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Time to default in credit scoring using survival analysis: a benchmark study

Author

Listed:
  • Lore Dirick

    (KU Leuven
    KU Leuven)

  • Gerda Claeskens

    (KU Leuven
    KU Leuven)

  • Bart Baesens

    (KU Leuven
    KU Leuven
    University of Southampton)

Abstract

We investigate the performance of various survival analysis techniques applied to ten actual credit data sets from Belgian and UK financial institutions. In the comparison we consider classical survival analysis techniques, namely the accelerated failure time models and Cox proportional hazards regression models, as well as Cox proportional hazards regression models with splines in the hazard function. Mixture cure models for single and multiple events were more recently introduced in the credit risk context. The performance of these models is evaluated using both a statistical evaluation and an economic approach through the use of annuity theory. It is found that spline-based methods and the single event mixture cure model perform well in the credit risk context.

Suggested Citation

  • Lore Dirick & Gerda Claeskens & Bart Baesens, 2017. "Time to default in credit scoring using survival analysis: a benchmark study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 652-665, June.
  • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:6:d:10.1057_s41274-016-0128-9
    DOI: 10.1057/s41274-016-0128-9
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    Cited by:

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    2. Alvaro Arroyo & Alvaro Cartea & Fernando Moreno-Pino & Stefan Zohren, 2023. "Deep Attentive Survival Analysis in Limit Order Books: Estimating Fill Probabilities with Convolutional-Transformers," Papers 2306.05479, arXiv.org.
    3. 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.
    4. Hao Wang & Anthony Bellotti & Rong Qu & Ruibin Bai, 2024. "Discrete-Time Survival Models with Neural Networks for Age–Period–Cohort Analysis of Credit Risk," Risks, MDPI, vol. 12(2), pages 1-26, February.
    5. Born, Alexander & Kovachka, Nikoleta & Lessmann, Stefan & Seow, Hsin-Vonn, 2018. "Price Management in the Used-Car Market: An Evaluation of Survival Analysis," IRTG 1792 Discussion Papers 2018-065, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Yan, Xiaodong & Wang, Hongni & Wang, Wei & Xie, Jinhan & Ren, Yanyan & Wang, Xinjun, 2021. "Optimal model averaging forecasting in high-dimensional survival analysis," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1147-1155.
    7. Zhao Wang & Cuiqing Jiang & Huimin Zhao, 2022. "Know Where to Invest: Platform Risk Evaluation in Online Lending," Information Systems Research, INFORMS, vol. 33(3), pages 765-783, September.
    8. Bátiz-Zuk Enrique & Mohamed Abdulkadir & Sánchez-Cajal Fátima, 2021. "Exploring the sources of loan default clustering using survival analysis with frailty," Working Papers 2021-14, Banco de México.
    9. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
    10. Dirick, Lore & Claeskens, Gerda & Vasnev, Andrey & Baesens, Bart, 2022. "A hierarchical mixture cure model with unobserved heterogeneity for credit risk," Econometrics and Statistics, Elsevier, vol. 22(C), pages 39-55.
    11. Jackson P. Lautier & Vladimir Pozdnyakov & Jun Yan, 2022. "On the Convergence of Credit Risk in Current Consumer Automobile Loans," Papers 2211.09176, arXiv.org, revised Jan 2024.
    12. Hung Xuan Do & Daniel Rösch & Harald Scheule, 2020. "Liquidity Constraints, Home Equity and Residential Mortgage Losses," The Journal of Real Estate Finance and Economics, Springer, vol. 61(2), pages 208-246, August.
    13. Bocchio, Cecilia & Crook, Jonathan & Andreeva, Galina, 2023. "The impact of macroeconomic scenarios on recurrent delinquency: A stress testing framework of multi-state models for mortgages," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1655-1677.
    14. Caselli, Stefano & Corbetta, Guido & Cucinelli, Doriana & Rossolini, Monica, 2021. "A survival analysis of public guaranteed loans: Does financial intermediary matter?," Journal of Financial Stability, Elsevier, vol. 54(C).
    15. Bátiz-Zuk Enrique & González-Holden Alexa, 2023. "Identifying Gender Disparities on the Time to Repay Microfinance Group Loans: Evidence from Mexico," Working Papers 2023-07, Banco de México.
    16. Wycinka Ewa & Jurkiewicz Tomasz, 2019. "Survival Regression Models For Single Events And Competing Risks Based On Pseudo-Observations," Statistics in Transition New Series, Polish Statistical Association, vol. 20(1), pages 171-188, March.

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