Set launch metrics for an experiment in fraud detection workflow with high trust risk

Problem Statement Description

You are evaluating an experiment in a fraud detection workflow for a large-scale product used by families, where incorrect decisions can create serious trust and safety consequences. The workflow may involve detecting suspicious account activity, payment abuse, identity misuse, account takeovers, fake profiles, unsafe transactions, or other behaviors that could harm parents, children, caregivers, or household accounts.

The experiment is intended to reduce risk, but it may also introduce friction, false positives, delayed access, unnecessary reviews, or missed fraud. Because the target segment is families, the launch metrics must account for both fraud reduction and the quality of the user experience when legitimate users are challenged, blocked, or routed through review.

Define how you would measure whether this experiment is safe and effective enough to launch, expand, hold, or roll back. Your answer should focus on the metric framework, how each metric is defined, who is included in the denominator, how the data would be instrumented, and how the metrics would support a launch decision.

The experience should consider:

- The primary success metric for reducing fraud or risk, including the event being counted and the eligible population.

- False positive and false negative measurement, especially for family accounts or family-linked usage patterns.

- User trust and friction metrics, such as challenge completion, appeal rate, account recovery, abandonment, complaints, or support contact rate.

- Operational metrics for manual review, escalation queues, investigation quality, review latency, and reviewer capacity.

- Cohort cuts such as new vs. existing family accounts, parent vs. child flows, geography, device type, payment method, account age, and prior risk history.

- Instrumentation needs across detection, decisioning, user notification, challenge/review outcomes, appeals, and downstream fraud confirmation.

- Guardrails for safety, fairness, accessibility, privacy, and business impact.

- Decision thresholds, monitoring windows, and how you would interpret conflicting signals before launch or ramp-up.

The goal is to design a rigorous launch measurement plan for a high-trust fraud experiment: one that can show meaningful risk reduction without creating unacceptable harm, confusion, or exclusion for legitimate families.