A firm building a loan-approval ML model needs both bias detection and explainable predictions. Which AWS solution provides these capabilities?

Amazon SageMaker Clarify is the correct choice because it directly addresses both bias detection and explainability for machine learning models. It helps identify potential biases in data and models and provides tools to understand model predictions, which is crucial for sensitive applications like loan approvals. Amazon SageMaker Data Wrangler is used for data preparation and feature engineering, not bias detection or explainability. Amazon SageMaker Model Cards are for documenting model details and performance, not for active bias detection or generating explanations. AWS AI Service Cards are a general concept for documenting responsible AI practices across AWS AI services, but SageMaker Clarify is the specific tool that performs the requested functions.