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Understanding Artificial Intelligence and Machine Learning model of Risk Management Process

The standard model of risk management process starts with identifying risks followed with analyzing, prioritizing, resolving, and finally monitoring these risks. With increased regulatory requirements around effective risk management, firms have been increasing their investments in regulatory technology and 2nd line of defense programs. Fin-tech startups are leading the innovation frontier by solving these problems using AI, rather than by taking traditional rules based approach for detecting such issues. AI models are proving to be more effective in detecting anomalies in financial transactions and user behaviors. A firm’s investment in these advanced technologies pays for itself in very little time with its ability to manage operational risks more efficiently and prevent huge losses.

Let’s discuss these in detail as below:

Risk Identification

Identifying  risk areas of an organization in advance helps it to manage its risks in a consistent and transparent manner. If done correctly, a well-defined risk framework will make the process more predictable and helps reduce uncertainty. The initial step is to identify the risks that the business is exposed to in its operating environment. For example in the area of Trading, there are various kinds of risks – Anomalous Trading risks,  Fraud risks, Data Quality risks, Market Exposure risks, Client Connectivity Risks, Regulatory / Compliance risks, etc. It is of utmost importance to identify as many of these risk factors as possible with the help of domain experts in this organization. It is recommended that an organization have a risk management solution automatically update a centralized system. The advantage of this approach is that these categories of risks and the health of risk management across each of the categories can be visible to every stakeholder in the organization. If done correctly, it will make the process more predictable and help reduce uncertainty, financial losses and regulatory fines.

Risk Analysis

After a risk is identified, the next step is to analyze the risk. The Risk scope must be determined and it is imperative to understand the link between the risk and different factors within the organization. There are risks that can bring the whole business to a standstill if that risk event occurs, and there are risks that can cause reputational damages to the firm in front of clients, regulators and common public. Most risk management solutions have different categories of risks, depending on the severity of the risk from low to high. It is important to rank risks of each category because it allows the organization to gain a holistic view of the risk exposure of the whole organization.

When an ideal risk management solution is implemented – it helps in mapping these risks to different documents, policies, procedures, and business processes along with the current health of the risk category. This means that the system will already have a mapped risk framework that will evaluate risks and let you know the far-reaching effects of each risk. Firms often spend far too much time developing disparate systems to support their risk management and still find themselves being charged by regulators of having inadequate internal risk management controls.

Risk Treatment

Risks should be eliminated or contained as much as possible. This is usually done by connecting with the experts of the field to which the risk belongs to. In an ideal risk management solution, all the relevant stakeholders can be sent notifications from within the system as soon as the risk is identified. The discussion regarding the risk and its possible solution can take place from within the system. Ownership can be assigned to individuals. Senior management can get updates directly from within the risk management solution instead of relying on information flow up the chain.

Risk Monitoring and Risk Review

Not all risks can be eliminated – some risks are always present. Market risks and environmental risks are just two examples of risks that always need to be monitored. Risk owners must make sure that they keep a close watch on all risk factors. Under a digital environment, the risk management system monitors the entire risk framework of the organization. Monitoring risks also allows your business to ensure continuity.

Once risks have been identified and assessed, all techniques to manage the risk fall into one or more of these four major categories:

– Avoid (eliminate – withdraw)

– Reduce (optimize – mitigate)

– Share (transfer – outsource)

– Retain (accept and budget)

Quantel AI has released an advanced risk management system for detecting trading anomalies like market abuse, fraudulent / manipulative trading, erroneous trading, malfunctioning algorithms and compliance violations. Many of the aspects of a design principles of risk management outlined above can be achieved through EagleAi. EagleAi is designed to be a seamless AI engine that ‘learns patterns by observing the flows’ which helps it to identify a problem as soon as it happens. EagleAi can also be an early warning system as it can see the trend to predict when a breach is expected to happen. EagleAI is built using advanced Self Learning AI/ML integrated with big data analytics with our real-time risk management solution – and ensures that the data in your system is accurate to reduce false positives. Because it is a self-learner, EagleAi can detect even issues that were previously not known to exist and prevent a future issue. EagleAi has integrated its risk modules in popular Enterprise GRC tools such as OpenPages and SeviceNow. EagleAi can be deployed both as an on-prem as well as a cloud hosted solution.

Request a demo today – and we can show you how EagleAi, a fully managed service can mitigate your enterprise’s risks at a fraction of cost and could even uncover lurking issues that could surface up to cause major losses.

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