Bank Risk Management Technology for The 4 Biggest Bank’s Risks
Bank risk management technology is an umbrella term for many different tools and technologies that help banks to manage and mitigate risks. The fundamental nature of different risks requires a completely different set of tools, which is why you will often see products and solutions dedicated to only one type of risk.
This means that different types of risks are being impacted very differently by advances in technology. A review of the 4 primary types of risks banks contend with, we will shed light on how the implementation of technology is evolving in different banking sectors and departments.
Liquidity risks directly impact a bank’s ability to achieve profit goals, which is why it is highly managed and prioritized. Liquidity risks are also unique among risks because it represents one of the first domains where technology made inroads into the banking sector. Spreadsheets proved to be the perfect way to store and track financial information. This early adoption of technology has resulted in liquidity risk management solutions being more mature than risk solutions for most other types of bank risks.
Why liquidity risks were easier to tackle from a technological perspective
Liquidity risks are not easier to manage with technology because they are important; they are easier to manage due to their quantifiable nature. Whenever we try to tackle any problem through technology the first step is to break down the problem into pieces which technology can understand. There was no need to do this with liquidity risks – liquidity risks are tracked by keeping track of the financial records of the bank. This means that all the data is already in numbers and computers are excellently suited to store and analyze quantifiable data.
The second most important factor in solving any problem through technology is gathering the data that the computing system requires to perform the analysis and give an output. Here too, it is easy to tackle the problem of liquidity risks. The data required to predict and manage liquidity risks is already present in a standardized form in every bank because the data is necessary for the operations of the bank. Thus, there was no reason to create any technology or a mechanism to collect the data that would be required.
Risk technology enables new possibilities with liquidity through real time analysis. Key risk indicators – metrics that directly or indirectly affect risks – can be tracked in real-time and help banks detect emerging risks. Instead of waiting for reports, the executive members of the bank and managers can instantly detect any liquidity related issues. Combining internal liquidity data with external market data in real-time enables banks to gain new risk insights and understand market factors and risks before their competition and thus make decisions which allows them to succeed in dominating their chosen markets.
Operational risks proved to be a much tougher problem to solve than liquidity risks because these risks largely revolve around the actions of employees and businesses instead of data or numbers. Operational risks arise when there is a process that may be violating a regulation or compliance requirement and increasing the overall risk exposure of the organization. We cannot keep a track of all the actions taken by all employees in an organization in real-time , which is why banks have struggled a lot in minimizing these risks. However, if we centralized operational risk management so that all operational risk related actions were recorded under a central platform, we can track these actions and detect problems instantly.
Operational risk management is currently one of the most exciting avenues in bank risk management technology. The tech industry has taken the challenges posed by operational risks and have come up with many different solutions. The most successful strategy currently being used is to streamline and automate as many parts of operational risk management.
. The technology focuses on making these assessments as fast and accurate as possible. This is accomplished by providing a centralized platform that accepts standardized data, ensuring that operational risk data is easily available for analysis. This means that risk managers can easily access all the data they need in a few clicks, whereas they previously had to spend hours simply collecting and extracting the data for analysis. Current operational bank risk management technology results in an exponential increase in both the speed and accuracy of assessing operational risks. The intelligent way the technology stores and uses data also enables it to predict emerging risks; giving some necessary insights and foresight to risk managers.
The future of operational bank risk management
The current operational risk management solutions use the latest technology to deliver the best possible outcomes. The most exciting avenue in risk technology, and in most technologies, is artificial intelligence. Being able to assess operational risks requires that computers be able to understand the way people work and the mistakes they may make to understand operational vulnerabilities. Artificial intelligence is a quickly emerging field but is already delivering astonishing results. The AI included in Predict360, our risk management solution, enables it to detect problems, parse information, and predict emerging risks. This increases the usefulness and efficiency of our solution exponentially, but the exciting part is that as AI develops further, we can expect even more from it.
Regulatory risks have always been uniquely important for heavily regulated industries such as banking. We have seen a major leap in regulatory risk management technology in the past decade. Assessing the severity of regulatory changes and understanding the changes themselves was out of the scope of most risk management solutions until a decade ago but this has quickly changed thanks to the development of natural language processing. Natural language processing gives computers a better understanding of the written word. This has resulted in risk management solutions gaining the ability to parse regulatory documents and quickly detect additions and changes.
The current use of technology in regulatory risk management
Smart design decisions allow current regulatory risk management solutions to deliver fantastic results. These solutions parse all regulatory updates and highlight the changes. They can also extract the changes most relevant to the bank. Risk maps allow these solutions to help with the implementation of changes as well. These solutions are fed with the relationship between different risks, regulations, policies, and documents when they are being implemented in the organization. This means that whenever there are any regulatory changes these solutions can instantly highlight every business process, policy, department, and document which may be affected by the regulatory updates.
There are many types of legal risks, each with their own dedicated risk management technology. Most legal risk solutions are, however, not put under the umbrella of risk management solutions. Compliance management solutions are a great example. Compliance is intrinsically linked with legalities because we are talking about complying with laws and regulations, but these solutions are usually considered different than risk solutions. Most banks also have a separate department handling compliance.
Bank risk management technology has quickly become an essential part of managing legal risks. Large banks have been using compliance and risk technology for multiple decades now. There are now cloud-based solutions available which are being implemented by small and mid-size banks across the world.
Integrated bank risk management solutions
Legal risks, as we mentioned before, are closely linked with or overlap with regulatory risks, operational risks, compliance risks, and more. That is why most banks are opting for integrated bank risk management solutions which can analyze the data from all types of risks to assess the legal risks faced by banks.