Fraud — INFERIVA

Signals in the moment, not patterns over weeks

What the session tells you

Before the transfer

Device and browser fingerprint
Remote access tools and emulators
Behaviour that does not match the account holder
Velocity against this customer's own baseline

What you can do about it

While it still matters

Hold the payment before it settles
Block an agent or a device automatically
Reach the customer before they send it
Open a case with the session evidence attached

Scam intervention

A customer being socially engineered is not committing fraud, they are losing money to it. Reaching them before the transfer completes is a different capability from scoring the transaction, and most AML platforms do not have it because it was never their problem.

Including your own people

Insider events and network links are tracked on the same graph as customer relationships. An employee sharing attributes with a customer account is a pattern worth surfacing, and it does not appear in either system alone.

And scoring you can explain

Model scores are versioned. When somebody asks why a payment was held in March, the answer is which model, at what version, scoring what — not a number with no provenance.

The agent laundering money on Tuesday is the agent taking scam deposits on Thursday. Two vendors cannot see that.

See it with your rules, not our demo data

Tell us where you operate and what you sell, and we will show you the platform configured the way it would actually run for you.

What happens next

One of us reads it, not a queue. We come back inside two working days with a time — or a straight answer about whether we are the right fit.

Stop it before the money goes