Fraud Risk: Sudden Drop in Credit Approval Rate

Context

You are the on-call Data Scientist supporting the risk/underwriting system. Historically, the daily approval rate has been stable. Yesterday, it dropped sharply in a single day.

Assume you have access to decision logs, rule engine configs, model registry, feature store, experiment platform, observability/monitoring dashboards, and vendor status pages.

Approval rate = approvals / submitted applications, measured on decision-event timestamps. (If your org uses a different definition, state and use it.)

Task

How would you diagnose the root cause? Provide:

1. A step-by-step investigative plan to localize and explain the drop.
2. The specific data you would pull.
3. A set of concrete hypotheses to test (and how to test them).

Hints

Consider:

• Traffic mix shifts (channel, merchant/partner, geo, device, new vs. returning).
• Rule or model changes (new version, thresholds, reason-code distribution).
• Data/feature pipeline issues (null spikes, late features, schema changes).
• Seasonality/calendar anomalies and promotions.
• Experiment/AB-test effects (assignments, guardrails, SRM).
• External dependencies (KYC/identity, bureau pulls, device fingerprinting, payment networks).
• Infrastructure/latency/timeouts and fail-closed policies.