<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The purpose of this study is to estimate the future duration of a loan contract on the basis of several factors. The main methodology consists of a brief explanation of a survival analysis and a thorough application of a survival analysis in loan management. A real dataset from a credit institution (situated in Varna) is used. All contracts were signed for 30 days but some contracts were ended earlier, others - later. The main research question concerns the following statement. We may try to predict future loan duration by making an econometric model describing the dependency between the loan duration (as a dependent variable) and several independent variables. The dataset is analysed by calculating life tables, applying the Kaplan-Maier method and using Cox regression within SPSS. It is has been proved that the main covariates affecting loan duration are the variables: born in the region, month of birth and age. The formulated conclusions are valid for the analysed credit institution. This work provides a methodology for adapting duration models in credit institutions. The presented methodology (in this paper) may be applied over the dataset of other credit institutions (including banks) for loan duration prediction.</p></abstract>

The purpose of this study is to estimate the future duration of a loan contract on the basis of several factors. The main methodology consists of a brief explanation of a survival analysis and a thorough application of a survival analysis in loan management. A real dataset from a credit institution (situated in Varna) is used. All contracts were signed for 30 days but some contracts were ended earlier, others - later. The main research question concerns the following statement. We may try to predict future loan duration by making an econometric model describing the dependency between the loan duration (as a dependent variable) and several independent variables. The dataset is analysed by calculating life tables, applying the Kaplan-Maier method and using Cox regression within SPSS. It is has been proved that the main covariates affecting loan duration are the variables: born in the region, month of birth and age. The formulated conclusions are valid for the analysed credit institution. This work provides a methodology for adapting duration models in credit institutions. The presented methodology (in this paper) may be applied over the dataset of other credit institutions (including banks) for loan duration prediction.

Duration Models in Loan Management

Varna University of Economics Department of Informatics Knyaz Boris I, 77, Varna, Bulgaria

Folia Oeconomica Stetinensia

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Duration Models in Loan Management"}

The purpose of this study is to estimate the future duration of a loan contract on the basis of several factors. The main methodology consists of a brief...

Duration Models in Loan Management

Data publikacji: 30 gru 2015

Zakres stron: 114 - 126

Otrzymano: 05 sty 2015

Przyjęty: 27 kwi 2015

DOI: https://doi.org/10.1515/foli-2015-0027

Słowa kluczowe
survival analysis, SPSS, the Wilcoxon test, the Kaplan-Maier method, Cox regression

© University of Szczecin

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Duration Models in Loan Management

Data publikacji: 30 gru 2015

Zakres stron: 114 - 126

Otrzymano: 05 sty 2015

Przyjęty: 27 kwi 2015

DOI: https://doi.org/10.1515/foli-2015-0027

Słowa kluczowesurvival analysis, SPSS, the Wilcoxon test, the Kaplan-Maier method, Cox regression

© University of Szczecin

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
survival analysis, SPSS, the Wilcoxon test, the Kaplan-Maier method, Cox regression