Incognia, the leader in cross-device risk intelligence, announced the launch of Real-Time Scam Prevention, an AI-powered solution that helps financial institutions detect and prevent payment scams, including authorized-payment fraud and social-engineering schemes, by combining Physical Social Graph intelligence with additional risk signals.

Authorized-payment scams present a growing challenge for financial institutions because the customer making the payment may be using a legitimate account, device and credentials. According to the FTC, consumers reported losing $3.5 billion to impersonation scams in 2025, nearly triple the amount reported in 2020. While traditional fraud controls focus on verifying the person initiating a transaction, they may miss signs that a legitimate customer is being manipulated into sending money to a scammer.

Incognia addresses this gap with its Physical Social Graph, powered by patented Trusted Locations technology. Using persistent, apartment-level indoor location intelligence, it reveals real-world connections between payment senders and recipients that conventional transaction data may miss, helping identify suspicious relationships and coordinated fraud activity.

In an analysis of transactions from a major financial institution, Incognia found that its Physical social graph technology alone identified approximately 70% of scam transactions in the analyzed dataset. The findings demonstrated how historical real-world relationships can provide valuable evidence of scam risk, even when conventional fraud signals appear legitimate.

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“Banks have gotten very good at determining whether the person making a payment is legitimate, but with a scam, the legitimate customer is often the one making the payment,” said André Ferraz, co-founder and CEO of Incognia.

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