How Important Is Model Risk Management Under Stressed Conditions

Financial institutions and asset managers depend on financial models to make key decisions. They use financial models as a framework that helps them make intelligent decisions. Including models for loans and profit/loss models, financial institutions employ a wide array of models in their day-to-day operations. Even the smallest mistake can hamper the operations of a financial institution. Banks and asset management firms often look for model risk management services to ensure everything is kosher.

What is model risk management for banks and asset managers?

A financial model may stop working. When a crucial model performs negatively, many business operations may be halted. The sudden stoppage of models is one of the many risks banks and asset managers are exposed to. Sometimes financial models start producing inaccurate results. This can be even more dangerous for a financial institution, as it may lead to wrong decisions. Consider a loan approval model that starts producing erroneous results. Since the employees rely on it, they may approve loans based on inaccurate model results. Also banks may approve loans to possible defaulters.

Incorrect data input is a material concern for financial institutions, as it jeopardizes the integrity of financial models. Banks also use risk models to mitigate problems hampering business continuity. But when risk models themselves stop working, who ensures continuity? 

In the last few years, banks’ and asset managers’ reliance on financial models has increased. This makes it paramount that financial models are always correct and provide accurate results. Sometimes models are interdependent within an organization. The failure of a single financial or risk model may affect all the other models. Organizations must keep a close eye on models and mitigate the associated risks. Through reliable model risk management services, banks can ensure all models are in optimum condition.

Importance of model risk management

Bank employees often come under the radar for failing to fulfill customer requests quickly. For example, banks look forward to accelerating loan-application processing. These lenders can win more customers if they approve loans very quickly. On the other hand, customers look for competition when a certain bank consumes a lot of time to process loan applications. Given the circumstances, bank employees rely on financial models to decide quickly. Issues arise when a model starts offering erroneous results, which bank employees invariably realize quite late. In the interim, they may have disbursed loans to people with a poor credit score, inviting further potential losses.

Besides causing financial losses, inaccurate models can result in improper resource allocation, loss of customers, and more. To prevent these losses, financial institutions must focus on model risk management.

Organizations must identify the sources of model risks and remove them proactively. A nonworking model may also impact other models and lead to serious damages.

Model risk management services help organizations avoid legal penalties. One may wonder how model risks can lead to regulatory penalties. Consider a bank that uses a tax model to prepare its financial documents. If the model starts offering inaccurate results, there may be discrepancies in the financial statements. This could result in the bank’s producing false tax documents, inadvertently resulting in tax evasion. Even if the bank’s intention is not to default on paying taxes, it may end up doing so. The moment this comes to the notice of the tax authorities, they will levy penalties on the bank. Similarly, financial institutions rely on compliance models to ensure they comply with the law. When a model fails, they face similar consequences as the bank.

In conclusion, banks and financial institutions are exposed to risks emanating from dysfunctional financial models and must take measures to avoid them. If there are no internal model experts, one can rely on model risk management services offered by outsourcing firms. 

Monitor and validate your models regularly to avoid such risks.