Verified trust boosts conversions, cuts fraud losses

Ping Identity has published findings from an IDC study linking continuous, contextual identity verification with higher transaction conversion, lower fraud losses, stronger compliance readiness, and faster workforce onboarding.

The research draws on a global survey of 794 organisations. It examined what IDC calls "verified trust", defined as "a continuous assurance that every digital interaction, whether human or machine/AI agent, is tied to an independently verified identity and remains trusted over time."

Organisations that met IDC's verified trust criteria recorded 51% higher customer registration conversion than peers. Fraud losses were 43% lower, compliance readiness was 44% stronger, and workforce onboarding was 47% faster.

Maturity gap

The study also highlighted a gap between how organisations rate their digital trust posture and what they have implemented. While 51% believe they are ahead of peers in establishing trusted digital identity, only 9% met IDC's criteria for verified trust leaders.

This gap matters as more business processes shift to AI-driven interactions and automated decision-making. Identity systems increasingly sit in the path of customer sign-ups, employee access, partner connections, and machine-to-machine activity. Weak verification or inconsistent controls can increase fraud risk and create operational friction.

IDC's model treats identity as an ongoing control point rather than a one-off authentication step. The white paper says verified trust "transforms identity from a static gate into a dynamic trust fabric," shifting away from perimeter-based approaches toward runtime checks that influence authorisation decisions.

How it works

IDC's definition of verified trust includes continuous, contextual verification for identity-sensitive events. It cites signals such as "zero-knowledge biometrics with liveness detection", device posture, behavioural intelligence, and AI-aware risk analysis.

In practice, organisations must collect and assess signals at multiple points in a digital journey, supported by policies that adjust to risk and context. That can mean tighter checks when a transaction looks unusual or when an identity is used in a new environment.

The model can apply to customers, employees, partners, and machine identities, including automated agents that request access to systems and data. Organisations have managed non-human identities for years through APIs and service accounts, but wider adoption of AI agents increases the volume and complexity of these interactions.

Leaders and starters

IDC split organisations by maturity. Leaders showed broader verification coverage across "trust flows": 69% verify 75% to 100% of trust flows, compared with 16% to 19% for early-stage adopters.

Scale was another differentiator. IDC found that 94% of leaders operate at enterprise scale across trust flows, while early-stage organisations were more likely to remain in pilot deployments.

Passwordless adoption also differed. Leaders used biometrics, passkeys, and digital wallets at rates of 80% to 83%, compared with under 30% among early-stage organisations.

These differences can shape customer journeys and internal processes. Stronger verification can reduce manual reviews and lower account takeovers and fraudulent registrations. For employees, faster onboarding can follow from more automated checks and tighter integration between identity systems and HR processes.

"In today's threat landscape, identity can no longer be treated as a single authentication event. In an AI-mediated enterprise, every authorisation decision must be continuously verified, contextualised, and governed," said Peter Barker, Chief Product Officer, Ping Identity.

"Verified trust is no longer a design choice - it's the prerequisite for operating at scale in AI driven environments," said Emanuel Figueroa, Senior Research Analyst, IDC.

Ping Identity focuses on identity security for large organisations, positioning its products around workforce, customer, and partner identity, alongside non-human identities. It also describes a "unified trust control plane" designed to adapt as risk and behaviour change.

IDC's findings suggest identity verification is becoming central to business performance metrics, not just security outcomes. As more interactions become automated and machine-initiated, organisations may face growing pressure to demonstrate stronger controls over who or what is accessing systems, and under what conditions.