An AI model uses transaction metadata to classify whether an online purchase is likely fraudulent. The model was originally designed for credit card transactions but is now being applied to peer-to-peer digital currency transfers without modification. Which AI risk is MOST prominent?

B is correct because applying a model to a fundamentally different transaction type (credit card vs. peer-to-peer digital currency transfers) without revalidation constitutes use case expansion risk. The transaction features, fraud patterns, counterparty relationships, and regulatory context differ substantially between these environments, and the model's validation evidence is no longer applicable. This is a form of out-of-scope deployment. Model drift (A) relates to temporal changes, not environment changes. Adversarial evasion (C) may be a risk but is not the most prominent risk at the time of deployment. Regulatory licensing (D) may be relevant but is not the primary model risk.