Transaction and customer behavior monitoring is a core element of every effective AML program. After reviewing the basic concepts and approaches, in this article we will focus on the practical application of monitoring, typical scenarios, real-world challenges, and proven methods for effectiveness.

How to Build an Effective Monitoring Process: From Templates to Action

1. Defining a Typical Customer Profile (“Normal Behavior Baseline”)

For each client type, it is necessary to build an understanding of what constitutes “normal behavior”:

• How often and what amounts the client typically transacts;
• Which jurisdictions the client interacts with;

What products or services the client uses

Example:
A client registered as a small retail merchant typically makes a few local transfers per month. Suddenly, they start receiving international payments from offshore companies

→ Alert: Unusual change in the source and nature of funds

2. Creating Practical Alert Scenarios

It is not enough to set static thresholds. Well-designed scenarios are needed, such as:

• Large single payments without prior history;
• Series of small payments just below reporting thresholds;
• Sudden changes in the countries involved in incoming or outgoing transfers;
• Frequent cash deposits or withdrawals within short periods;
• Use of new payment channels, such as cryptocurrencies;
• Activity at unusual hours (e.g., midnight transactions without a logical reason).

Example of an automatic scenario:
“If a client performs 5 or more transactions under EUR 9,000 within 7 days → trigger an alert for potential structuring.”

How to Identify Real Risks Among Numerous Alerts

Prioritization of Alerts:

• High risk: immediate review (e.g., transfer to a sanctioned country);
• Medium risk: gather additional information (e.g., a new source of funds);
• Low risk: ongoing monitoring and scheduled review

Practical Tip:
Not every alert indicates suspicious activity. Apply a contextual review — analyze the client’s behavior in a broader context.

Common Monitoring Mistakes and How to Avoid Them

1. Rules Too Narrow → Missing Risks

Example: Monitoring only transactions over EUR 10,000 may miss structured laundering via multiple smaller amounts.
Solution: Include behavioral scenarios, not just static value thresholds.

2. Excessive Alerts → Overwhelming the Team

Example: Generating 200 alerts per day for a team of three analysts.
Solution: Implement risk scoring and threshold logic for alerts.

3.Static Settings → Rapidly Outdated Monitoring

Example: The COVID-19 pandemic changed client behavior, but many systems did not adapt their rules.
Solution: Review and update monitoring rules at least every six months.

Practical Examples Across Different Industries

Financial Institutions:

• Monitoring inconsistencies between usual and new sources of funds;
• Reviewing large transactions from FATF-listed countries.

Crypto Platforms (VASPs):

• Tracking links with mixers and transactions through Tor networks;
• Monitoring large cryptocurrency purchases followed by rapid withdrawals.

Real Estate Sector:

• Identifying unusual cash payments for property purchases;
• Checking for complex ownership structures.

Luxury Goods Traders:

• Monitoring large cash purchases;
• Tracking quick resale of assets shortly after acquisition.

What Works in Practice?

• A combination of real-time and Day+1 monitoring;
• Risk-based scenario settings;
• Integrating behavioral analytics;
• Training the team to interpret alerts in context.

White Listing: How to Apply It Reasonably

White Listing is the process of marking certain clients or types of transactions as low-risk to avoid generating unnecessary alerts. This includes:

• Clients with a long-standing, stable history verified by the AML team;
• Regulated counterparties;
• Intra-group operations;

Clients performing recurring, previously verified transactions

Monitoring Effectiveness: Tracking KPIs

Monitoring the following key performance indicators is critical for effective oversight:

• Number of generated alerts per month;
• Percentage of false positives;
• Average time to process an alert;
• Percentage of alerts escalated to STR (Suspicious Transaction Reports);
• Number of STRs filed versus total alerts.

KPIs should be reviewed periodically and used to adapt and improve the monitoring system

Defining User Roles in the Monitoring Process

Clear role distribution is essential for effective monitoring:

• Analysts: perform initial alert reviews;
• Supervisors: review and approve or return alerts for reanalysis;
• Compliance/AML Officers: make final decisions on escalation or case closure;
• System Administrators: manage monitoring system configurations without participating in alert analysis.

This separation ensures process integrity and quality control.

Documenting Monitoring Activities

Each alert must be documented, including:

• What was observed;
• What analysis was conducted;
• What decision was made and why.

Additionally, documentation must cover:

• All cases of White Listing;
• Changes to monitoring system settings;
• Team training sessions related to monitoring.

Conclusion: Monitoring Is Not Just a System, It Is an Intelligent Process

Effective monitoring requires a combination of technology, expertise, adaptability to new risks, and intelligent resource management. Only in this way can monitoring become a real defense against financial crime — not just a formal exercise.

Want to Learn More?

Compliance Navi offers the development of complete monitoring programs, practical team trainings, and consulting services to optimize your AML systems according to the specific needs of your business.