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Joint modeling: an application in behavioural scoring

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  • Wenbin Hu
  • Junzi Zhou

Abstract

Survival analysis has become an appealing approach in credit scoring. It is able to readily incorporate time-dependent covariates and dynamically predict the survival probability. However, the difference between endogenous and exogenous covariates is ignored in the existing extended Cox models in behavioural scoring. In this paper, we apply joint modelling framework, which can be seen as an extension of survival analysis, to overcome such deficiency of survival models. We carefully design experiments on two datasets and verify the superiority of joint modelling over the extend Cox model through cross validation on dynamic discrimination and calibration performance measures. The experimental results indicate that the joint model performance is better, especially in the calibration measure. The key reason for the better performance is discussed and illustrated.

Suggested Citation

  • Wenbin Hu & Junzi Zhou, 2019. "Joint modeling: an application in behavioural scoring," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(7), pages 1129-1139, July.
    • Handle: RePEc:taf:tjorxx:v:70:y:2019:i:7:p:1129-1139
    DOI: 10.1080/01605682.2018.1487821
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    Cited by:

    1. 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.
    2. 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.
    3. Pascal Kundig & Fabio Sigrist, 2024. "A Spatio-Temporal Machine Learning Model for Mortgage Credit Risk: Default Probabilities and Loan Portfolios," Papers 2410.02846, arXiv.org.
    4. Victor Medina-Olivares & Finn Lindgren & Raffaella Calabrese & Jonathan Crook, 2023. "Joint model for longitudinal and spatio-temporal survival data," Papers 2311.04008, arXiv.org.

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