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| Main Author: | |
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| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidad ESAN
2017
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| Subjects: | |
| Online Access: | https://www.redalyc.org/articulo.oa?id=360752107002 https://www.redalyc.org/journal/3607/360752107002/ https://www.redalyc.org/journal/3607/360752107002/html/ https://www.redalyc.org/journal/3607/360752107002/360752107002.epub https://www.redalyc.org/journal/3607/360752107002/movil |
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Table of Contents:
- Using a naive Bayesian classifier methodology for loan risk assessment. Evidence from a Tunisian commercial bank Aida Krichene Multidisciplinarias (Ciencias Sociales) ROC curve Default risk Banking sector Risk assessment Bayesian classi fi er algorithm Purpose – Loan default risk or credit risk evaluation is important to fi nancial institutions which provide loans to businesses and individuals. Loans carry the risk of being defaulted. To understand the risk levels of credit users (corporations and individuals), credit providers (bankers) normally collect vast amounts of information on borrowers. Statistical predictive analytic techniques can be used to analyse or to determine the risk levels involved in loans. This paper aims to address the question of default prediction of short-term loans for a Tunisian commercial bank. Design/methodology/approach – The authors have used a database of 924 fi les of credits granted to industrial Tunisian companies by a commercial bank in the years 2003, 2004, 2005 and 2006. The naive Bayesian classi fi er algorithm was used, and the results show that the good classi fi cation rate is of the order of 63.85 per cent. The default probability is explained by the variables measuring working capital, leverage, solvency, pro fi tability and cash fl ow indicators. Findings – The results of the validation test show that the good classi fi cation rate is of the order of 58.66 per cent; nevertheless, the error types I and II remain relatively high at 42.42 and 40.47 per cent, respectively. A receiver operating characteristic curve is plotted to evaluate the performance of the model. The result shows that the area under the curve criterion is of the order of 69 per cent. Originality/value – The paper highlights the fact that the Tunisian central bank obliged all commercial banks to conduct a survey study to collect qualitative data for better credit notation of the borrowers. 2017 artículo científico 2077-1886 https://www.redalyc.org/articulo.oa?id=360752107002 https://www.redalyc.org/journal/3607/360752107002/ https://www.redalyc.org/journal/3607/360752107002/html/ https://www.redalyc.org/journal/3607/360752107002/360752107002.epub https://www.redalyc.org/journal/3607/360752107002/movil en http://www.redalyc.org/revista.oa?id=3607 Journal of Economics, Finance and Administrative Science application/pdf Universidad ESAN Journal of Economics, Finance and Administrative Science (Perú) Num.42 Vol.22