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

Francisco Venegas-Martínez, José Francisco Martínez-Sánchez and María Teresa Verónica Palacios

Estudios Gerenciales, 2016, vol. 32, issue 140, 208-220

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.

Keywords: Operational risk; Bayesian analysis; Monte Carlo simulation (search for similar items in EconPapers)
JEL-codes: C11 C15 D81 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:col:000129:015179

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