Incode Technologies, a global leader in artificial intelligence-powered identity verification and fraud prevention, has officially launched TrustGraph. Billed as the first biometric-anchored, privacy-preserving trust network built specifically for the agentic era, TrustGraph enables financial institutions, marketplaces, and AI companies to detect repeat fraud rings and automated agentic threats without ever pooling, exchanging, or exposing underlying customer data.
Incode launched TrustGraph, a privacy-preserving trust network designed to catch repeat fraud and autonomous agentic attacks.
During early access trials, participating institutions using TrustGraph surfaced up to 53% more fraud than they caught with existing standalone models alone.
The network is powered by patented peer-to-peer cryptography originating from Identiq, which was acquired by Incode in June 2026.
TrustGraph operates without a central data lake, ensuring that customer records remain strictly within each institution’s local environment.
Industry partnerships, such as with Canada’s Interac network, leverage TrustGraph to share cross-institution intelligence without compromising user privacy.
The platform provides contextual risk and trust signals, leaving final decision-making rules entirely in the hands of the host institution.
As malicious actors increasingly leverage autonomous AI agents to build synthetic identities, forge documents, and rapidly cycle through rejection loops across hundreds of companies simultaneously, traditional siloed defenses struggle to keep pace. Individual institutions typically only see isolated attempts within their own ecosystems, missing broader patterns where a single rogue device or digital identity targets multiple banks or platforms in an afternoon.
TrustGraph overcomes this limitation by connecting risk intelligence across participating organizations using advanced, privacy-preserving cryptography. Anchored to verified biometric identities, the network recognizes repeat offenders even when bad actors alter names, documents, or devices, delivering real-time signals during onboarding, login, or high-risk transactions.
"Fraud is networked. Defenses are still siloed," said Ricardo Amper, founder and CEO of Incode. "Attackers benefit from operating across institutions because each institution typically sees only its own interactions. A trust network changes that equation by turning isolated attempts into signals others can use. This is the trust infrastructure the AI era requires, and we're proud to make it available today."
Built on more than a decade of research and a $50M+ investment in cryptographic validation, TrustGraph enables secure multi-party computation (SMPC) to match fraud indicators without exposing sensitive customer records. Key architectural safeguards include:
Decentralized Design: Because the network is peer-to-peer, there is no central data lake or repository of personal identifiable information (PII) for attackers to target.
Strict De-Identification: Customer data, requestor identities, and contributing sources are completely masked through multi-layered cryptographic tokenization.
Institutional Autonomy: TrustGraph acts strictly as an intelligence provider, returning explainable risk or trust signals accompanied by reason codes while leaving final decision rules to the host institution.
Navjeet Grewal, Managing Director of Verification and Digital Credentials at Interac, emphasized the necessity of shared intelligence: "How do you expect every single business to keep up with deepfakes, synthetic identities, and romance scams on its own? It is impossible... TrustGraph allows institutions to benefit from fraud signals across the network without exposing customer data. If Company A experiences an attack and the same actor later targets Company B, Company B doesn’t have to face that attack as if it were the first time."
About Incode
Incode is a global leader in AI-driven identity and trust, with a mission to power a world of trust. Its platform verifies identity and age and stops fraud, using its own AI models, trained on more than 7 billion trust checks on a privacy-by-design architecture. Customers include eight of the top 10 U.S. banks, four of the top five marketplaces in the world, and the top three global neobanks. Founded in 2015 in San Francisco, Incode has been named a Leader in the Gartner® Magic Quadrant™ for Identity Verification three years in a row.
