Ultimate AML / Transaction Monitoring Bootcamp

Explain how transaction monitoring tracks historic and current customer activity, uses financial crime typologies to identify suspicious activity, and escalates findings within an AML program including KYC and sanctions.

Implement transaction monitoring to identify and mitigate money laundering and terrorism financing risks, and escalate suspicious activity to the financial intelligence unit.

Explain how transaction monitoring sits after KYC, continuously analyzes ongoing transactions, flags suspicious activity, generates cases, and escalates for financial crime investigations using data analytics, AI, and ML.

Describe the role of a transaction monitoring analyst by analyzing alerts, conducting investigations of account activity, and applying AML, KYC, and enhanced due diligence and screening.

Explore how transaction monitoring combines automated and non automated systems with human oversight to detect suspicious activity and escalate cases that automation alone cannot resolve within an AML/CTF program.

Explore how transaction monitoring evolved from frontline escalation to automated, ai-driven systems that reduce false alerts, boost efficiency, and sharpen focus on high-profile clients while raising regulatory expectations.

Explore why transaction monitoring remains challenging due to diverse customer typologies, false positives, and constant rule tuning across jurisdictions, requiring human oversight and tailored tech solutions.

Apply a risk-based approach to transaction monitoring, mitigating suspicious activity and escalating only when evidence exists, while moving on from low-risk cases and conducting enhanced due diligence when needed.

Trace the evolution of transaction monitoring from early physical observation under the bsa act to a legally required, risk-based aml program powered by technology and ai.

Generate alerts when thresholds are triggered in the transaction monitoring lifecycle, then investigate and decide to mitigate risk or escalate for financial crime review and possible suspicious activity reports.

Run daily transaction checks against monitoring rules. Identify breaches, collect them, and match to existing customers by ID to generate alerts for the analyst to investigate.

Onboard clients with a robust KYC profile and implement continuous transaction monitoring, then assess alerts against expected activity, product use, and countries of operation to determine red flags.

Rules in transaction monitoring generate alerts and drive investigations, letting institutions decide what constitutes financial crime and set thresholds to manage their risk mandate.

Minimize false positives in transaction monitoring and name screening by calibrating rules, reducing wasted time and resources, and protecting against missed true hits.

Reduce false positives in transaction monitoring by using control testing, adjusting algorithms, rules, thresholds, and real-time big data analytics with AI and machine learning insights to combat financial crime.

Explore terrorism financing within transaction monitoring, including the 24-hour SAR requirement to the financial intelligence unit and the need to escalate to the top for swift reporting.

Clarify the roles of transaction monitoring and name screening in AML compliance. Name screening occurs at onboarding to flag negative news and sanctions, while transaction monitoring tracks post-KYC client activity.

Learn how transaction monitoring generates alerts by evaluating industry, client size, location, and activity within KYC and high risk country scenarios.

Keep seven years of all transaction data for transaction monitoring, make it easily accessible to analysts, and train staff to retrieve it during investigations of alerts and SARs.

Review and clear alerts in transaction monitoring, escalating only when suspicious and using machine learning to reduce false matches and improve efficiency.

Use the can this transaction be reasonably explained check as a key AML investigation technique. If you can explain it, clear the alert; if not, investigate further for suspicious activity.

Explain the cash transaction threshold and currency transaction reports filed with FinCEN under the Bank Secrecy Act, including an example of a 13,548 cash deposit triggering alerts.

Identify structuring as the early anti-money laundering tactic to evade currency transaction report thresholds by splitting deposits with multiple people across branches, including cross-border movements.

See how structuring triggers a red flag in transaction monitoring: three deposits of 8,000 on the same day totaling 24,000, prompting escalation and currency transaction reporting considerations.

Smurfing is structuring to evade currency transaction reporting thresholds by splitting large deposits across many individuals; modern monitoring uses AI and real-time analytics to detect, flag, and investigate such activity.

In this smurfing example, cash mules deposit $9,000 to multiple branches to evade the $10,000 reporting threshold, illustrating how alerts and thresholds detect such activity.

Cuckoo smurfing weaves funds through multiple intermediaries and shell companies across countries via remittance transactions to mask origins and make money look legitimate.

Explore why an unusually large transaction may trigger a financial crime alert, and use KYC, source of wealth, and client context to decide if action is warranted.

Set a high transaction value rule to generate alerts for unusually large transactions, enabling risk-based controls, investigation, and escalation via KYC checks.

Identify a high number of transactions within seven or 30 days as a potential risk signal. Escalate suspicious activity to your manager.

Assess jurisdiction risk by flagging high-risk countries and requiring management approval before transactions proceed. The example shows handling residency ambiguity between Australia and Myanmar under policy and escalation procedures.

Detect sanctions exposure in transactions and generate alerts when dealings involve OFAC, EU, UN, or Australian sanctions. Escalate flagged cases to sanctions teams for review.

Examine a high risk country scenario in transaction monitoring and KYC remediation, escalate evidence of jurisdictional risk to line two, determine residency, assess risk rating, and flag high risk transactions.

Explore unusual activity reports in transaction monitoring, a documented step between clearing alerts and filing suspicious activity reports. Learn how these reports differ from SARs and how analysts use them.

Identify human trafficking indicators in a border town like El Paso, where high-intensity crime areas raise trafficking risk, evidenced by $312 fast-food purchases triggering a SAR.

Explore how transaction monitoring detects bribery by using rules and alerts for abnormal cash payments, lavish gifts, excessive expensing, and insistence on specific vendors.

Apply a risk-based approach to detect bribery and corruption using indicators and high-risk scenarios. Escalate suspicious activity through leadership and financial intelligence units for possible law enforcement action.

Document unusual activity with the unusual activity report to capture non-normal events not yet suspicious, not a SAR.

Prioritize alerts in transaction monitoring by risk level, processing high-risk cases first and lower-risk cases second, with immediate escalation for suspected terrorism financing to the FIU via SMR or SAR.

Identify and document suspicious activity, escalate to write a formal sar for submission to the financial intelligence unit, and follow the regulatory workflow while avoiding tipping off.

Assign the AML officer as the final decision maker for filing a suspicious activity report, and the designated staff who actually submit it, with possible delegation but ultimate AMLO accountability.

Learn why tipping off about an ongoing money-laundering investigation violates AML rules and risks jail or fines. Regulators prohibit sharing SAR details with clients to protect investigations and reputations.

Learn how a suspicious activity report documents money laundering risks, including customer profile, source of wealth and funds, trust ownership, and unusual windfall activity flagged to regulators like AUSTRAC.

The lecture explains lookback remediation in transaction monitoring, detailing how to gather data, mitigate high-risk alerts, and design lookback rules with higher thresholds to balance remediation costs.

Differentiate transaction monitoring from fraud: it can detect fraud but belongs to AML/compliance, with distinct typologies and investigation processes.

Identify suspicious activity indicators and document previous reports. Build a customer profile with kyc details, including source of wealth, source of funds, and director roles across companies.

Gain insights into the CTMA certified transaction monitoring associate exam within the AML / transaction monitoring bootcamp, featuring a 60-question scenario-based multiple-choice test, SAS thresholds, and a $1,000 fee.

Master AML and transaction monitoring skills to obtain a job as a transaction monitoring analyst. The instructor offers support for any questions.