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Recovery process optimization using survival regression

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  • Jiří Witzany
  • Anastasiia Kozina

Abstract

The goal of this paper is to propose, empirically test and compare different logistic and survival analysis techniques in order to optimize the debt collection process. This process uses various actions, such as phone calls, mails, visits, or legal steps to recover past due loans. We focus on the soft collection part, where the question is whether and when to call a past-due debtor with regard to the expected financial return of such an action. We propose using the survival analysis technique, in which the phone call can be compared to a medical treatment, and repayment to the recovery of a patient. We show on a real banking dataset that, unlike ordinary logistic regression, this model provides the expected results and can be efficiently used to optimize the soft collection process.

Suggested Citation

  • Jiří Witzany & Anastasiia Kozina, 2020. "Recovery process optimization using survival regression," FFA Working Papers 2.004, Prague University of Economics and Business, revised 16 Jul 2020.
  • Handle: RePEc:prg:jnlwps:v:2:y:2020:id:2.004
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    References listed on IDEAS

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    1. Mee Chi So & Christophe Mues & Adiel T. de Almeida Filho & Lyn C Thomas, 2019. "Debtor level collection operations using Bayesian dynamic programming," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(8), pages 1332-1348, August.
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    8. Maria Stepanova & Lyn Thomas, 2002. "Survival Analysis Methods for Personal Loan Data," Operations Research, INFORMS, vol. 50(2), pages 277-289, April.
    9. 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.
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    More about this item

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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