Determinant of Operational Risk

Size of bank

Size has been the most widely used explanatory variable to determine whether this variable have significant impact or not to the institutions. According to the studies from (Chernobai, Jorion & Yu 2011), (Kaspereit et al. 2017), (Dahen & Dionne 2010) and (Wang & Hsu 2013) found that size of bank has positive significant impact to operational risk events. This showed that as the size of the bank increase, the bank have to face more operational risk events. Although larger banks have better control management, they have to deal with larger scale of trades and complex transaction.

Therefore, these factors have led larger banks tend to expose more to operational risk events (Chernobai, Jorion & Yu 2011). The most proxy used to measure size of the bank is market value of equity and total asset.

Age of bank

Age of the bank is the number of years since a bank went public. The longer the year of the bank went public, the bank can be said to have establish a better risk management system.

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For this determinants, it showed that younger banks may face more operational risk than older banks because of their deficiencies in internal control systems and are less developed (Chernobai, Jorion & Yu 2011). Hence, there is significantly negative relationship between age of the banks and operational risk. The bank age variable is estimated by the number of months that the institution has been public.

Complexity of financial transactions

Industry experience suggest that complexity of financial transaction is positively correlated with operational risk.

(Abdymomunov & Ergen 2017) found in their analysis that the occurrence of operational losses are among larger and complex banks. Besides, (Chernobai, Jorion & Yu 2011) also found that the more complex the organizations, the higher the operational risk because they are more difficult to control and monitor. They used the number of operating and geographical segments to measure the complexity of the institutions.

MACROECONOMIC VARIABLES

Size of economy

Major proxy used to determine the operational risk for size of economy is Gross Domestic Product (GDP). GDP per capita is a measure of individual wealth within a country, According to (Cope, Piche & Walter 2012) larger economics will have larger transaction sizes. (Li & Moosa 2015) and (Moosa 2015) found that positive correlated between size of economy and operational risk because operational risk is related to the value of transaction which big losses are incurred by firms operating in big economics. The bigger the size of the economy the higher the operational losses will occur in that country.

State of economy

The economy situation of a country may be one of the contributory factors to operational risk. (Chernobai, Jorion & Yu 2011) in their studies found weaker results with respect to state of economy. They found that operational risk events were more frequent during economic downturns using GDP and disposable income growth as the proxy. In contrast to the study from (Dahen & Dionne 2010), they found that GDP have positive relationship with operational losses. In addition the fact for their result is that during economic downturns in which GDP is lower, the activities of banks may be limited, which reduces the probability of extreme losses.

Besides, there are studies using unemployment rate as proxy for the economic condition. They used unemployment rate as a proxy because most of the operational risk is associated with the failure of people and unemployment is about people (Moosa 2011). According to studies from (Moosa 2011), as the unemployment rate increase that implying a weak economy, the operational risk will increase. Meanwhile, (Hambuckers, Groll & Kneib 2018) also using unemployment rate as proxy but found different result which good economic faces with huge losses. In a booming economy, the size of the transactions increases and so does the potential amount of money to be lost in the case of failure of these transactions and also may create incentives to commit fraud.

GOVERNANCE RELATED VARIABLES

The connection between operational risk and corporate governance has also been recognized. This is simply because corporate governance is a control function in the monitoring of operations or may be defined formally as procedures and processes according to which an organization is directed and controlled (Li & Moosa 2015).

Internal governance

(Basel Committee on Banking Supervision 1998) highlighted that the importance of internal controls driven by the quality of corporate governance. If corporate governance is determinant of internal controls, it must be related to operational risk (Li & Moosa 2015). Hence, the board plays an important role in setting the organisation‘s strategy, high-level objectives and the allocation of resources (Young 2008a).

•  Number of board member

According to (Wang & Hsu 2013) larger board can help to generate more external resources to improve financial institution performance. They found that the size of board is negatively associated with operational risk events. This suggest that the larger the size of board the lower the possibility of operational risk events indicating that additional board member can contribute to knowledge development. However, they also found that too many of board member can also increase the operational risk events. This statement is in line with research from (Chernobai, Jorion & Yu 2011) found that larger board tends to have higher operational risk events.

•  Number of independent board member

(Chernobai, Jorion & Yu 2011) found negative relationship between number of independent board member and operational risk. Financial institution with more independent board member can increase the monitoring and internal control function hence reducing the operational risk events.

 External governance

G-index proxy is used to determine whether the external governance contribute to operational risk or not. (Chernobai, Jorion & Yu 2011) found that higher G-index which mean the financial institution has large number of antitakeover provision typically interpreted as an indicator of weaker external governance. This means that G-index is positively related to operational risk events.