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Predicting Consumer Default: A Deep Learning Approach

Citations

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Cited by:

  1. Eccles, Peter & Grout, Paul & Siciliani, Paolo & Zalewska, Anna, 2021. "The impact of machine learning and big data on credit markets," Bank of England working papers 930, Bank of England.
  2. Luca Barbaglia & Sebastiano Manzan & Elisa Tosetti, 2023. "Forecasting Loan Default in Europe with Machine Learning," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 569-596.
  3. Andrés Alonso & José Manuel Carbó, 2022. "Accuracy of explanations of machine learning models for credit decisions," Working Papers 2222, Banco de España.
  4. Jessica LaVoice & Domonkos F. Vamossy, 2019. "Racial Disparities in Debt Collection," Papers 1910.02570, arXiv.org, revised Jun 2023.
  5. Nicola Branzoli & Ilaria Supino, 2020. "FinTech credit: a critical review of empirical research," Questioni di Economia e Finanza (Occasional Papers) 549, Bank of Italy, Economic Research and International Relations Area.
  6. Vamossy, Domonkos F., 2021. "Investor emotions and earnings announcements," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
  7. Giacomo De Giorgi & Costanza Naguib, 2022. "Life after Default: Credit Hardship and its Effects," Diskussionsschriften dp2206, Universitaet Bern, Departement Volkswirtschaft.
  8. Paritosh Navinchandra Jha & Marco Cucculelli, 2021. "A New Model Averaging Approach in Predicting Credit Risk Default," Risks, MDPI, vol. 9(6), pages 1-15, June.
  9. Van Loo, Ellen J. & Caputo, Vincenzina & Lusk, Jayson L., 2020. "Consumer preferences for farm-raised meat, lab-grown meat, and plant-based meat alternatives: Does information or brand matter?," Food Policy, Elsevier, vol. 95(C).
  10. Agnese Carella & Federica Ciocchetta & Valentina Michelangeli & Federico Maria Signoretti, 2020. "What can we learn about mortgage supply from online data?," Questioni di Economia e Finanza (Occasional Papers) 583, Bank of Italy, Economic Research and International Relations Area.
  11. Andrés Alonso & José Manuel Carbó, 2021. "Understanding the performance of machine learning models to predict credit default: a novel approach for supervisory evaluation," Working Papers 2105, Banco de España.
  12. Michael Karpe, 2020. "An overall view of key problems in algorithmic trading and recent progress," Papers 2006.05515, arXiv.org.
  13. Mirko Moscatelli & Simone Narizzano & Fabio Parlapiano & Gianluca Viggiano, 2019. "Corporate default forecasting with machine learning," Temi di discussione (Economic working papers) 1256, Bank of Italy, Economic Research and International Relations Area.
  14. Bastien Lextrait, 2021. "Scaling up SME's credit scoring scope with LightGBM," EconomiX Working Papers 2021-25, University of Paris Nanterre, EconomiX.
  15. Giacomo De Giorgi & Matthew Harding & Gabriel Vasconcelos, 2021. "Predicting Mortality from Credit Reports," Papers 2111.03662, arXiv.org.
  16. Ajitha Kumari Vijayappan Nair Biju & Ann Susan Thomas & J Thasneem, 2024. "Examining the research taxonomy of artificial intelligence, deep learning & machine learning in the financial sphere—a bibliometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 849-878, February.
  17. Domonkos F. Vamossy, 2023. "Social Media Emotions and IPO Returns," Papers 2306.12602, arXiv.org, revised Apr 2024.
  18. Vitaly Meursault & Daniel Moulton & Larry Santucci & Nathan Schor, 2022. "One Threshold Doesn’t Fit All: Tailoring Machine Learning Predictions of Consumer Default for Lower-Income Areas," Working Papers 22-39, Federal Reserve Bank of Philadelphia.
  19. Nigmonov, Asror & Shams, Syed & Alam, Khorshed, 2022. "Macroeconomic determinants of loan defaults: Evidence from the U.S. peer-to-peer lending market," Research in International Business and Finance, Elsevier, vol. 59(C).
  20. Oskar Kowalewski & Pawel Pisany & Emil Slazak, 2021. "What determines cross-country differences in fintech and bigtech credit markets?," Working Papers 2021-ACF-02, IESEG School of Management.
  21. Costa, Luciano da F., 2022. "On similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
  22. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
  23. Giacomo De Giorgi & Costanza Naguib, 2023. "Life after (Soft) Default," Papers 2306.00574, arXiv.org.
  24. Kowalewski, Oskar & Pisany, Paweł & Ślązak, Emil, 2022. "Digitalization and data, institutional quality and culture as drivers of technology-based credit providers," Journal of Economics and Business, Elsevier, vol. 121(C).
  25. Nicola Branzoli & Edoardo Rainone & Ilaria Supino, 2023. "The role of banks' technology adoption in credit markets during the pandemic," Temi di discussione (Economic working papers) 1406, Bank of Italy, Economic Research and International Relations Area.
  26. Adebayo Oshingbesan & Eniola Ajiboye & Peruth Kamashazi & Timothy Mbaka, 2022. "Model-Free Reinforcement Learning for Asset Allocation," Papers 2209.10458, arXiv.org.
  27. Dimitrios Nikolaidis & Michalis Doumpos, 2022. "Credit Scoring with Drift Adaptation Using Local Regions of Competence," SN Operations Research Forum, Springer, vol. 3(4), pages 1-28, December.
  28. Magdalena Brygała, 2022. "Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data," Risks, MDPI, vol. 10(2), pages 1-13, January.
  29. Domonkos F. Vamossy & Rolf Skog, 2021. "EmTract: Extracting Emotions from Social Media," Papers 2112.03868, arXiv.org, revised Jun 2023.
  30. Fraisse, Henri & Laporte, Matthias, 2022. "Return on investment on artificial intelligence: The case of bank capital requirement," Journal of Banking & Finance, Elsevier, vol. 138(C).
  31. Alessandro Bitetto & Stefano Filomeni & Michele Modina, 2021. "Understanding corporate default using Random Forest: The role of accounting and market information," DEM Working Papers Series 205, University of Pavia, Department of Economics and Management.
  32. Alonso-Robisco, Andrés & Carbó, José Manuel, 2022. "Can machine learning models save capital for banks? Evidence from a Spanish credit portfolio," International Review of Financial Analysis, Elsevier, vol. 84(C).
  33. Andrés Alonso Robisco & José Manuel Carbó Martínez, 2022. "Measuring the model risk-adjusted performance of machine learning algorithms in credit default prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-35, December.
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