Define the investigation question
Start with a specific pattern: shared-device account abuse, suspicious beneficiary chains, or payment-instrument reuse. Define what useful evidence would look like and which team will review the result. A bounded question makes an evaluation easier to judge than a general promise to detect more fraud.
Establish the data contract
Identify event sources, stable entity identifiers, timestamps, and labels. Document missing values and known quality limitations. Agree on permissible data use, retention, residency, and access before sending production information. Use synthetic or appropriately de-identified examples for an initial discussion.
Compare against a baseline
Evaluate graph signals against the current rules or models on a representative historical period. Include legitimate overlap and known difficult cases. Define how to measure detection quality, incorrect escalations, and analyst usefulness before inspecting the results.
Design the failure path
A production decision point needs explicit timeouts, retries, idempotency, and a fallback policy. Decide whether an unavailable risk response leads to review, a challenge, or another controlled path. Requirements differ between an offline investigation and a real-time payment workflow.
Inspect evidence and controls
Ask how a score connects to source events, how relationship confidence is represented, and how analysts can correct outcomes. Review access controls, audit history, environment separation, and security documentation. Product claims should be supported by evidence relevant to the proposed deployment.
Agree on an exit decision
Set a limited evaluation scope and a review point. Decide what results justify a next phase, what needs more testing, and what would make the approach unsuitable. An evaluation should create a better-informed decision, even when the decision is not to proceed.