The cycle of our articles described key risk indicators for banks according to the European Central Bank’s assessment. In previous article we spoke about business process management and the way to automate it. We also tried to analyze Eurozone banks’ cost structures and how Business Rules Management Systems (BRMS) can help enhance business models of banks and improve their resilience and sustainability.
Taking into consideration the risks mentioned above, we can conclude that risk management in banking is an issue by itself. Prevention and prediction is a far wiser option than dealing with negative effects and consequences. That’s why banking risk management becomes one of the top priority tasks.
Risk is an inherent characteristic of financial institutions and banking organizations. In this article, we will explain why Risk Management is important for banking institutions.
Types of risks in finance business
A bank in its day-to-day activity faces different types of risks. All of them need to be managed very carefully. Expected or unexpected events in the economy or the financial markets arise different types of risks in banking.
Risks can also come from staff oversight or illegal intention, which causes erosion in the values of assets thus leading to a reduction in the bank’s integral value.
Fig. 1. Types of risks in finance
There are two major types of risks in finance namely:
- Systemic Risks
- Unsystematic Risks
Let us define these two types of risks and understand the concept behind them.
Systematic risk is caused by the external factors’ influence on an organization. Such factors are normally uncontrollable. It is a macro in nature because it affects a large number of financial organizations and cannot be planned.
Unsystematic risk, on the contrary, occurs due to the influence of internal factors prevailing within a bank. Such factors are normally controllable from a financial organization’s point of view. Unsystematic risk is micro in nature and has an impact only on a particular financial organization. It can be planned and predicted. That’s why necessary actions can be taken by the organization to mitigate the risk.
Though the sources of systematic and unsystematic risks are of different nature, both types of risks can be predicted. Consequently, banks can develop a set of actions to mitigate the negative effects and minimize losses. And sophisticated and smart risk management software solutions can swiftly choose what scenario to unfold.
No one can give a ready-made blueprint of how to mitigate banking risks in the future or predict all upcoming disruptions. But modern fundamental trends suggest that banks can take some initiatives now to achieve short-term results while preparing for the coming changes. Banking institutions are to establish a reliable and comprehensive risk management system, integrated in all business processes to form a bank’s risk profile which is always in line with the established risk tendencies.
A risk management system should comprise:
- Risk management strategy together with procedures for risk identification and measurement.
- Appropriate bank’s organizational structure.
- Effective and efficient risk management process which covers risks the bank is exposed to or maybe potentially exposed.
- Sufficient internal controls system.
- Appropriate information system.
- Proper process of assessment of internal capital adequacy.
Risk management solutions. Mitigate banking risks wisely
The latest global study on risk management done by Dun & Bradstreet indicates that global digital transformation in the banking and finance sector covers all business areas and business processes. The future of the banking sector requires the application of smart tools and technology in risk management, customer communication, or commercial and marketing management, among others via modern enterprise risk management solution implementation.
In Fig. 2 you can see what digital transformation solutions are used by leading companies for data processing to manage risk in their organizations.
Fig. 2. Technology in risk management
Technological innovations continuously emerge, enabling new techniques for managing risks thus promoting digital transformation in financial services and helping banking organizations make better risk decisions at a lower cost. Big data, crowdsourcing, Artificial Intelligence (AI) and machine learning (ML) in finance illustrate the potential impact.
How machine learning in finance leads to the digital transformation strategy
Risk management systems based on AI and machine learning algorithms will have to reinvent themselves and become drivers of digital transformation in business. How banks navigate the risks and opportunities presented by technological innovations will dictate their ability to thrive.
Artificial intelligence will create new liabilities for organizations, but it can also be used as a powerful risk management tool. With its help, risk managers can process high volumes of data and get a better understanding of the risks they face, spend less time on routine and repetitive tasks, and use connected devices to enhance their risk management processes.AI can enhance the processing of structured and unstructured data and can be used to look for patterns in large amounts of data to determine the value of critical assets, among other things.
AI is a “cognitive technology” that extends and improves processes like thinking, learning, and predicting and embeds them in networked machines. The technology is often freely available today from major developers such as Google, IBM, and Microsoft. That’s why start-up companies are just as able to disrupt industries as large, cash-rich organizations.
The Conclusion
Perhaps one of the most essential challenges that banking risk managers face is knowing what can be controlled and prioritized for protection. It is impossible for the function to protect everything, but the focus should be on preparation and planning. That is how risk managers can deal with their sphere of control.
The potential for technology to improve risk management processes is exciting. But finance leaders will need to prepare for this transformation, and experts believe there’s much work to be done. And financial organizations should rapidly sense and respond to opportunities in the AI-enabled landscape.
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