ORIGINAL COMPANY-CONTEXT PRACTICE
Evaluate a fraud-review ranking with delayed labels
Original practice scenario: A hypothetical payments team can manually review only a fixed number of alerts. Confirmed outcomes arrive late and many unreviewed transactions have unknown status. Design evaluation.
Written for independent practice using company context; this is not a verified question from a company interview.
A REASONED APPROACH
Model answer.
Match evaluation to the review budget and label-availability process. Overall accuracy can look excellent in a rare-event setting while giving a poor investigation queue.
Work through it
- Define prediction time and a mature outcome window, retaining which cases were reviewed and why rather than treating unreviewed transactions as confirmed negatives.
- Compare precision, recall and operational workload at realistic queue sizes using time-separated splits and transparent rule-based baselines.
- Assess calibration and error patterns across relevant transaction segments, then monitor drift and analyst overrides during a bounded deployment with review authority retained.
Tradeoffs to discuss
- A more sensitive queue may recover additional suspicious cases but increase investigator burden and disruption to legitimate activity.
Common pitfalls
- Do not leak chargeback or investigation results into features recorded before the alert.
- Selective review creates evaluation bias; document coverage and use justified sampling when obtaining additional labels.