Bank using AML transaction monitoring systems to reduce workload of compliance teams and stop financial crime

Investigating high-risk transactions days, weeks, or months after they happen makes no sense for financial institutions (FIs). Criminals count on a sluggish response from FIs’ anti-money laundering compliance teams to blend in among trustworthy customers. Banks need an AML transaction monitoring system to reveal financial crime patterns and reduce their compliance teams’ workloads.

What is AML Transaction Monitoring?

AML Transaction Monitoring systems enable banks to rapidly perform risk assessments of customer transactions. With these insights, banks can understand the potential risk of money laundering or other financial crimes. As more people shop online, banks need to watch closely for suspicious payments and transactions.

How AML Transaction Monitoring Works

AML Transaction Monitoring solutions work by taking a risk-based approach to reviewing transactions with the customers’ known profile information. This information is collected during the KYC/CDD process when the customer onboards with the bank. The types of transactions reviewed include ACH activities, cash deposits and withdrawals, credit card and debit card transactions, and wire transfers, to name a few options. 

Effective solutions also review embargoes and sanction screening watchlists. These are critical steps in the workflow to help financial institutions remain compliant and avoid severe consequences. Think fines, sanctions, regulatory audits, and even criminal charges in the worst-case scenarios.  

Benefits of a Risk-Based Approach to AML

Why should FIs consider implementing a risk-based approach to AML Transaction Monitoring? Let’s break down the potential benefits.

Access to more accurate SAR reporting

An effective AML Transaction Monitoring system holistically assesses a customer’s profile. From there, it projects how their risk level will evolve, instead of assessing each transaction in isolation.

If the customer’s transaction triggers a rule that initiates a suspicious activity report (SAR). The solution bases the SAR on the facts of the transaction parties. More accurate SARs reduce the risk that the FI will face regulatory fines for non-compliance issues. It can also reduce the risk of public image damage or even criminal threats.

Generate fewer false positives

By producing more accurate SAR results based on risk, AML compliance teams can spend less time pursuing false positives. Too many false positives can strain AML compliance teams’ resources, making it easier for criminals to commit financial crimes and for money laundering schemes to go undetected. AML transaction monitoring systems deliver more accurate alerts, enabling compliance teams to focus their attention on quality alerts that identify high risk transactions.

Uncover new financial crime patterns

Many FIs build AML compliance programs based on a network of rules-based systems. However, this puts FIs with rules-based systems at a disadvantage since criminals will simply shift their tactics to avoid detection. Once the rules are changed, bad actors just change their tactics again. Using rules-based systems alone FIs will struggle to identify new fraud threats and patterns. Supporting rules-based AML Transaction Monitoring systems with AI and machine learning technology can reveal previously unknown or undetected patterns that raise suspicion. Further investigation sheds light on whether the new behavior is legitimate or if it’s indicative of money laundering activity. 

Break down internal data silos

Many banks rely on a series of interconnected and disjointed systems to manage their financial crime needs. This arrangement leads to communication gaps that enable fraud and money laundering activities to go undetected. The systems enable banks to implement a holistic view of the customer across multiple banking channels. With this view, different teams have a more accurate understanding of a customer’s risk level.

AML Transaction Monitoring systems are not just a necessary tool for financial institutions. They are a critical component of a comprehensive and effective anti-money laundering strategy. By adopting a risk-based approach, banks can improve the accuracy of suspicious activity reports, reduce false positives, uncover new financial crime patterns, and break down internal data silos. Implementing these systems will go a long way in protecting the integrity of financial institutions and safeguarding the global financial system from criminal activities.