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

José Francisco Martínez-Sáncheza; María Teresa V. Martínez-Palaciosa; Francisco Venegas-Martínez

doi:10.1016/j.estger.2016.06.004

Authors

José Francisco Martínez-Sáncheza Profesor-Investigador, Escuela Superior de Apan, Universidad Autónoma del Estado de Hidalgo, Apan, Mexico
María Teresa V. Martínez-Palaciosa Profesor-Investigador, Escuela Superior de Apan, Universidad Autónoma del Estado de Hidalgo, Apan, Mexico
Francisco Venegas-Martínez Profesor-Investigador, Escuela Superior de Economía, Instituto Politécnico Nacional, México D.F., Mexico

DOI:

https://doi.org/10.1016/j.estger.2016.06.004

Keywords:

Operational risk, Bayesian analysis, Monte Carlo simulation

Abstract

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.

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