Case—Quantifying Operational Risk in Financial Institutions

Modelling Operational Risk in Financial Institutions using HDBNs

This paper describes the use of Hybrid Dynamic Bayesian Networks (HDBNs) to model the operational risk faced by financial institutions in terms of economic capital. It describes a methodology for modelling financial losses resulting from intentional or accidental events and characterises these by their ability to evade controls and ultimately lead to increasingly severe financial consequences. ...

Board composition and operational risk events of financial institutions

We investigate the relation between board composition and operational risk events of financial institutions in the period from 1996 to 2010. Drawing from corporate governance literature, we consider the impact of board characteristics on the likelihood of operational risk events. Overall, our findings suggest that board size is negatively and non-linearly associated with the possibility of oper...

Reputational Effects of Operational Risk Events for Financial Institutions

This paper aims at measuring reputational effects for financial institutions by examining a firm’s stock price reaction to the announcement of particular operational loss events such as internal frauds. We conduct at this purpose an event study analysis of the impact of operational loss events on the market values of banks and insurance companies, using the OpVar database (OpData dataset suppli...

Risk Measurement for Financial Institutions

Operational risk management in financial institutions: Process assessment in concordance with Basel II

The improvement of banks’ operational risk management frameworks concerns new requirements addressed in the Basel II Framework, a new capital adequacy regulation proposed by the Basel Committee on Banking Supervision (BCBS). Basel II will apply to internationally active banks and to all banks and investment firms in the EU via transposition of a new Directive into national regulations. By doing...