its Applications (2002)The Credit Scoring Toolkit (2007)Development and application of consumer credit scoring models using profit-based classification measures (2014)A novel multi-stage hybrid model with enhanced multi-population niche genetic algorithm: An application in credit scoring (2018)A study on credit scoring modeling with different feature selection and machine learning approaches (2020)The Estimation of the Lorenz Curve and Gini Index (1972)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Consumer credit-risk models via machine-learning algorithms (2010)Bayesian regularized artificial neural networks for the estimation of the probability of default (2019)Deep learning for credit scoring: Do or don’t? (2021)Corporate finance risk prediction based on LightGBM (2022)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)A machine learning approach combining expert knowledge with genetic algorithms in feature selection for credit risk assessment (2021)A two-stage hybrid credit risk prediction model based on XGBoost and graph-based deep neural network (2022)Assessing credit risk of commercial customers using hybrid machine learning algorithms (2022)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Financial Distress Prediction and Feature Selection in Multiple Periods by Lassoing Unconstrained Distributed Lag Non-linear Models (2020)Credit Decision Support Based on Real Set of Cash Loans Using Integrated Machine Learning Algorithms (2021)What should lenders be more concerned about? Developing a profit-driven loan default prediction model (2022)To Explain or to Predict? (2010)Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China (2021)Default or profit scoring credit systems? 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(2019)Corporate financing and investment decisions when firms have information that investors do not have (1984)The Capital Structure Puzzle (1984)Using thematic analysis in psychology (2006)Global fintech trends and their impact on international business: a review (2023)Small businesses and FinTech: a systematic review and future directions (2023)AI integration in financial services: a systematic review of trends and regulatory challenges (2025)
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References

  • 2012Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending1,299 cited
  • 2018Credit Risk Analysis Using Machine and Deep Learning Models318 cited
  • 2015Financial credit risk assessment: a recent review234 cited
  • 2020Machine learning techniques for credit risk evaluation: a systematic literature review226 cited
  • 2017Cost-based feature selection for Support Vector Machines: An application in credit scoring155 cited
  • 2019A multi-objective approach for profit-driven feature selection in credit scoring141 cited
  • 2021Online peer-to-peer lending: A review of the literature126 cited
  • 2020Mining Semantic Soft Factors for Credit Risk Evaluation in Peer-to-Peer Lending107 cited
  • 2006Credit Risk Management in Banks: Hard Information, Soft Information and Manipulation43 cited
  • 2019Profit-based credit scoring based on robust optimization and feature selection39 cited
  • 1999Feature Selection for Financial Credit-Risk Evaluation Decisions35 cited
  • 2022Multi-view representation learning with Kolmogorov-Smirnov to predict default based on imbalanced and complex dataset25 cited
  • 2015Comparative study of classifier ensembles for cost-sensitive credit risk assessment21 cited

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