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Modelling repayment patterns in the collections process for unsecured consumer debt: A case studyAuthor-Name: Thomas, Lyn C

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  • Matuszyk, Anna
  • So, Mee Chi
  • Mues, Christophe
  • Moore, Angela

Abstract

One approach to modelling Loss Given Default (LGD), the percentage of the defaulted amount of a loan that a lender will eventually lose is to model the collections process. This is particularly relevant for unsecured consumer loans where LGD depends both on a defaulter's ability and willingness to repay and the lender's collection strategy. When repaying such defaulted loans, defaulters tend to oscillate between repayment sequences where the borrower is repaying every period and non-repayment sequences where the borrower is not repaying in any period. This paper develops two models – one a Markov chain approach and the other a hazard rate approach to model such payment patterns of debtors. It also looks at simplifications of the models where one assumes that after a few repayment and non-repayment sequences the parameters of the model are fixed for the remaining payment and non-payment sequences. One advantage of these approaches is that they show the impact of different write-off strategies. The models are applied to a real case study and the LGD for that portfolio is calculated under different write-off strategies and compared with the actual LGD results.

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  • Matuszyk, Anna & So, Mee Chi & Mues, Christophe & Moore, Angela, 2016. "Modelling repayment patterns in the collections process for unsecured consumer debt: A case studyAuthor-Name: Thomas, Lyn C," European Journal of Operational Research, Elsevier, vol. 249(2), pages 476-486.
    • Handle: RePEc:eee:ejores:v:249:y:2016:i:2:p:476-486
    DOI: 10.1016/j.ejor.2015.09.013
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    Cited by:

    1. Nazemi, Abdolreza & Rezazadeh, Hani & Fabozzi, Frank J. & Höchstötter, Markus, 2022. "Deep learning for modeling the collection rate for third-party buyers," International Journal of Forecasting, Elsevier, vol. 38(1), pages 240-252.
    2. Jiří Witzany & Anastasiia Kozina, 2022. "Recovery process optimization using survival regression," Operational Research, Springer, vol. 22(5), pages 5269-5296, November.
    3. Zanin, Luca, 2018. "Private monetary transfers between households: Who is helped and by whom?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 76-82.
    4. Arno Botha & Conrad Beyers & Pieter de Villiers, 2020. "The loss optimisation of loan recovery decision times using forecast cash flows," Papers 2010.05601, arXiv.org.
    5. Arno Botha & Conrad Beyers & Pieter de Villiers, 2020. "Simulation-based optimisation of the timing of loan recovery across different portfolios," Papers 2009.11064, arXiv.org, revised Apr 2021.
    6. Chen, Shou & Jiang, Xiangqian & He, Hongbo & Zhou, Xi, 2020. "A pricing model with dynamic repayment flows for guaranteed consumer loans," Economic Modelling, Elsevier, vol. 91(C), pages 1-11.

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