A lending model is found to approve applicants from one postcode group at a much lower rate. The team removes ethnicity from the training data and retrains. Approval rates remain skewed. What is the most accurate explanation?

• AThe model needs more training data before the disparity will resolve.
• BThe remaining skew reflects real differences and is therefore fair.
• CThe model is underfitted and needs a more flexible architecture.
• DOther fields act as proxies, so removing the attribute removed the ability to measure the disparity rather than the disparity itself.