Incode Launched TrustGraph Fraud Network
The new network allows global institutions to share fraud signals while keeping customer data private.
Updated on Oct. 14, 2026 in Financial Crime
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Incode has officially launched TrustGraph, a fraud intelligence network that enables institutions to exchange security signals without sharing sensitive personal information. The platform uses secure multi-party computation to help organizations identify potential threats using data from other network participants.
Why it matters
Financial institutions need advanced ways to detect fraud attacks that are novel to their own internal records. By learning from the collective experience of other entities, organizations can better stop sophisticated threats while maintaining compliance with international privacy regulations.
In early access testing, participants identified 53 percent more fraud cases across 12.2 million verified sessions. The system functions by de-identifying signals to search for cryptographic matches.
The players
Incode
Incode is a biometric identity verification company that develops advanced software for secure digital authentication.
Identiq
Identiq is a privacy-focused company that provides anonymous identity resolution technology to help organizations validate user data.
Interac
Interac is a Canadian financial services organization that utilizes Incode document verification technology for secure transactions.
The details
The technology integrates Incode's biometric identity verification with the anonymous resolution capabilities of Identiq, which Incode acquired earlier this year. TrustGraph provides explainable risk signals by utilizing reason codes to help security teams understand flagged activities.
Timeline
Incode acquired Identiq in June 2026.
The agentic fraud report was released in August 2026.
TrustGraph launched on October 14, 2026.
AI-powered fraud is projected to reach 61 percent by the end of 2026.
Legal Context
The launch of TrustGraph marks a shift in how institutions defend against the growing trend of AI-powered attacks. This tool directly addresses the projected rise in AI-driven fraud by allowing collective intelligence without compromising individual privacy.
This network helps businesses prevent unauthorized access by leveraging insights from a broader range of financial interactions. For the average user, this means an increased likelihood that fraudulent login or payment attempts are blocked before they impact account security.
The takeaway
As fraud tactics become more automated, collective defense networks are becoming essential for securing digital identities. Institutions that share threat signals remain better protected against novel attack patterns compared to those relying solely on isolated internal data.
Further reading
For more information on the evolving landscape of security threats, visit our Financial Crime section.
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Do you trust private companies to share fraud data without compromising your personal privacy?
