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23/06/2026 7:26 pm
TL;DR: Trust is now the hardest currency in digital identity, with AI, bots, synthetic IDs, deepfakes, regulation, transparency, and reusable identity all reshaping fraud and verification priorities, according to SumSub. The practical lesson is that identity programmes must treat trust as a governable control surface, not a branding outcome.
NHIMG editorial — based on content published by Sumsub: Fraud, Digital Identity, Trust. Where do we go from here?
Questions worth separating out
Q: How should teams handle trust decisions when AI makes identity evidence easier to fake?
A: Treat trust as a layered decision, not a single check.
Q: When does reusable digital identity create more risk than it reduces?
A: Reusable identity becomes risky when assurance is carried forward without freshness, revocation, or scope limits.
Q: What do security teams get wrong about synthetic identity fraud?
A: They often focus on one verification step instead of the full trust chain.
Practitioner guidance
- Map trust decisions to specific assurance levels Document which onboarding and transaction steps rely on weak, medium, or strong evidence, then require escalation when the evidence source changes or confidence drops.
- Test identity proofing against synthetic and deepfake scenarios Run red-team style exercises that simulate fabricated documents, face swaps, and replayed identity signals so you can see where single-factor trust still passes.
- Define freshness and revocation rules for reusable identity Set clear limits on how long attributes remain valid, who can issue them, and what conditions force re-validation before reuse.
What's in the full article
Sumsub's full podcast covers the operational detail this post intentionally leaves for the source:
- Guest discussion on how fraud, verification, and identity teams should divide responsibilities in practice
- Practical commentary on synthetic IDs, deepfakes, and trust signals used in real onboarding flows
- Coverage of regulation, transparency, and reusable digital identity from a platform and compliance perspective
- Examples from work with large enterprises on fraud protection and identity verification
👉 Read Sumsub's podcast on fraud, digital identity, and trust in the age of AI →
Digital identity trust in the age of AI and fraud?
Explore further
25/06/2026 3:26 am
Trust has become a control surface, not a soft brand attribute. The article is correct to frame trust as the hardest currency in digital identity, because AI now compresses the cost of deception while increasing the volume of identity signals that must be judged. For IAM and fraud teams, this means the boundary between assurance, access, and fraud prevention is disappearing. Practitioners should treat trust decisions as governable security events, not marketing language.
A few things that frame the scale:
- 79% of organisations have experienced secrets leaks, with 77% of these incidents resulting in tangible damage, according to Ultimate Guide to NHIs.
- 91.6% of secrets remain valid five days after the targeted organisation is notified, showing a critical gap in remediation procedures.
A question worth separating out:
Q: Who should own digital identity trust when fraud, IAM, and compliance overlap?
A: Ownership should be shared, but accountability must be explicit. Fraud teams understand attack patterns, IAM teams control access decisions, and compliance teams define evidence requirements. If those groups do not review the same trust rules, the organisation will miss gaps between proofing, access, and auditability.
👉 Read our full editorial: Trust in digital identity is weakening under AI-driven fraud
