Customer story · Compliance

The Silent Drain: Detecting A Slow-Burn Money Laundering Network

How RemitSo's continuous transaction monitoring uncovered a 90-day layering scheme that manual reviews would have missed entirely.

Linked accounts identified
23
Laundered funds intercepted
£187K
Monitoring window
90 days
Transactions analysed
340+
Executive summary

Nothing looked wrong. Until it did.

A UK-based FCA-registered payment institution deployed RemitSo's white-label platform to serve diaspora communities across 25+ corridors. Over 90 days, continuous transaction monitoring tracked subtle, evolving patterns across 23 seemingly unrelated accounts, gradually building a risk profile that revealed a layering operation routing £187,000 through the UAE to Nigeria-based shell entities.

The challenge

When nothing looks wrong.

Transactions that individually appeared entirely legitimate. Every customer had passed eKYC, every transaction had a plausible purpose, and no single amount triggered reporting thresholds.

Low-value consistency

Individual transactions ranged between £200 and £800, well below the £1,000 threshold that typically triggers enhanced scrutiny.

Varied timing

Transactions were spaced 5 to 12 days apart per account, mimicking genuine family remittance patterns.

Diverse profiles

Senders included healthcare workers, students and small business owners, a natural mix for diaspora remittances.

Multiple corridors

Transactions appeared to target different countries before converging on common intermediary accounts in the UAE.

How it was detected

Four phases over 13 weeks.

The Risk Rule Engine's 55+ automated factors accumulated micro-indicators, from baseline profiling to critical escalation.

Risk score progression over 90 days
TimelineAccounts flaggedRisk score
Weeks 1–20 of 2318/100 · Low
Weeks 3–58 of 2342/100 · Medium
Weeks 6–919 of 2367/100 · High
Weeks 10–1323 of 2391/100 · Critical
  1. Weeks 1–2 · Baseline profiling

    Behavioural baselines built. All 23 accounts showed normal activity: small, periodic transfers to Nigeria, Ghana and the UAE. Risk scores 10–25. No alerts.

  2. Weeks 3–5 · Pattern divergence

    8 accounts began routing to a common UAE intermediary. Average values rose from £280 to £620. Intervals shortened across 11 accounts. 6 accounts changed their declared purpose without profile updates.

  3. Weeks 6–9 · Network mapping

    All 23 accounts surfaced as one connected cluster, routing through 3 UAE intermediaries into 7 Nigerian beneficiaries. One beneficiary was a partial OFAC SDN match. 5 senders had KYC documents with sequential serial numbers. 14 accounts used just 4 devices.

  4. Weeks 10–13 · Escalation

    All 23 accounts breached the critical threshold. The system suspended them, froze £12,400 in pending transactions and escalated everything to the compliance officer with a complete evidence package.

Deep investigation

Unmasking the network.

Money laundering flow: UK to UAE to Nigeria
StageDetailsVolume
Placement23 UK senders, individual small transfers£187,340
LayeringConsolidated into 3 UAE intermediary accounts£182,100
IntegrationDisbursed to 7 Nigerian shell company accounts£176,800
  • 23 sender accounts suspended and moved to a "Blocked: AML investigation" customer segment.
  • 3 UAE intermediary accounts permanently blacklisted across the platform.
  • £12,400 frozen in pending transactions; £174,940 in completed transactions flagged for tracing.
  • High-risk country rules updated to apply enhanced monitoring to all UAE–Nigeria corridor transfers.
Regulatory reporting
AuthorityAction taken
UK National Crime AgencySuspicious activity reports filed for all 23 accounts with full histories, device fingerprints and the behavioural timeline
FCA supervisorProactive notification showing the effectiveness of automated monitoring controls
UAE Financial Intelligence UnitIntermediary account details shared for downstream investigation
NFIU NigeriaBeneficiary details and flow analysis shared through international cooperation channels
Why continuous monitoring wins

The pattern was suspicious, not the accounts.

01Behavioural baselines

Continuous profiling catches drift that point-in-time snapshots miss.

02Risk score evolution

Scoring escalated 23 accounts from low to critical over 90 days, with no analyst needed to trigger it.

03Network detection

Risk Radar connected 23 isolated accounts into one visible cluster.

04Cross-corridor analysis

Intermediary patterns exposed the layering structure, connecting UK senders to Nigerian shell entities.

05Automated escalation

System-driven suspension and freeze stopped further movement without human delay.

06Audit trail

One evidence package supported reporting to four authorities in three jurisdictions.

The most dangerous financial crimes are not the ones that trigger alarms. They are the ones designed to avoid them entirely.

RemitSo compliance team
Full case study Download the PDF

Get the complete analysis, including detailed forensic findings, regulatory references and recommendations.

Download PDF of this case study

Built by people who have helped MSBs for years.

The risk checks on every online transfer come from what they see every day.

  • The person paying isn't the customer
  • One bank account, several customers
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