P85Model EvaluationAdvancedDiagnose16 min

Diagnose High AUROC but Poor Alert Precision

Diagnose why strong ranking quality can coexist with poor precision at an operational threshold.

#diagnose#auroc#precision

Scenario

A fraud model has AUROC 0.93 on data with 1% fraud. At the deployed threshold it creates 1,000 alerts: 70 are fraud and 930 are false positives.

Problem statement

Explain the apparent conflict and identify checks or changes before declaring the model useful.

Your Task

  1. Separate ranking quality from threshold behavior.
  2. Use prevalence and false positives in the explanation.
  3. Recommend threshold- and workload-aware checks.

Related Concepts

AUROCPrecision-recallPrevalence

Ready to count this problem?

Mark it complete when you have reasoned through the solution in your own words.