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How to identify early defaults in online lending: A cost-sensitive multi-layer learning framework
16 references·5 citing·41 second hop
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References

  • 2015Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research1,277 cited
  • 2003Benchmarking state-of-the-art classification algorithms for credit scoring903 cited
  • 2017A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring770 cited
  • 1996A comparison of neural networks and linear scoring models in the credit union environment522 cited
  • 2014Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending495 cited
  • 2007Recent developments in consumer credit risk assessment472 cited
  • 2015Instance-based credit risk assessment for investment decisions in P2P lending313 cited
  • 2017Credit Scoring and Its Applications306 cited
  • 2008An experimental comparison of ensemble of classifiers for bankruptcy prediction and credit scoring290 cited
  • 2016The use of profit scoring as an alternative to credit scoring systems in peer-to-peer (P2P) lending253 cited
  • 2011Two credit scoring models based on dual strategy ensemble trees244 cited
  • 2008Credit scoring with macroeconomic variables using survival analysis232 cited
  • 2019Two-stage consumer credit risk modelling using heterogeneous ensemble learning182 cited
  • 2017Loan default prediction by combining soft information extracted from descriptive text in online peer-to-peer lending

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180 cited
  • 2020Three-stage reject inference learning framework for credit scoring using unsupervised transfer learning and three-way decision theory120 cited
  • 2015A Data-Driven Approach to Predict Default Risk of Loan for Online Peer-to-Peer (P2P) Lending78 cited
  • Cited by

    • 2024Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art42 cited
    • 2024Cost-sensitive stacking ensemble learning for company financial distress prediction34 cited
    • 2022A credit scoring model based on the Myers–Briggs type indicator in online peer-to-peer lending20 cited
    • 2023A recent review on optimisation methods applied to credit scoring models20 cited
    • 2023A new hybrid credit scoring ensemble model with feature enhancement and soft voting weight optimization18 cited