Search results

Loan default risk or credit risk evaluation is important to financial 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.

The authors have used a database of 924 files of credits granted to industrial Tunisian companies by a commercial bank in the years 2003, 2004, 2005 and 2006. The naive Bayesian classifier algorithm was used, and the results show that the good classification rate is of the order of 63.85 per cent. The default probability is explained by the variables measuring working capital, leverage, solvency, profitability and cash flow indicators.

The results of the validation test show that the good classification 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.

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.

El riesgo de incumplimiento de préstamos o la evaluación del riesgo de crédito es importante para las instituciones financieras que otorgan préstamos a empresas e individuos. Existe el riesgo de que el pago de préstamos no se cumpla. Para entender los niveles de riesgo de los usuarios de crédito (corporaciones e individuos), los proveedores de crédito (banqueros) normalmente recogen gran cantidad de información sobre los prestatarios. Las técnicas analíticas predictivas estadísticas pueden utilizarse para analizar o determinar los niveles de riesgo involucrados en los préstamos. En este artículo abordamos la cuestión de la predicción por defecto de los préstamos a corto plazo para un banco comercial tunecino.

Utilizamos una base de datos de 924 archivos de créditos concedidos a empresas industriales tunecinas por un banco comercial en 2003, 2004, 2005 y 2006. El algoritmo bayesiano de clasificadores se llevó a cabo y los resultados muestran que la tasa de clasificación buena es del orden del 63.85%. La probabilidad de incumplimiento se explica por las variables que miden el capital de trabajo, el apalancamiento, la solvencia, la rentabilidad y los indicadores de flujo de efectivo.

Los resultados de la prueba de validación muestran que la buena tasa de clasificación es del orden de 58.66% ; sin embargo, los errores tipo I y II permanecen relativamente altos, siendo de 42.42% y 40.47%, respectivamente. Se traza una curva ROC para evaluar el rendimiento del modelo. El resultado muestra que el criterio de área bajo curva (AUC, por sus siglas en inglés) es del orden del 69%.

El documento destaca el hecho de que el Banco Central tunecino obligó a todas las entidades del sector llevar a cabo un estudio de encuesta para recopilar datos cualitativos para un mejor registro de crédito de los prestatarios.

Curva ROC, Evaluación de riesgos, Riesgo de incumplimiento, Sector bancario, Algoritmo clasificador bayesiano.

Artículo de investigación

The purpose of this study is to understand how internal auditors perceive the internal audit quality and to highlight the different profiles of internal auditors based on their perception of internal audit quality determinants.

The authors’ methodological approach is based on the submission of a self-administered questionnaire. The final sample consists of 104 internal auditors. The first stage of the study is in the lead of a certified public accountants (CPA), which highlights seven factors of the internal audit quality. The second step is a confirmatory factor analysis (CFA) that allowed the authors to validate the model proposed by the CPA. Finally, the authors carry out a typological analysis of the auditors according to their way of perceiving the factors extracted by the CPA.

The authors’ model, validated by the CFA, shows that the knowledge of the internal auditor, the independence of reporting, compliance with professional standards of internal audit, the relationship with the external auditor, the personal relationship of the internal auditor, the access to information and the field of intervention of the internal auditor have a positive association with the internal audit quality but with a different degree of significance. For example, the field of intervention of the internal auditor and the access to information explain better the internal audit quality. However, the knowledge of the internal auditor and the relationship with the external auditor are not significant to explain the internal audit quality. From the hierarchical cluster analysis, four groups of internal auditors emerged: the autonomous, the perfectionists, the rigorous ones and the objectives.

In offering these findings, the paper contributes to the existing internal audit literature by introducing evidence from an emerging country, namely, Tunisia, of the internal audit quality model. In addition, the authors proposed a new measure to the internal audit quality model which is the use of the work of the internal auditor by the external auditor. This study is also interesting to managers and professional internal audit organizations in recognizing the characteristics of the quality of the internal audit and advance reflections on the effectiveness of internal audit practices. The authors’ study proposes a typology of certified internal auditors through their perceptions of the quality of the internal audit while taking into account the specificities of the Tunisian audit market. This provides insights to managers and audit committees on the measures necessary to ensure the relevance of the internal audit work within their companies.