Das Szenario
A lending platform must log loan applications, model predictions, and actual outcomes to evaluate bias across protected attributes over time.
Was diese Zeichnung zeigt
Die dahinterstehenden Entscheidungen verstehen.
01
Separate ApplicantAttribute join table to track multiple protected attributes per applicant
02
Decouple ModelVersion and MonitoringRun so each deployed model version can be audited independently
03
Store BiasMetric thresholds and pass flags alongside Alert records for reproducible detection
Use when building a monitoring data lake for ML models that need bias auditing, drift tracking, or fairness reporting.