The Role of Technology in Modern Anti-Money Laundering Services

Criminal activity is constantly changing and evolving.

Organised criminals are becoming more sophisticated in how they approach money laundering. Compliance teams and manual review just can’t keep up anymore.

Technology has evolved from a “nice to have” a decade ago, to a must-have now for organisations that are serious about preventing and detecting financial crime.

The great news is that modern technology is helping to level the playing field.

In this post we take a closer look at what we believe is the biggest thing to happen to modern anti money laundering services in the last few years. Artificial intelligence.

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Why Is Technology Important in AML Compliance?

Anti-money laundering services are more important than ever.

Eftsure research suggests that in 2023, a staggering $3.1 trillion was laundered through the financial system globally. That is NOT a typo. Trillions of dollars.

Traditional rules-based systems are creaking at the seams. Investigators are drowning in hundreds of alerts every day, the vast majority of which are false positives.

The explosion in transaction volumes combined with the ever-present threat from organised crime syndicates means manual review just isn’t an option anymore.

Working with AML consultants in UAE and other jurisdictions helps organisations source and implement cutting-edge technology that actually delivers.

The right technology stack helps to automate and accelerate AML investigations so compliance teams have the capacity to deal with all alerts.

Key Technologies Powering Anti-Money Laundering Services

The best modern AML compliance software stacks multiple technologies to power anti-money laundering services.

Artificial intelligence, real-time transaction monitoring, advanced analytics and big data are becoming the norm.

Let’s look at how each of these technologies supports modern anti-money laundering services.

Artificial Intelligence & Machine Learning

Artificial intelligence and machine learning are powering the next generation of AML tools.

These technologies work through vast datasets at speed to uncover patterns and anomalies.

AI systems learn from historical data to apply behavioural baselines to customers. Over time, as more data is fed into the system, the models become even smarter.

AI is particularly useful for working through hundreds of thousands of alerts and picking out real, unusual activity from everyday false positives.

Traditional rule-based software is set in stone.

The software cannot learn or adjust to the changing behaviour of customers over time. This is why AI is such a game-changer.

Real-Time Transaction Monitoring

AML services need to monitor transactions across every channel and data source.

Real-time AML transaction monitoring means analysing and assessing customer activity on an on-going basis, rather than waiting for end-of-day or end-of-week processing.

The ability to catch suspicious activity as soon as it happens has several key advantages:

• Fraudsters have less time to move funds before being flagged
• Investigations start earlier, giving compliance teams more time
• Staff build dynamic customer risk profiles based on transaction history

In the past, batch processing was normal. Compliance teams worked through transactions received in large data batches.

Now, in contrast, the ability to process in real time provides a major advantage.

Advanced Analytics & Big Data

The volume of financial transactions and data assets in banks is ever-increasing. As it is growing, financial services organisations generate and store a mind-boggling amount of data every single day.

Big data and advanced analytics allows this mass of data to be processed so that suspicious links and connections between transactions, customers, and accounts can be identified.

This makes it possible to piece together patterns of suspicious activity that might not trigger an alert on their own.

Someone may make a series of low-level deposits that individually fall below thresholds.

But when taken together, do they form part of a bigger scheme?

The analytics tools help draw together a number of dots on the wall in order to establish a bigger, money laundering picture.

How Artificial Intelligence Can Reduce False Positive Rates

False positives continue to cause headaches for financial institutions.

PwC reports that between 90-95% of risk alerts generated by traditional AML systems turn out to be false positives.

This means that 95% of the time compliance teams are chasing non-issues.

The result is a sense of frustration and wasted time.

Reducing false positive rates is a critical way to free up limited compliance resources.

Artificial intelligence is at the core of most modern anti-money laundering software.

AI uses multiple variables in order to understand what a “normal” transaction looks like for a specific customer or customer type.

This process is often referred to as “knowing the normal.”

Once the AI knows the normal, it can then use algorithms to understand when transactions deviate outside of this norm.

By setting different thresholds for different customers and transaction types, the false positive rates can drop dramatically.

Selecting the Right Technology Stack for Anti-Money Laundering Services

There are several key considerations when selecting which anti-money laundering services to work with.

Here are the four most important.

1. Scalability Can the AML service scale as the business grows?
2. Integration Does it plug into existing banking systems and data sources?
3. Compliance Is the solution fully compliant with FATF and local regulatory requirements?
4. Explainability Can the AI technology explain how it is scoring and flagging potential money laundering activity?

The optimal solution would use an ensemble approach, blending a number of different technologies and systems in order to create a single, joined-up view of suspicious activity.

Transaction monitoring

Customer due diligence and onboarding

Sanctions screening

Continuous transaction monitoring

Reporting

Case management

Process automation

…and more.

The key here is to select a single provider (or a handful of integrated providers) that can support your organisation’s AML needs end-to-end.

Wrapping It All Up

Technology is the most significant advancement in modern anti-money laundering services in recent years.

AI, real-time monitoring, and analytics tools are all playing their part in helping to automate and accelerate investigations.

While some organisations remain worried about AML being turned over to “robots,” the fact is that modern systems empower compliance teams to do their jobs better.

The ideal AML solution takes manual review out of the equation wherever possible while still allowing human judgement to play a critical role.

Artificial intelligence has helped level the playing field, and should be seen as a force multiplier rather than a threat to jobs.

If your organisation wants to get ahead of the competition and stop taking massive AML fines, it’s time to make a change.

Technology is no longer a “nice to have” but a competitive differentiator for organisations that implement the right tools for their unique AML compliance requirements.

Featured Image by Alexa from Pixabay