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How Leading Financial Services Companies are Managing Model Risk in 2023

How Leading Financial Services Companies are Managing Model Risk in 2023

Financial services companies face a complex risk management landscape, with model risk being one key area of concern. Model risk is a bit unique because it is a risk factor that is essentially exclusive to the financial sector and companies that are applying risk management principles in a financial context. 

In the world of finance, quantitative data rules. A seemingly small error or data corruption incident could result in transaction errors or even complete system shutdowns. Few would argue that model risk management is not critical to success in the financial industry. But developing an effective model risk management strategy can be challenging due to the dynamic, high-risk nature of the financial space. 

Financial services companies can see significant losses as a result of model risk-related issues — a fact that underscores the importance of an effective risk management and mitigation strategy. This may lead you to wonder: how are leading financial services companies managing model risk in 2023? 

What is Model Risk in the Financial Services Industry? 

Model risk refers to the risk factors and vulnerabilities that arise when a flawed or inaccurate financial model is put to use such as in the case of strategy development, policy creation, or a decision-making process. 

To put this point to work, consider the following scenario. Let’s say your financial services company offers personal loans. You may develop a policy stating that the company will not lend more than $150,000 to individuals under the age of 25 because they represent a higher-than-acceptable level of risk. But it turns out that this actually isn’t true and as a result, the policy is inherently flawed. This is an example of model risk since we have a policy that’s based on an inaccurate premise or model. The financial services company stands to lose as a result of this error since they’re turning away prospective borrowers — individuals who may have been great clients. 

What Factors Lead to Model Risk? 

Model risk can take many forms since there is plenty of room for error when you’re developing a strategy or policy. Here is a look at a few of the many factors that can lead to model risk. 

  • Data – A model that’s based upon flawed or inaccurate data points translates into a significant risk factor. Incomplete data sets can also be problematic from a model risk perspective since you’re basing your decision or strategy upon a limited portion of the equation. When your basis is flawed, so too is your strategy or decision. 
  • Model Implementation – A model may be implemented improperly or the implementation may be incomplete. The result? Anything that is based upon this model will be inherently flawed as well. 
  • Model Interpretation – If you happen to misinterpret the data associated with a model, you risk a situation where every decision or strategy that’s based upon that model is flawed as well. 

Model risk can impact a financial services company in many ways. In fact, these issues represent a very real risk factor for this type of business since data-driven decision-making is so commonplace in this industry. In fact, the ability to make data-driven decisions is really critical for financial services firms due to the data-centric nature of this business niche. What’s more, the U.S. Federal Reserve Bank has even issued a model risk management (MRM) regulatory standard known as SR-11-7. The Federal Deposit Insurance Corporation — better known as the FDIC — has also issued model risk management recommendations. In short,  there is no shortage of industry heavyweights advising on the topic of MRM. 

How to Manage Model Risk in 2023

Financial services companies are driven forward by data, yet that’s precisely where model risk dwells. This begs the question: How are the leading financial services companies managing model risk in 2023 and beyond?

Governance Practices – By following the industry’s best data management and governance practices as recommended by well-known agencies such as the FDIC and the Federal Reserve, financial services companies can usually manage model risk quite effectively. Periodic self-evaluations are beneficial too because these measures will allow you to examine your governance practices and identify areas where you may be falling short.  Recommendations and best practices do change periodically, though, so it is important that companies stay up-to-date with the most current advice on the subject of model risk management-related governance and risk management in general. 

Model Validation – Model validation can be time-consuming and tedious, but most find that it’s worth the effort. Through the model risk management validation process, you have the ability to minimize or even eliminate an element of risk from the equation. Therefore, consider taking the time to verify that your model — and your interpretation of that model — is accurate and valid to minimize this risk factor. 

Routine Model Risk Assessments – Data-driven decision-making is the preferred norm in the business world. But this places decision-makers in a precarious position because it means that their decisions are only as good as the data that they are based upon. If your model is flawed, then any decision that arises from this data will lack integrity. For this reason, top financial services companies perform regular model risk assessments on a regular basis — semi-annually or quarterly in many cases. 

Model Risk Management Frameworks – Some risk management software platforms are equipped with model risk management frameworks. Also called MRM frameworks, these platforms offer tools and features that will guide your company’s model risk management efforts. This can include checklists and tools for identifying instances of model risk within your organization. You’ll also find tools that can be used to assess and evaluate potentially-problematic models, with project planning-type features that allow you to map out an action plan in the event that a problem area is identified. These MRM frameworks are great for financial services companies that need a bit of guidance in their risk management efforts. 

A robust model risk management strategy is essential for success in today’s high-risk financial industry. But actually developing and implementing this type of strategy can be a tremendous challenge. This is where the right technology comes into play. The recipe for success is comprised of a well-architected MRM framework, combined with a commitment to rooting out any flaws, inaccuracies, or errors that could compromise a model’s integrity.

The Right Technology to Support Your Model Risk Management Needs

The right risk management software platform can go a long way toward helping your financial services company to manage model risk and the other threats and vulnerabilities that your business routinely confronts. 

At iTech, model risk management solutions are among our specialties. We provide clients with custom-tailored risk management software solutions. This includes platforms that can be leveraged as part of a financial services company’s model risk management strategy. We take a collaborative approach, working with the client to gain a full understanding of their risk management pain points and strategic objectives. Then, we work to develop an innovative risk management solution that will deliver an operational, strategic, and competitive advantage. If you’re seeking the right technology to manage model risk for your financial services company, contact the team at iTech. We’ll start a dialogue on your model risk management needs.