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Time varying and dynamic models for default risk in consumer loans

Citations

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Cited by:

  1. Djeundje, Viani Biatat & Crook, Jonathan, 2019. "Dynamic survival models with varying coefficients for credit risks," European Journal of Operational Research, Elsevier, vol. 275(1), pages 319-333.
  2. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
  3. Zhiyong Li & Xinyi Hu & Ke Li & Fanyin Zhou & Feng Shen, 2020. "Inferring the outcomes of rejected loans: an application of semisupervised clustering," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 631-654, February.
  4. Medina-Olivares, Victor & Calabrese, Raffaella & Crook, Jonathan & Lindgren, Finn, 2023. "Joint models for longitudinal and discrete survival data in credit scoring," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1457-1473.
  5. Do, Hung Xuan & Rösch, Daniel & Scheule, Harald, 2018. "Predicting loss severities for residential mortgage loans: A three-step selection approach," European Journal of Operational Research, Elsevier, vol. 270(1), pages 246-259.
  6. Medina-Olivares, Victor & Lindgren, Finn & Calabrese, Raffaella & Crook, Jonathan, 2023. "Joint models of multivariate longitudinal outcomes and discrete survival data with INLA: An application to credit repayment behaviour," European Journal of Operational Research, Elsevier, vol. 310(2), pages 860-873.
  7. Li, Aimin & Li, Zhiyong & Bellotti, Anthony, 2023. "Predicting loss given default of unsecured consumer loans with time-varying survival scores," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
  8. Oliver Blümke, 2020. "Estimating the probability of default for no‐default and low‐default portfolios," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(1), pages 89-107, January.
  9. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
  10. Jobst, Rainer & Kellner, Ralf & Rösch, Daniel, 2020. "Bayesian loss given default estimation for European sovereign bonds," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1073-1091.
  11. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
  12. Hon, Pak Shun & Bellotti, Tony, 2016. "Models and forecasts of credit card balance," European Journal of Operational Research, Elsevier, vol. 249(2), pages 498-505.
  13. Dendramis, Y. & Tzavalis, E. & Varthalitis, P. & Athanasiou, E., 2020. "Predicting default risk under asymmetric binary link functions," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1039-1056.
  14. Bellotti, Tony & Crook, Jonathan, 2011. "Forecasting and Stress Testing Credit Card Default Using Dynamic Models," Working Papers 11-34, University of Pennsylvania, Wharton School, Weiss Center.
  15. Medina-Olivares, Victor & Lindgren, Finn & Calabrese, Raffaella & Crook, Jonathan, 2025. "Joint model for longitudinal and spatio-temporal survival data," European Journal of Operational Research, Elsevier, vol. 327(3), pages 892-904.
  16. Arno Botha & Tanja Verster & Roelinde Bester, 2024. "The TruEnd-procedure: Treating trailing zero-valued balances in credit data," Papers 2404.17008, arXiv.org, revised Nov 2025.
  17. Jiří Witzany & Anastasiia Kozina, 2022. "Recovery process optimization using survival regression," Operational Research, Springer, vol. 22(5), pages 5269-5296, November.
  18. Douw Gerbrand Breed & Niel van Jaarsveld & Carsten Gerken & Tanja Verster & Helgard Raubenheimer, 2021. "Development of an Impairment Point in Time Probability of Default Model for Revolving Retail Credit Products: South African Case Study," Risks, MDPI, vol. 9(11), pages 1-22, November.
  19. Bellotti, Tony & Crook, Jonathan, 2013. "Forecasting and stress testing credit card default using dynamic models," International Journal of Forecasting, Elsevier, vol. 29(4), pages 563-574.
  20. Martin Hauptfleisch, 2019. "Financial Decision-Making Using Data," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 6-2019, January-A.
  21. Victor Medina-Olivares & Finn Lindgren & Raffaella Calabrese & Jonathan Crook, 2023. "Joint model for longitudinal and spatio-temporal survival data," Papers 2311.04008, arXiv.org.
  22. Fernando F. Moreira, 2010. "Copula‐Based Formulas to Estimate Unexpected Credit Losses (The Future of Basel Accords?)," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 19(5), pages 381-404, December.
  23. Divino, Jose Angelo & Rocha, Líneke Clementino Sleegers, 2013. "Probability of default in collateralized credit operations," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 276-292.
  24. Bernd Engelmann & Ha Pham, 2020. "A Raroc Valuation Scheme for Loans and Its Application in Loan Origination," Risks, MDPI, vol. 8(2), pages 1-20, June.
  25. Arno Botha & Tanja Verster & Roland Breedt, 2025. "Modelling the term-structure of default risk under IFRS 9 within a multistate regression framework," Papers 2502.14479, arXiv.org, revised Apr 2026.
  26. Thamayanthi Chellathurai, 2017. "Probability Density Of Recovery Rate Given Default Of A Firm’S Debt And Its Constituent Tranches," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-34, June.
  27. Cho, Yongbok & Lee, Yongwoong, 2022. "Asymmetric asset correlation in credit portfolios," Finance Research Letters, Elsevier, vol. 49(C).
  28. Dendramis, Y. & Tzavalis, E. & Adraktas, G., 2018. "Credit risk modelling under recessionary and financially distressed conditions," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 160-175.
  29. Arno Botha & Tanja Verster, 2025. "Approaches for modelling the term-structure of default risk under IFRS 9: A tutorial using discrete-time survival analysis," Papers 2507.15441, arXiv.org, revised Dec 2025.
  30. Arno Botha & Esmerelda Oberholzer & Janette Larney & Riaan de Jongh, 2023. "Defining and comparing SICR-events for classifying impaired loans under IFRS 9," Papers 2303.03080, arXiv.org, revised Feb 2025.
  31. Leow, Mindy & Crook, Jonathan, 2014. "Intensity models and transition probabilities for credit card loan delinquencies," European Journal of Operational Research, Elsevier, vol. 236(2), pages 685-694.
  32. Partha Sengupta & Christopher H. Wheeler, 2024. "Credit card loss forecasting: Some lessons from COVID," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2448-2477, November.
  33. Maria Rocha Sousa & João Gama & Elísio Brandão, 2013. "Introducing time-changing economics into credit scoring," FEP Working Papers 513, Universidade do Porto, Faculdade de Economia do Porto.
  34. Chrysovalantis Gaganis & Panagiota Papadimitri & Fotios Pasiouras & Menelaos Tasiou, 2023. "Social traits and credit card default: a two-stage prediction framework," Annals of Operations Research, Springer, vol. 325(2), pages 1231-1253, June.
  35. Arno Botha & Tanja Verster & Bernard Scheepers, 2025. "Exploring different subtypes of recurrent event Cox-regression models in modelling lifetime default risk: A tutorial," Papers 2505.01044, arXiv.org, revised Jan 2026.
  36. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2016. "Accuracy of mortgage portfolio risk forecasts during financial crises," European Journal of Operational Research, Elsevier, vol. 249(2), pages 440-456.
  37. Allen, D.E. & Powell, R.J. & Singh, A.K., 2016. "Take it to the limit: Innovative CVaR applications to extreme credit risk measurement," European Journal of Operational Research, Elsevier, vol. 249(2), pages 465-475.
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