RMA Model Validation Consortium Brings Banks Together to Tackle Issues
Financial institutions face a number of risks as they speed up digitization and rely more heavily on new technology to influence lending and other decisions, a new study of 62 banks by the Risk Management Association (RMA) has found.
“Banks increasingly use models to make decisions as well as to identify and measure risk, conduct stress tests, and perform other critical operations. This includes some powerful innovative practices like AI-driven models,” said Edward J. DeMarco, Jr., the head of Non-Financial Risk at RMA. “While this benefits customers by speeding credit decisions—and banks by making it easier to detect fraud—banks need to fully understand models and validate their accuracy to avoid creating more risk for their institutions.”
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The Survey of Model Risk Management, Vendor Model Validation, and Third-Party Model Risk covers the model risk management practices of North American banks ranging from $2 billion to $2 trillion in assets and explores in depth how financial institutions use and validate third-party models.
Among the key findings:
- The top two challenges to expanding validation capabilities were talent (72%) and cost (63%).
- More than 70% of firms validate models every one to two years, a best practice. The rest validate models every three years.
- Nearly two-thirds of respondents said their model risk management (MRM) function reports directly into the chief risk officer, a sign of MRM’s growing stature.
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RMA has established a Model Validation Consortium (MVC) to assist banks in validating the accuracy of models. More than 25 banks participate in the MVC.
“The increase in modeling comes at a time of growing concern about talent shortages in the financial industry, particularly in areas requiring technical skills such as model validation,” said Kevin D. Oden, founder and managing partner of Kevin D. Oden & Associates, a leading risk modeling validation company and RMA partner for RMA’s Model Validation Consortium. “This creates challenges for all banks but especially for community and mid-tier banks, as they often rely on third-party vendors to create models. Banks must verify that those models meet business needs and do not propagate errors or bias.”
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