An exclusive article by Fred Kahn

Anti-Money Laundering red flags are the warning beacons in transaction monitoring systems that, when correctly configured and acted upon, can stop illicit flows before they spiral into billion-dollar penalties. Unfortunately, systemic failures in parameter settings, scenario coverage, and investigative follow-through have repeatedly undermined the promise of transaction monitoring. By dissecting real enforcement actions, we can pinpoint exactly which red flags were missed—and why.

AML Red Flags in Action: Case Analyses

TD Bank’s $3 Billion Penalty for Lax Controls

Between 2014 and 2023, TD Bank’s U.S. operation processed approximately $18.3 trillion in wire transfers—yet its transaction monitoring failed to detect a sophisticated drug-trafficking money-laundering ring. Regulators found that:

• Overly broad thresholds: The bank set alarm thresholds so high that unusual transfers under $100,000—common in layering—never triggered alerts.
• Insufficient scenario coverage: Synthetic identity schemes and mule account patterns were not modeled. No rule flagged multiple small transfers to newly opened accounts.
• Alert triage backlog: AML analysts faced a backlog of more than 5,000 unreviewed alerts per day. Legitimate red flags—such as rapid movement of funds between related accounts—were buried.
• Flat-budget paradigm: Despite rising alert volumes, compliance headcount remained stagnant. Investigations were rushed or closed without adequate documentation.

These failures allowed travel-rule evasion and repeated layering through correspondent accounts. The guilty plea in March 2024 cost TD $3 billion and highlighted that missing even one key red flag scenario can render a transaction monitoring program ineffective.

Metro Bank’s £16.7 Million Fine for Monitoring Failures

From June 2016 to December 2020, Metro Bank missed over 60 million high-risk transactions. The FCA identified specific breakdowns:

• Misconfigured watchlists: Sanctioned-person screening lists were updated quarterly, not in real time. Transfers to shell companies registered two months earlier on the OFSI list were never blocked.
• Rule logic errors: The “structuring detection” rule only flagged deposits above £10,000 made on the same day. Criminals structured deposits of £9,900 over two days, evading the rule entirely.
• Lack of risk-based differentiation: Retail and corporate customers shared identical monitoring parameters. High-net-worth clients engaged in multimillion-pound transfers faced the same scrutiny as typical account holders.
• Human oversight gaps: Junior compliance officers spotted unusual repeat transfers but escalation procedures were unclear. More than 150 SARs were filed only after FCA intervention—all deemed late or incomplete.

Metro Bank’s £16.7 million penalty underscores that missing even a single misconfigured rule can blind a monitoring system to glaring structuring red flags.

Julius Baer’s CHF 4.8 Million Penalty for Control Gaps

Between 2009 and 2019, Swiss private bank Julius Baer failed to detect illicit fund flows despite multiple red flag indicators:

• Inactive alert types: Scenario libraries included “Politically Exposed Person (PEP) activity” and “rapid inbound/outbound transfers,” but the latter was deactivated during a system upgrade in 2015 and never reactivated.
• Threshold drift: The bank raised its high-value transfer threshold from CHF 50,000 to CHF 250,000 in 2017, leaving mid-range laundering transactions unmonitored.
• Limited geographic risk calibration: Countries under FATF monitoring were not flagged as high-risk. Transfers from sanctioned jurisdictions went undetected because geographic weighting was omitted.
• Fragmented data sources: Client profiles were housed in separate legacy systems. Alerts lacked integration with KYC databases, so multiple beneficial-owner changes went unnoticed.

The Swiss Financial Market Supervisory Authority (FINMA) required a CHF 4.8 million payment, highlighting that even established private banks can falter when critical red flag scenarios are disabled or mis-tuned.

Common Transaction Monitoring Red Flags and Why They Fail

Financial institutions rely on these red flags to spot suspicious behavior early. Below is an expanded look at each indicator and the typical pitfalls that render them ineffective:

• Unusual Transaction Patterns
  Transaction volumes, frequencies or counter-party profiles that stray from a customer’s historical norm should trigger scrutiny. Failure often comes from:
  • Overbroad baselines that lump high-risk and low-risk customers together, so moderate anomalies never breach the alert threshold.
  • Static profiles that aren’t updated after major client events (e.g., corporate expansion, change of ownership), causing true outliers to appear “normal.”
  • Rule proliferation without coherently tuning scenarios, leading to conflicting alerts that overwhelm analysts rather than highlight genuine risks.
• Large Cash Transactions
  Significant cash deposits or withdrawals—especially when inconsistent with a customer’s known business—are classic red flags. Yet:
  • Thresholds set above regulatory minimums create blind spots where suspicious cash volumes slip through unreported.
  • Aggregation windows only sum transactions over 24 hours, allowing criminals to break large sums into multiple sub-daily deposits (“smurfing”) and avoid any single alert.
• Rapid Movement of Funds
  Quick successive transfers through multiple accounts or jurisdictions suggest layering. Common failures include:
  • Short tracking windows, where systems only trace flows within one business day, missing multi-day layering chains.
  • Lack of network analytics, so while individual transfers look innocuous, the bigger picture of funds cycling through dozens of accounts goes unseen.
• Structuring (Smurfing)
  Deliberate splitting of large sums into smaller chunks to avoid reporting thresholds. Systems falter when:
  • Structuring logic is too narrow, only flagging same-day multiples instead of patterns over several days or accounts.
  • Single-account focus means that coordinated activity across multiple related accounts isn’t aggregated, so no single account triggers an alert.
• Use of Shell Companies
  Entities with no clear business purpose often serve as conduits. Detection gaps arise from:
  • Superficial KYC checks, where incorporation documents aren’t cross-checked against reliable registries or scanned for anomalies.
  • No adverse-media or beneficial-owner linkage, so a shell set up by a known fraudster escapes notice if the name doesn’t match sanction lists.
• PEP and Sanctions Screening
  Transactions involving Politically Exposed Persons or sanctioned parties should always raise a flag. Yet firms slip up by:
  • Infrequent list updates, sometimes monthly or quarterly, letting newly sanctioned names or aliases bypass real-time screening.
  • Weak fuzzy-matching that fails to catch names with minor spelling variations or non-Latin characters, allowing sanctioned individuals to transact undetected.
• Geographic and Jurisdictional Risks
  Transfers to or from high-risk countries require enhanced scrutiny. Failures often trace to:
  • Incomplete country risk calibration, where only FATF “blacklist” nations are flagged, ignoring those on the grey list or under regional sanctions.
  • No dynamic weighting, so once a customer makes a one-off transfer to a risky jurisdiction, their risk score doesn’t adjust to reflect the elevated ongoing threat.

Each of these red flags is only as strong as the rules, scenarios and investigative processes behind it. By broadening baselines, tightening logic windows, integrating advanced network analysis and continuously updating watch-lists, institutions can turn these theoretical alerts into practical defenses.

Conclusion: Building Resilient Transaction Monitoring

Effective transaction monitoring demands more than off-the-shelf scenarios. Institutions must:

• Maintain dynamic, data-driven customer baselines that adjust to evolving client profiles.
• Conduct frequent rule performance reviews—both to lower false negatives and to recalibrate thresholds.
• Integrate disparate data sources—KYC, adverse media, sanctions lists—into a unified monitoring platform.
• Empower investigators with contextual intelligence, network analysis, and clear escalation protocols.

By rigorously testing scenarios, closing governance gaps, and ensuring robust alert triage, banks can turn AML red flags from theoretical markers into practical safeguards.

Related Links

• FinCEN Enforcement Actions
• FATF Recommendations
• FFIEC BSA/AML Examination Manual
• OCC Enforcement Actions
• FCA Enforcement Actions 2023/2024

Other FinCrime Central News About Transaction Monitoring

• Understanding False Positives in AML Compliance
• Optimizing Transaction Monitoring Parameters for Effective Compliance
• The Vital Role of Transaction Monitoring in Crypto Compliance

Some of FinCrime Central’s articles may have been enriched or edited with the help of AI tools. It may contain unintentional errors.