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Models, therefore, should not be validated by their owners as they can be highly technical, and some institutions may find it difficult to assemble a model risk team that has sufficient functional and technical expertise to carry out independent validation.

When faced with this obstacle, institutions often outsource the validation task to third parties.

For example, a poorly designed risk assessment model may result in a bank establishing relationships with clients that present a risk that is greater than its risk appetite, thus exposing the bank to regulatory scrutiny and reputation damage.

A validation should independently challenge the underlying conceptual design and ensure that documentation is appropriate to support the model’s logic and the model’s ability to achieve desired regulatory and business outcomes for which it is designed.

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4 Process Validation To verify that a model is operating effectively, it is important to prove that the established processes for the model’s ongoing administration, including governance policies and procedures, support the model’s sustainability.Where gaps or limitations are observed, controls should be evaluated to enable the model to function effectively.3 Data Validation and Quality Assessment Data errors or irregularities impair results and might lead to an organisation’s failure to identify and respond to risks.A review of the processes also determines whether the models are producing output that is accurate, managed effectively, and subject to the appropriate controls.If done effectively, model validation will enable your bank to have every confidence in its various models’ accuracy, as well as aligning them with the bank’s business and regulatory expectations.

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