The Human Side of Financial Crime: A Call for Efficient AML Regulations

An estimated $800 billion to $2 trillion is laundered worldwide each year. This figure has frustratingly gone unchanged for the better part of two decades. And as anti-money laundering practitioners, we know this estimate is too low. While banks and financial institutions have invested considerable resources into detection, prevention, and due diligence, the scale of money laundering has not diminished. In many cases, it is exploding. 

That’s why enhanced AML intelligence framework and regulations are necessary. However, it may ultimately be banks, not regulators, that create an environment for change.

Key Takeaways

• Between $800 billion and $2 trillion is laundered worldwide each year.
• An estimated 90% of money laundering crimes go undetected.
• More efficient AML regulations are emerging in the US, UK, and Singapore.
• Banks can embrace more intelligent AML solutions without waiting for new AML regulations.
• Financial institutions can build an intelligent and effective AML framework by focusing on the human element of financial crime, automating manual processes, and more.
• What’s more, banks can achieve this by augmenting, instead of replacing, their existing legacy AML systems.

A Brief History of Modern AML Regulations

I have been involved in stopping financial crime since 2001, dating back to the implementation of The USA PATRIOT Act. At that time, the estimates of the amount of money laundered each year were between 2-5% of the world’s GDP, and those estimates remain the same today in 2025. 

Back in 2001, banks substantially increased their anti-money laundering (AML) teams, implemented transaction monitoring detection technology, put in more Know Your Customer checks in their onboarding processes, and regularly screened outgoing payments for suspicious transactions. Unfortunately, all of this resulted in more work with endless false positive alert “hits” and never-ending due diligence requirements and processes. In many cases, these caused more work as bank customers would not respond to the bank’s inquiries. 

Much has improved since 2001. At the same time, much has not. This perspective is validated by recent estimates that say that 90% of money laundering crimes go undetected. Those involved in financial crime prevention understand the current state of alert levels and due diligence processes are unsustainable. 

Despite these challenges, many professionals in the industry remain committed to stopping financial crime. Yet, there is a strong sense of discouragement among many of the financial crime fighters I have worked with over the years. These committed actors who really want to stop financial crime and make a difference in the world need a new framework for AML regulations. 

Financial Crime’s Human Toll

Criminals have advanced their methods, using the latest AI and machine learning technology to perpetrate financial crime through some of the worst human crimes that affect society, including human trafficking, child exploitation, scams, and elder exploitation. All of these actions are fueled by greed and propelled by advancements in technology.

The consequences of these crimes extend far beyond financial losses—they devastate lives, stripping victims of their security, dignity, and futures. From a retiree losing their life savings to fraud or pig butchering scams or vulnerable individuals being trafficked through illicit financial networks, the human cost of financial crime is immeasurable.

To really put a dent in this massive problem, the current financial crime regulatory framework needs to change and move forward to motivate banks to respond effectively, especially since financial services are becoming increasingly faster and the risks of financial crime are growing just as quickly.

How AML Regulations Are Adapting

Regulators from around the globe have recently demonstrated interest in implementing a more efficient AML framework. Consider these recent developments:

• In July 2024, the United States’ Financial Crimes Enforcement Network (FinCEN)  released an Interagency Statement on the Issuance of the AML/CFT Program Notices of Proposed Rulemaking. The statement included the following language, “focuses attention and resources in a manner consistent with the risk profile of the financial institution; may include consideration and evaluation of innovative approaches to meet its AML/CFT compliance obligations.”
• The Monetary Authority of Singapore (MAS) actively encourages and supports the use of machine learning and data analytics for preventing money laundering, detect suspicious activity, and identify potential networks of illicit behavior. Essentially, MAS views machine learning as a key technology for financial institutions to enhance their AML efforts and compliance.
• The UK’s Financial Conduct Authority (FCA) recently issued Consultation Paper 24-9, outlining proposed guidance on transaction monitoring practices. The FCA emphasizes the importance of gaining a holistic view of customer behavior, encouraging financial institutions to monitor transactions at multiple levels to detect suspicious patterns more effectively. 

All of this attention by the regulatory bodies is promising, but change and action need to happen quickly. Direct regulatory policy change needs to come from these agencies so that financial institutions can shift the paradigm from managing financial and human crime to preventing it, from patching leaks to creating a solid foundation.

6 Ways FIs Can Embrace Intelligent AML Framework…Ahead of Regulatory Mandates

Instead of waiting for regulators to inform best practices or regulatory actions, FIs can lead the charge. Taking these steps enables banks to take the lead in protecting everyday people from serious harm, keeping criminals out of financial services, and adding humanity back into the process.

Here are six key steps financial institutions can take to build a truly intelligent and effective AML framework:

1. Prioritize the Human Element

Financial crime isn’t just about numbers. It’s about the real people whose lives are impacted by horrendous acts of criminality. By recognizing the devastating effects of human trafficking, slavery, romance scams, pig butchering, and other illicit activities, we can create a powerful impetus for change, even in the absence of pressure from AML regulations.

2. Automate Manual Processes

Free your analysts and compliance teams from tedious, repetitive tasks by automating data collection and integration. Embracing automation empowers your teams to focus on what matters most: identifying and investigating truly suspicious activity. This includes leveraging new data sources like ISO20022 payment messages for new threats and emerging patterns. Sending data to your AML transaction monitoring or screening solutions enables your organization to break down data silos between fraud and AML teams and connect suspicious patterns that might go unnoticed otherwise.

3. Modernize Transaction Monitoring

Traditional transaction monitoring systems are often outdated and struggle to keep pace with evolving criminal tactics. By augmenting existing systems with machine learning and advanced analytics, you can gain a more comprehensive and contextual view of transactional risk. 

4. Enhance KYC/Customer Due Diligence 

Static, periodic reviews are no longer sufficient. KYC processes must become dynamic, incorporating real-time data and behavioral insights to identify changes in customer risk profiles and trigger timely reviews. Data that meets the ISO20022 standards can significantly improve AML operations and due diligence investigations.

5. Leverage Intelligence for Context

Data is only valuable when it tells a story. By integrating device and network intelligence and applying machine learning for contextual evaluation, you can uncover hidden connections and understand the true nature of transactions and account openings, even when faced with falsified documentation.

6. Augment, Don’t Replace Legacy AML System

Modernizing your AML framework doesn’t necessarily require a complete overhaul. By strategically augmenting existing systems with intelligent capabilities, you can achieve significant improvements without the disruption and cost of a full rip-and-replace.

FIs Must Do the Right Thing….Even Without a Regulatory Mandate

This is the time for FIs to move forward, on their own, to a modern, more intelligent AML program, even if updated AML regulations are not currently in place. The move to a more proactive stance is a requisite to protect customer relationships and their reputation. 

Machine learning models can bring multiple disparate data points together, providing a comprehensive and contextual analysis of a transaction or its geolocation. This data enhances the due diligence process by flagging transactions coming from areas that were unusual for the customer.

The estimated figure of $800 billion to $2 trillion in laundered funds has been the default statistic on money laundering for too long now. Let’s move the needle forward and make this world a better place, beginning with every financial institution. Just think of the possibilities of contextually applying the data you have to reduce financial and human suffering.

• Blog: Enhancing AML Transparency with Smarter Data
• Report: The State of Anti-Money Laundering 2025
• Report: Top 18 Vendors or AML Transaction Monitoring
• Solution Sheet: AML Transaction Monitoring