Catch the applicants who never intend to pay
First party fraud hides inside your first payment defaults. Infact screens every application in real time across every lender reporting into our bureau, flagging data manipulation and intent signals at the point of application.
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At a glance
Detect first party fraud at the point of application.
Income, employment and household details that change across applications are read for what they usually signal:
Explain your first payment defaults.
Outcome intelligence from across the bureau links an application to confirmed fraud and previous first payment defaults on the same identity.
Fraud savings without the friction.
Real-time screening with no footprint on the consumer's file, no added journey steps, and fewer false positive referrals holding up genuine customers.
The pain
The first payment defaults nobody can explain
One credit risk lead tested 850 bureau variables against an unexplained first payment default problem and found nothing.
No repayment is fraud
Most lenders book all of it as credit loss. That means the fraud has no owner, no budget and no fix.
The proof of concepts that prove nothing
If a test cannot find the fraud you already confirmed, it cannot size the fraud you have not.
How it works: intent shows before the first payment is missed
Tuesday: a credit card application.
Wednesday: a different lender, two dependants instead of three.
Thursday: one dependant, a better job title, higher income.
Three clean applications. One invisible sequence.
Wednesday: a different lender, two dependants instead of three.
Thursday: one dependant, a better job title, higher income.
Three clean applications. One invisible sequence.
Screening at the point of application
Every application is screened in real time against activity across every lender reporting into the Infact bureau. Detection focuses on data manipulation between applications: income that creeps up, employment status that changes with each attempt, household composition that shifts, amounts that escalate. Shopping around for credit is healthy behaviour and is treated as a positive signal. Manipulation is not.
Outcome intelligence
Because Infact is a bureau, every application resolves to a single verified identity, matched even as names, addresses and contact details shift. One person, one view, however the story is told. Confirmed outcomes flow back into the bureau. An application can be linked to previous first payment defaults and confirmed fraud on the same identity, and detection strategies learn from outcomes as they mature.
Third party signal, and growing
Identity, email, phone, IP and mobile network intelligence (SIM swap recency, call forwarding, number tenure, direct from the network operators) extend detection to third party fraud and account takeover. These signals prove themselves in live testing, which is exactly how we deploy them: shadow mode on your applications, measured against your confirmed outcomes.
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