Seon has enhanced its fraud detection platform with over 1,100 data signals, aiming to help banks, fintechs, and online businesses identify fake profiles and linked accounts with reduced customer disruption by leveraging detailed analysis across multiple data points.
SEON has widened its fraud detection platform to more than 1,100 data signals, a move the company says is designed to help banks, fintechs and online businesses spot fake identities and linked fraudulent accounts with less disruption to genuine customers. The update builds on a signal base that previously covered more than 900 first-party risk indicators, according to SEON.
The expanded system brings in address, phone and session data, alongside more detailed checks on digital footprints and devices. SEON says the aim is to spot inconsistencies across multiple data points that would be easy to miss if each check were reviewed in isolation. That matters because fraud teams are increasingly confronting AI-generated identities that can appear convincing at first glance, but often fail when their history is tested across several dimensions.
Tamas Kadar, SEON’s co-founder and chief executive, said the harder problem for criminals is not creating one believable profile but sustaining a consistent record across many accounts and many pieces of infrastructure. The company argues that its broader signal base makes it more difficult for bad actors to hide when they reuse devices, phone numbers, internet connections or address patterns.
Among the new checks are address verification tools that standardise locations across more than 240 countries, helping teams detect when apparently separate accounts are tied to the same building. SEON also says its upgraded device intelligence can flag AI-agent activity, compromised iPhones and Android eSIM mismatches, while session monitoring can identify automation, remote access and other behaviour during sign-up, login, account recovery, checkout and payment. The company has also made the signals available to connected AI tools through its Model Context Protocol server and launched a new investigation series called Hidden Risk Files.
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