A specialist in KYE, KYC and KYB, iCover uses Finovox to detect forged documents during recruitment and customer onboarding. Integrated through an API and a SaaS platform, the solution complements other fraud indicators and has become an essential part of its checks.
“Finovox helps detect forged documents alongside a range of corroborating indicators. The solution has become an indispensable component for iCover.”
Antoine Andrieu
Head of Fraud Solutions at iCover
iCover wanted to complement its KYE and KYC checks by analysing documents submitted during recruitment and customer onboarding.
Finovox was integrated through its SaaS platform and API to detect forged documents, complementing the other fraud indicators used by iCover.
The challenge
In its recruitment (KYE) and customer due diligence (KYC) processes, iCover uses several factors to assess fraud risk. The challenge was to incorporate document analysis while maintaining the fast response times expected in these processes.
iCover needed a solution capable of analysing documents in any language and in real time. Forged document detection therefore had to fit into the checks carried out during recruitment or customer onboarding.
Document analysis needed to fit alongside the many detection factors already used by iCover. Its role was to provide additional evidence from the submitted documents, to be considered alongside other signals when assessing risk.
Our solution
Finovox was quickly deployed at iCover to integrate forged document detection into its KYE and KYC processes. The implementation relied on two complementary ways to access the solution: the SaaS platform and the API.
The SaaS platform was initially made available in summer 2022 for a limited scope of documents. By September 2022, both the platform and the API were available for the full scope of documents agreed with iCover.
Finovox’s analysis forms part of iCover’s existing detection framework. Signs of document tampering complement other fraud indicators, helping teams assess risk based on multiple corroborating signals.
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