Survival analysis as a methodological alternative to estimate probabilities of default of corporate credit debtors and large companies in Peru

Authors

  • Fátima Uriarte Cáceres Universidad Nacional Mayor de San Marcos. Lima, Perú.
  • Ysela Agüero Palacios Universidad Nacional Mayor de San Marcos, Dpto. de Estadística. Lima, Perú.

DOI:

https://doi.org/10.15381/idata.v20i1.13486

Keywords:

survival analysis, Cox proportional hazards model, probability of default

Abstract

The calculation of probabilities of default can be improved by incorporating additional variables that can be predicted and which are associated with changes in the debtors' financial situation and the economic situation. The inclusion of these variables is possible through the use of survival analysis. In the present paper, an application of the Cox proportional hazards model is performed to identify some explanatory variables of the risk of default of new corporate credit debtors and large companies. The characteristics of the debtor (economic sector, indebtedness, profitability, size of the company); credit (initial loan, percentage in foreign currency, percentage of guarantees); together with entity grouping and business confidence index were identified as risk factors for non-compliance in the payment of corporate and large companies loans.

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Published

2017-07-24

Issue

Vol. 20 No. 1 (2017)

Section

Producción y Gestión

License

Copyright (c) 2017 Fátima Uriarte Cáceres, Ysela Agüero Palacios

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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c. Authors retain theirs right to make a subsequent publication of their work, to use the article or any part thereof (eg a compilation of his papers, lecture notes, thesis, or a book), always indicating the source of publication (the originator of the work, journal, volume, number and date).

How to Cite

Survival analysis as a methodological alternative to estimate probabilities of default of corporate credit debtors and large companies in Peru. (2017). Industrial Data, 20(1), 7-16. https://doi.org/10.15381/idata.v20i1.13486