Introduction
Evolving globalization trends have significantly contributed to major changes in the fields of business and economics. The effect of recent technological advances is evident as well, with banks becoming more dependent on online systems. As a result of accidents and faults in the mentioned systems, unplanned events eventually cause financial loss or reduced earnings for banks, also known as risks (Leo et al., 2019). Risks can be categorized into several types according to their causes and financial consequences, including business, reputational, and operational risks (Leo et al., 2019). Specifically, operational risks have been poorly researched, which resulted in multiple financial crises. Analyzing the top operational risk to banks is crucial for successful bank management and regulation of new businesses.
Causes of Possible Operational Risks
To highlight the most important operational risk, the general concepts of risk origin must be reviewed. Operational risks can be defined as risks of loss due to failed internal processes, people, or systems (Leo et al., 2019). The process deals with fraud, cyber safety, employee productivity, and technological factors (Leo et al., 2019). Hence, the risks are generally caused by poorly managed bank routines. Research into the financial crises of the decade outlined the critical role of organized strategies in minimizing risks in financial institutions (Aloqab et al., 2018). The institution’s staff’s ability to resolve issues under stressful circumstances is another element related to risk management.
Additionally, technical issues and internal process failures contribute to eventual operational risks. Modern technology is required to predict risks and analyze the existing operational indicators (Aloqab et al., 2018). Otherwise, the bank staff becomes very limited in resources to resolve the issues efficiently. Moreover, internal and external frauds have become one of the leading causes of operational risk development (Leo et al., 2019). Therefore, constant system failures and inadequate employee response to possible crisis threats constitute the leading causes of the issue.
Examples of Possible Operational Risks
As a result of the mentioned factors accumulating over time, the operational risks can be expressed in various disadvantageous forms. These forms are essentially linked to the outlined causes, yet the former is more focused on the consequences of inadequate system regulation skills. In this way, one example of the operational risk and its consequences can be viewed from the bankruptcy of the Barings Bank, which initially lost over one billion dollars over individual negligence (Aloqab et al., 2018). The instance emphasized the detrimental consequences of an action caused by a single employee.
On the other hand, the detection of fraud and cyber security threats objectively leads to banking system issues. Several institutions possess mechanisms that allow them to track suspicious transactions and procedures (Leo et al., 2019). While the implementation of progressive technologies allows for better management of potential risks, the quality and budget for the tools can become a limiting factor for non-government-based organizations. Moreover, credit card fraud has resulted in millions of dollars worth of loss for banks in recent years (Leo et al., 2019). Once again, the fraud process is monitored internally and occurs in the case of deficient management conditions.
Highlighting the Top Operational Risk
Various forms of operational risks to banks have been reviewed to focus on the most detrimental ones finally. Separating the risks into two major categories of objective and subjective factors aids in determining the top influential one. Individual human errors are often unintentional and random, meaning discussing methods of reducing such errors would be counter-productive. On the contrary, technologies based on online mechanisms play a more prominent role in modern risk management procedures and include more controllable risk factors. For example, more and more banks rely on computer systems to calculate big data sets and moderate internal processes, the latter being human-controlled in the past (Zhang et al., 2020). Therefore, any threat to the accessibility and efficiency of the machines is far more damaging to a financial institution than an employee error. Propositions regarding ways of avoiding the risks can be drawn to present the ideal technologies to filter through data daily. In this way, the top operational risk might be handled through innovative strategies.
Discussion of Risk Reduction Methods
The key strategies for managing operational risks in banks include implementing high-quality technology. For example, many researchers suggest machine learning as a tool to extract valuable information from large data sets (Leo et al., 2019). In financial institutions, the tool’s main function is to analyze data from client interactions, consumer applications and other external sources (Leo et al., 2019). Additionally, the machine learning system is applicable in preventing and assessing potential risks. In this way, machine learning allows banks to handle business-threatening elements with minimal error probability.
Other methods of reducing operational risks include procedures being regulated by employees. Risk sharing refers to the process of relying on insurance policies for further assistance (Aloqab et al., 2018). To avoid any type of risk, most banks are recommended to prioritize not gaining anything over major losses. Of course, this method is not relevant for cases that determine the overall success rate of an institution (Aloqab et al., 2018). To accurately assess the situation, machine learning tools can be applied. Having a backup plan, in any case, is just as essential as the initial proposition, and both should integrate machine and employee skills to different extents. Hence, it is wiser to reject a complicated offer and use technologies for the calculations rather than risk a great loss.
Conclusion
The main operational risks include internal and external fraud, systematic failures, employee errors, and cyber security issues. The consequences of operational risks range from minor losses to bankruptcy. It has been determined that technology-related risks require more attention due to the significant role they play in reducing risks. On the other hand, human errors are unpredictable and random, so attempting to prevent them would be counter-productive. Due to the potential risks involved, modern technological tools must be implemented to ensure accurate predictions and data assessments. Insurance policies and detailed risk assessments have also been identified as additional methods. Finally, financial institutions must specifically target operational risks for management to prevent other types of risks from developing.
References
Aloqab, A., Alobaidi, F., & Raweh, B. (2018). Operational risk management in financial institutions: An overview. Business and Economic Research, 8(2), 10-32. Web.
Leo, M., Sharma, S., & Maddulety, K. (2019). Machine learning in banking risk management: A literature review. Risks, 7(1), 29. Web.
Zhang, C., Zhang, T., & Tan, T. (2020). Internationalization of Chinese banks: How to strengthen and enhance overseas operations and management. Advances in Economics, Business and Management Research, 126, 144-150.