Model validation is the set of processes and activities designed to verify that models are performing as expected, in line with their design objectives and business purposes. Effective validation helps ensure that models are structurally sound, and identifies potential limitations and assumptions, and assesses their possible impact. The rigour and sophistication of validation should be commensurate with the user's overall use of models, the complexity and materiality of its models, and the size and complexity of the user's operations. Ongoing validation activities are intended to ascertain that changes in markets, products, exposures, activities, customers or business practices do not create new model limitations while material changes to models should also be subject to validation. Rigorous model validation plays a pivot role in model risk management, and entails a consistent testing framework and engine with proprietary data from model users.

A variety of statistical capabilities are applied by CT RISK to test, review, and validate models. The validation process will be documented and auditable with results logged and available to model users, including model comparison reports, adopting a scorecard-based approach for risk assessments. The model performance results will be responded to a questionnaire applicable to the specific model validation type in question. In addition to any feedback and recommendation, individual scores are aggregated at the questionnaire level to arrive at the overall score, based on which the validation rating is assigned.