Aportaciones metodológicas para luchar contra el fraude: un reto multidisciplinar

Autores/as

DOI:

https://doi.org/10.3145/thinkepi.2018.60

Palabras clave:

Fraude financiero, Técnicas cientí­ficas, Detección, Multidisciplinar, Triángulo del fraude.

Resumen

Estado de la cuestión sobre métodos cientí­ficos utilizados contra el fraude financiero, principalmente de tipo técnico (informáticos, económicos, matemáticos). Aunque algunas de las áreas cientí­ficas involucradas no están relacionadas con la tecnologí­a -por ejemplo, la sociologí­a-, es importante insistir en que todas ellas proporcionan herramientas útiles para detectar el fraude. La detección y prevención del fraude financiero es una tarea multidisciplinar, por lo que la solución a este problema de urgente actualidad deberán aportarla equipos multidisciplinares.

Citas

Abdullahi, Rabi´u; Mansor, Noorhayati (2015). "Fraud triangle theory and fraud diamond theory. Understanding the convergent and divergent for future research". International journal of Academic Research in Accounting, Finance and Management Sciences, v. 5, n. 4, pp. 38-45. http://www.iiste.org/Journals/index.php/EJBM/article/viewFile/26274/26919

Dorminey, Jack; Fleming, A. Scott; Kranacher, Mary-Jo; Riley, Richard A. Jr. (2012). "The evolution of fraud theory". Issues in accounting education, v. 27, n. 2, pp. 555-579. https://doi.org/10.2308/iace-50131

Mock, Theodore; Srivastava, Rajendra; Wright, Arnold M. (2017). "Fraud risk assessment using the fraud risk model as a decision aid". Journal of emerging technologies in accounting, v. 14, n. 1, pp. 37-56. https://doi.org/10.2308/jeta-51724

Naruedomkul, Pornchai; Rodwanna, Pannipa; Wonglimpiyarat, Jarunee (2010). "Organization frauds in Thailand: A survey on risk factors". International journal of criminal justice sciences, v. 5, n. 1, pp. 203-219. https://goo.gl/Zb2rkq

Ngai, Eric W.T.; Hu, Yong; Wong, Y. H.; Chen, Yijun; Sun, Xin (2011). "The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature". Decision support systems, v. 50, n. 3, pp. 559-569. https://doi.org/10.1016/j.dss.2010.08.006

Richhariya, Pankaj; Singh, Prashant (2012). "A survey on financial fraud detection methodologies". International journal of computer applications, v. 45, n. 22, pp. 975-1007.

https://goo.gl/EZAuuu

Szárnyas, Gábor; Koovári, Zsolt; Salánki, Ágnes; Varró, Dániel (2016). "Towards the characterization of realistic models: Evaluation of multidisciplinary graph metrics". In: Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems, pp. 87-94. https://inf.mit.bme.hu/sites/default/files/publications/models2016-metrics.pdf

Trompeter, Gregory M.; Carpenter, Tina D.; Jones, Keith L.; Riley, Richard A. Jr. (2014). "Insights for research and practice: What we learn about fraud from other disciplines". Accounting horizons, v. 28, n. 4, pp. 769-804. https://doi.org/10.2308/acch-50816

West, Jarrod; Bhattacharya, Maumita (2016). "Intelligent financial fraud detection: a comprehensive review". Computers & security, v. 57, pp. 47-66. https://doi.org/10.1016/j.cose.2015.09.005

Wilks, T. Jeffrey; Zimbelman, Mark F. (2004). "Using game theory and strategic reasoning concepts to prevent and detect fraud". Accounting horizons, v. 18, n. 3, pp. 173-184. https://doi.org/10.2308/acch.2004.18.3.173

Zhao, Jie; Lau, Raymond Y.K.; Zhang, Wenping; Zhang, Kaihang; Chen, Xu; Tang, Deyu (2016). "Extracting and reasoning about implicit behavioral evidences for detecting fraudulent online transactions in e-Commerce". Decision support systems, v. 86, pp. 109-121. https://doi.org/10.1016/j.dss.2016.04.003

Descargas

Publicado

2018-04-26

Cómo citar

Ferrer-Sapena, A., & Sánchez-Pérez, E. A. (2018). Aportaciones metodológicas para luchar contra el fraude: un reto multidisciplinar. Anuario ThinkEPI, 12, 356–360. https://doi.org/10.3145/thinkepi.2018.60

Número

Sección

F. Tecnologí­as de información: normativa y gestión de información