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Machine learning and artificial neural networks to construct P2P lending credit-scoring model: A case using Lending Club data
13 references·5 citing·51 second hop
Machine learning and artificial neural networks to construct P2P lending credit-scoring model: A case using Lending Club data (2022)Machine learning and artificial neural ne…Financial system modeling using deep neural networks (DNNs) for effective risk assessment and prediction (2019)Financial system modeling usi…The use of profit scoring as an alternative to credit scoring systems in peer-to-peer (P2P) lending (2016)The use of profit scoring as …Predicting Credit Risk in Peer-to-Peer Lending: A Neural Network Approach (2015)Predicting Credit Risk in Pee…Determinants of Default in P2P Lending (2015)Determinants of Default in P2…The failure of models that predict failure: Distance, incentives, and defaults (2014)The failure of models that pr…Anatomy of the credit score (2011)Anatomy of the credit scoreScreening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending? (2010)Screening in New Credit Marke…Group Membership, Relationship Banking and Loan Default Risk: The Case of Online Social Lending (2008)Group Membership, Relationshi…Neural network survival analysis for personal loan data (2005)Neural network survival analy…Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Benchmarking state-of-the-art…A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers (2000)A survey of credit and behavi…Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Financial Ratios and the Prob…Warren S. McCulloch and Walter Pitts. A logical calculus of the ideas immanent in nervous activity. Bulletin of mathematical biophysics, vol. 5 (1943), pp. 115–133. (1944)Warren S. 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References

  • 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy6,005 cited
  • 2003Benchmarking state-of-the-art classification algorithms for credit scoring903 cited
  • 2000A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers744 cited
  • 2014The failure of models that predict failure: Distance, incentives, and defaults497 cited
  • 2015Determinants of Default in P2P Lending327 cited
  • 2016The use of profit scoring as an alternative to credit scoring systems in peer-to-peer (P2P) lending253 cited
  • 2015Predicting Credit Risk in Peer-to-Peer Lending: A Neural Network Approach152 cited
  • 2010Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending?150 cited
  • 2005Neural network survival analysis for personal loan data145 cited
  • 2008Group Membership, Relationship Banking and Loan Default Risk: The Case of Online Social Lending109 cited
  • 2019Financial system modeling using deep neural networks (DNNs) for effective risk assessment and prediction94 cited
  • 2011Anatomy of the credit score78 cited
  • 1944Warren S. McCulloch and Walter Pitts. A logical calculus of the ideas immanent in nervous activity. Bulletin of mathematical biophysics, vol. 5 (1943), pp. 115–133.55 cited

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  • 2024

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Enhancing transparency and fairness in automated credit decisions: an explainable novel hybrid machine learning approach
41 cited
  • 2024Ensemble-Based Machine Learning Algorithm for Loan Default Risk Prediction32 cited
  • 2024Performance Evaluation of Hybrid Machine Learning Algorithms for Online Lending Credit Risk Prediction23 cited
  • 2025A dynamic financial risk prediction system for enterprises based on gradient boosting decision tree algorithm21 cited
  • 2024Profit-sensitive machine learning classification with explanations in credit risk: The case of small businesses in peer-to-peer lending20 cited