You deployed a credit scoring model 8 months ago. Today's monitoring report shows:
- PSI of 0.31 on the "monthly_income" feature (training baseline = 0.05)
- Average predicted probability of default has increased from 4.2% to 7.8%
- Actual default rate (90-day lag) has not yet been measured for recent predictions
Answer the following:
(1) Diagnose what is most likely happening. Distinguish between data drift, concept drift, and label shift, and identify which of these is the most likely explanation given the evidence.
(2) Should you retrain immediately or investigate first? Justify your answer — what specific investigation steps would you take, and what would change your answer?
(3) Describe what a complete retraining and revalidation process would look like, including the deployment strategy you would use to roll the new model out safely.