Modeling Truncated Loss Data of Operational Risk in E-banking

Operational risk is an important risk component for financial institutions, especially in E-banking. Large amount of capital that are assigned to decrease this risk are evidence to this subject. One of the most important factors for modeling operational risk to estimate capital charge is loss data collections of banks. But sometimes for reasons like decreasing the costs, banks save only the losses above some determined thresholds at their database. For achieving accurate capital charge, this threshold should be considered in determining capital charge. This paper focuses on modeling truncated loss data above some given threshold. We discuss several statistical methods for modeling truncated data, and suggest the best one for modeling truncated loss data. We have tested our suggested model for some operational loss data samples. Our results indicate that our approach can be useful for increasing accuracy of estimating operational risk capital charge in E-banking.