You are a data scientist at a financial institution tasked with identifying and mitigating bias in a machine learning model used for loan approvals. The model is deployed using Amazon SageMaker, and the regulatory team has raised concerns about potential discrimination based on sensitive attributes such as gender and ethnicity. Which of the following steps is MOST APPROPRIATE to effectively identify and mitigate bias using Amazon SageMaker Clarify?