An analysis on operational risk in international banking: A Bayesian approach (2007–2011)

• Autores: José Francisco Martínez Sánchez , María Teresa V. Martínez Palacios, Francisco Venegas Martínez
• Localización: Estudios Gerenciales: Journal of Management and Economics for Iberoamerica, ISSN 0123-5923, Vol. 32, Nº. 140, 2016, págs. 208-220
• Idioma: inglés
• DOI: 10.1016/j.estger.2016.06.004
• Enlaces
  • Texto completo (pdf)
• Dialnet Métricas: 4 Citas
• Resumen

  • This study aims to develop a Bayesian methodology to identify, quantify and measure operational risk in several business lines of commercial banking. To do this, a Bayesian network (BN) model is designed with prior and subsequent distributions to estimate the frequency and severity. Regarding the subsequent distributions, an inference procedure for the maximum expected loss, for a period of 20 days, is carried out by using the Monte Carlo simulation method. The business lines analyzed are marketing and sales, retail banking and private banking, which all together accounted for 88.5% of the losses in 2011. Data was obtained for the period 2007–2011 from the Riskdata Operational Exchange Association (ORX), and external data was provided from qualified experts to complete the missing records or to improve its poor quality.

• Referencias bibliográficas
  • Citas Aquaro, V., Bardoscia, M., Belloti, R., Consiglio, A., De Carlo, F., & Ferri, G. (2009). A Bayesian networks approach to operational...
  • Alexander, C. (2002). Operational risk measurement: Advanced approaches. UK: ISMA Centre. University of Reading. Retrieved from: http://www.dofin.ase.ro/Lectures/Alexander%20Carol/Oprisk...
  • Artzner, P., Delbaen, F., Eber, J., & Heath, D. (1999). Coherent measures of risk. Mathematical Finance, 9(3), 203–228.
  • Basel II. (2001a). Operational risk. Consultative document. Retrieved from: https://www.bis.org/publ/bcbsca07.pdf
  • Basel II. (2001b). Working paper on the regulatory treatment of operational risk. Retrieved from: http://www.bis.org/publ/bcbswp8.pdf
  • Carrillo-Menéndez, S., & Suárez-González, A. (2015). Challenges in operational risk modelling. In International Model Risk Management...
  • Carrillo-Menéndez, S., Marhuenda-Menéndez, M., & Suárez-González, A. (2007). El entorno AMA (Advanced Model Approach). Los datos y su...
  • Cowell, R., Dawid, G., Lauritzen, A. P., & Spiegelhalter, D. J. (1999). Probabilistic networks and expert systems. Berlin: Springer-Verlag.
  • Cruz, M. G. (2002). Modeling, measuring and hedging operational risk. In Series Wiley Finance. West Sussex, UK: John Wiley & Sons.
  • Cruz, M. G., Peters, G. W., & Shevchenko, P. V. (2002). Fundamental aspects of operational risk and insurance analytics: A handbook of...
  • Degen, M., Embrechts, P., & Lambrigger, D. (2007). The quantitative modeling of operational risk: Between g-and-h and EVT. Switzerland:...
  • Embrechts, P., Furrer, H., & Kaufmann, O. (2003). Quantifying regulatory capital for operational risk. Derivatives Use, Trading and Regulation,...
  • Ferguson, T. S. (1973). A Bayesian analysis of some nonparametric problems. Annals of Statistics, 2(4), 615–629.
  • Guo, H., & Hsu, W. (2002). A survey of algorithms for real-time Bayesian network inference. In Join Workshop on Real Time Decision Support...
  • Heinrich, G. (2006). Riesgo operacional, pagos, sistemas de pago y aplicación de Basilea II en América Latina: evolución más reciente. Boletín...
  • Jensen, F. V. (1996). An introduction to Bayesian networks (1st ed.). London: UCL Press.
  • Kartik, A., & Reimer, K. (2007). Phase transitions in operational risk. Physical Review E, 75(1 part 2), 1–14.
  • Lauritzen, S. L., & Spiegelhalter, D. J. (1988). Local computations with probabilities on graphical structures and their application to...
  • Moscadelli, M. (2004). The modelling of operational risk: Experience with the analysis of the data collected by the Basel committee. Bank...
  • Neil, M., Marquez, D., & Fenton, N. (2004). Bayesian networks to model expected and unexpected operational losses. Risk Analysis, 25(4),...
  • Panjer, H. (2006). Operational risk. Modeling analytics (1st ed.). Hoboken, NJ: Wiley- Interscience.
  • Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (first edition). San Francisco, CA, USA:...
  • Pearl, J. (2000). Causality, models, reasoning, and inference. London: Cambridge University Press.
  • Reimer, K., & Neu, P. (2003). Functional correlation approach to operational risk in banking organizations. Physica A: Statistical Mechanics...
  • Reimer, K., & Neu, P. (2002). Adequate capital and stress testing for operational risks. Physical Review E, 75(1), 016111.
  • Supatgiat, C., Kenyon, C., & Heusler, L. (2006). Cause-to-effect operational risk quantification and management. Risk Management, 8(1),...
  • Venegas-Martínez, F. (2006). Riesgos financieros y económicos. Productos derivados y decisiones económicas bajo incertidumbre (1a. Ed.). México...
  • Zellner, A. (1971). An Introduction to Bayesian inference in econometrics. New York: Wiley.