About Footprint
Footprint is a rapidly growing, AI-native platform for risk operations, identity verification, and compliance. Their platform helps companies grow faster by orchestrating onboarding, identity verification, and fraud controls in one place, replacing point solutions and manual case review with programmable playbooks and autonomous AI agents. Footprint's Percy AI agents run investigations, screen for sanctions and adverse media, and produce audit-ready decisions at machine speed, while its Identity platform gives businesses a fully customizable, end-to-end onboarding experience. Footprint's customers span fintech, banking, and lending, including companies like Apiture, Nuvei, LoanPro, and Findigs.
The challenge
Effective risk decisioning and identity verification requires more than the single-point-in-time credential information an applicant submits. Names, documents, and answers to onboarding questions can be manipulated or reused, and identity data alone often can't reveal when the same actor, device, or environment is behind multiple applications.
Footprint needed a way to bring a greater level of device context into its decisioning and AI systems. They wanted to ensure their platform and risk teams could recognize related activity across applications and sessions, not just evaluate each one in isolation.
Why Fingerprint
Footprint chose Fingerprint for the accuracy of our device identification, the breadth and depth of signals we provide, and how easily those signals fit into and complement their existing workflows. Fingerprint's device intelligence gives Footprint's decisioning systems and AI agents consistent, reliable context about the device behind every interaction, a foundation Footprint can build on without having to develop and maintain device fingerprinting in-house.
Better together
Fingerprint provides the device intelligence layer. Footprint combines it with identity data, verification results, AI agent findings, customer-specific policies, and prior activity. Bringing these signals together lets Footprint's platform evaluate the full context behind an application, surface relevant connections between seemingly unrelated events, and help risk teams decide what to approve, decline, or send for closer review.
AI is only as useful as the context it can reason over. Fingerprint gives Footprint a dependable device intelligence layer that helps our AI agents connect related activity across time, surface relevant risk patterns, and give risk teams clearer context to produce more informed decisions.
Business impact
Fingerprint's clearest impact for Footprint has been stronger detection of device-linked activity, such as fraud rings, that identity data alone may not reveal. By recognizing devices across sessions and applications, Fingerprint helps Footprint:
- Surface possible duplicate accounts
- Identify suspicious environments, including virtual machines, emulators, and tampering
- Give reviewers more context when investigating a flagged application
Device intelligence also lets Footprint's customers apply friction more selectively. Rather than challenging every applicant with additional verification, they can focus friction and manual review on sessions carrying stronger risk indicators, such as those onboarding through a VPN, while allowing lower-risk applicants through with less disruption.
Looking ahead: Risk Intelligence Fabric
Footprint is building toward a future where risk decisions carry context across time rather than evaluating each event in isolation. Their upcoming Risk Intelligence Fabric, an AI memory infrastructure layer, will embed events and extracted attributes into a memory graph so the Footprint platform can recall relevant history across interactions and cases.
Fingerprint's visitor ID is set to be one of the important signals feeding that memory layer. By embedding persistent device identity as part of Footprint's memory graph, Fingerprint will help their decisioning systems and AI agents recall related activity and reason over richer context every time a new event comes in.
