Person: Pascual Ezama, David
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First Name
David
Last Name
Pascual Ezama
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Ciencias Económicas y Empresariales
Department
Administración Financiera y Contabilidad
Area
Economía Financiera y Contabilidad
Identifiers
5 results
Search Results
Now showing 1 - 5 of 5
Item Análisis de los factores de riesgo en el seguro de automóvil mediante ecuaciones estructurales(Innovar, 2015) Segovia Vargas, María Jesús; Camacho Miñano, María del Mar; Pascual Ezama, David; Tolmos Rodríguez-Piñero, PiedadLa gestión de riesgos, asociada al seguro del automóvil, es una cuestión crucial a la que se enfrentan en la actualidad tanto actuarios como profesionales del sector. Es clave seleccionar adecuadamente los factores de riesgos para asignar las tarifas a los asegurados en función del riesgo asociado. Por tanto, el objetivo de este trabajo es comprobar empíricamente la validez de la utilización de los niveles de “bonus-malus” para clasificar adecuadamente a los asegurados a través de dos modelos de ecuaciones estructurales. Los análisis sobre una muestra de 4.365 pólizas automovilísticas españolas descritas a través de 11 factores de riesgo muestran que la variable BM contribuye a mejorar la capacidad explicativa del modelo pero no de manera significativa.Item Explaining the causes of business failure using audit report disclosures(Journal of Business Research, 2019) Muñoz-Izquierdo, Nora; Segovia Vargas, María Jesús; Camacho Miñano, Juana María Del Mar; Pascual Ezama, DavidThis paper examines the ability of audit report disclosures to explain the causes of business failure. Despite incremental interest in organizational failure, much of the existing literature has used accounting ratios to foresee why firms fail. We hypothesise that the audit report can also be employed for this purpose because it provides information regarding any material uncertainty relating to events that may warn users about possible causes of business default. Using a matched sample of 808 failed and non-failed firms, our results suggest that audit report disclosures significantly explain the causes of business failure. Moreover, these findings are consistent with the results of studies that integrate both deterministic and voluntaristic perspectives into the examination of the antecedents of organizational failure, as disclosures about both external and internal factors are mentioned in the audit report and contribute to assessing default. Managers, auditors, regulators and other users may consider the audit report to be useful as a tool to anticipate business failure.Item Risk factor selection in automobile insurance policies: a way to improve the bottom line of insurance companies(Revista Brasileira de Gestao de Negocios, 2015) Segovia Vargas, María Jesús; Camacho Miñano, María del Mar; Pascual Ezama, DavidThe objective of this paper is to test the validity of using 'bonus-malus' (BM) levels to classify policyholders satisfactorily. In order to achieve the proposed objective and to show empirical evidence, an artificial intelligence method, Rough Set theory, has been employed. The empirical evidence shows that common risk factors employed by insurance companies are good explanatory variables for classifying car policyholders' policies. In addition, the BM level variable slightly increases the explanatory power of the a priori risks factors.Item Which characteristics predict the survival of insolvent firms? An SME reorganization prediction model(Journal of Small Business Management, 2015) Camacho Miñano, María del Mar; Segovia Vargas, María Jesús; Pascual Ezama, DavidThe negative impact of insolvency, especially in small and medium enterprises, informs the objective of this paper: to study the characteristics of bankrupt firms to achieve a preventive diagnosis for reorganization by means of artificial intelligence (AI) methodologies such as rough set and PART methods. The AI models obtained show not only the key variables to predict insolvency, but also their relations and the critical values. Using only five firm characteristics (sector, size, number of shareholdings, return on assets, and cash ratio), our model could reduce delays and costs, since it is able to predict which firms will undergo reorganization or liquidation before the legal procedure.Item Is the External Audit Report Useful for Bankruptcy Prediction? Evidence Using Artificial Intelligence(International Journal of Financial Studies, 2019) Muñoz Izquierdo, Nora; Camacho Miñano, María del Mar; Segovia Vargas, María Jesús; Pascual Ezama, DavidDespite the number of studies on bankruptcy prediction using financial ratios, very little is known about how external audit information can contribute to anticipating financial distress. A handful of papers have shown that a combination of ratios and audit data is significant for predictive purposes, but only one recent paper provided a predictive accuracy of 80% solely by using the disclosures contained in audit reports. This study was complemented by simplifying the analysis of audit reports for prediction purposes and the same predictive accuracy was achieved. By applying three artificial intelligence techniques (PART algorithm, random forest, and support vector machine), the predictive ability of more easily extracted information from the report was examined and a practical implication suggested for each user. Simply by (1) finding the audit opinion, (2) identifying if a matter section exists, and (3) the number of comments disclosed, any user may predict a bankruptcy situation with the same accuracy as if they had scrutinized the whole report. In addition, an extended literature review is included, on previous studies on the interaction between bankruptcy prediction and the external audit information.