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11/06/2026 11:03 pm
TL;DR: Structuring, or smurfing, breaks large cash movements into smaller deposits below reporting thresholds, while AI-generated identities and deepfakes make account creation and coordination harder to detect, according to Veriff's analysis and Fraud Index 2025. The lesson for financial institutions is that transaction monitoring alone is not enough when identity proofing, mule-account creation, and reporting workflows are all under pressure.
NHIMG editorial — based on content published by Veriff: Structuring, fraud, and the future of banking security
By the numbers:
- The Veriff Fraud Index 2025 reveals a 21% year-on-year increase in online fraud since 2024.
- 79% of people have been targeted by AI-generated, nerated fraud or deepfakes at least once in the past year.
- 97% of people believe strong security measures are, asures are important when signing up for a new financial service.
Questions worth separating out
Q: How should financial institutions stop structuring when deposits stay below reporting thresholds?
A: They should aggregate activity across accounts, branches, and time, rather than rely on single-transaction alerts.
Q: Why do synthetic identities make AML programmes less effective?
A: Synthetic identities weaken AML because they let criminals create accounts that look legitimate enough to receive dispersed deposits.
Q: What do financial institutions get wrong about structuring detection?
A: They often treat structuring as a threshold problem instead of a lifecycle problem.
Practitioner guidance
- Tighten identity proofing at account opening Require stronger verification for new financial-service signups so mule-account creation becomes harder before any structured deposits can be placed.
- Link sub-threshold transactions across entities Use pattern analytics that connect repeated deposits by different people, at different branches, into the same behavioural cluster instead of treating each transfer in isolation.
- Unify fraud and AML case handling Route suspicious onboarding, behavioural anomalies, and reporting evidence into one workflow so investigators can see identity confidence and transaction context together.
What's in the full article
Veriff's full blog covers the operational detail this post intentionally leaves for the source:
- Step-by-step explanation of structuring and smurfing patterns that compliance teams can map to their own alert logic
- Examples of how AI-generated identities and deepfakes affect financial onboarding and mule-account risk
- Specific discussion of automated SAR compilation and the data points a filing must include
- Consumer survey findings on trust, biometrics, and identity verification adoption
👉 Read Veriff's analysis of structuring, AML controls, and identity fraud →
Structuring and AML controls: where financial identity checks fail?
Explore further
12/06/2026 7:33 am
Structuring exposes an identity-assurance gap, not just a transaction-monitoring gap. The article is right to show that sub-threshold deposits are only one part of the problem. The real weakness is that financial institutions often treat account opening, ongoing behaviour, and suspicious reporting as separate controls when criminals use them as one coordinated path. For practitioners, that means AML effectiveness depends on the integrity of the identity chain, not on threshold logic alone.
A few things that frame the scale:
- Only 5.7% of organisations have full visibility into their service accounts, according to Ultimate Guide to NHIs.
- 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools.
A question worth separating out:
Q: Who is accountable when suspicious activity is discovered after deposits have already been accepted?
A: Accountability usually sits across onboarding, fraud, AML, and compliance teams because each control stage contributed to the outcome. The practical question is whether the organisation can show who approved identity, who monitored behaviour, and who triggered the SAR workflow when the pattern emerged.
👉 Read our full editorial: Structuring exposes the limits of identity-led AML controls
