Real ID. Matching selfie. Clean liveness. You approved the account, and it belongs to a fraudster. Your checks never looked at who was holding the document. This is how that happens, what it costs you, and how silent capture closes the gap.
Keep crypto destination records and deposit observations organised. A deposit observation, customer match, screening decision and settled funds are separate facts.
Set up your organisation’s Travel Rule information-exchange journey, test it and follow the displayed activation requirements. Every transfer still needs its own current authorisation before your wallet acts.
Screen a saved crypto wallet and inspect the decision with its exposure evidence. Keep blockchain risk, address approval, signed control and transfer clearance separate.
Read customer risk with its evidence and assessment basis. Customer risk helps explain a customer’s recorded state; it is different from the risk decision for a specific payment.
Assess transaction risk before your application moves money. Submit an exact amount, the right direction and the parties involved, then use the decision and its explanation.
Assess logins, account recovery and other non-payment activity. Send the actual customer and device context, read the returned decision and enforce it in your own app.
Continuous monitoring rechecks selected customer evidence over time. Configure a policy, enrol eligible customers and give material changes a clear review owner.
Screen customers for sanctions, politically exposed person and adverse-media findings. Start with a correctly linked customer, run the supported checks, then review possible matches with the evidence available.
Matching a face to one document is a contained problem. Searching it against every identity a business has verified is not. Why our fraud work is becoming a compute problem, and why Toden has joined NVIDIA Inception.