POT model for operational risk: Experience with the analysis of the data collected from Chinese commercial banks

•Using statistical method, it summarizes the characteristics of operational risk in Chinese commercial banks;•Using POT model, it finds the optimal threshold, calculates the VaR and ES and compares them at different confidence level.•It finds internal fraud is the main type of operational risk and explains its reason from behavioral finance.

This paper takes 533 operational risk loss events publicly announced by Chinese commercial banks in the period of 1995-2012 as the sample, using Peaks over Threshold (POT) model to quantify the operational risk. The statistical data classification indicates the internal fraud is the main type of operational risk in Chinese commercial banks. This paper explains its causes from the perspective of behavioral finance. The results are as follows: first, Chinese commercial banks' operational risk loss events show an upward trend, then downward trend beginning in 2003 and currently an upward trend again; second, through the empirical analysis, this paper simulates the extreme value distribution function, finds the optimal threshold, and calculates the VaR and ES of the operational risk of Chinese commercial banks and compare them at different confidence levels; and third, in view of behavioral finance theory, overconfidence and loss aversion contribute to high internal fraud incidence.