Regulatory expectations are evolving: How robust is your AML program?

profile picture Ferreneik Betton 6 min read
AML compliance officer

Managing financial crime is very complex and presents several challenges for financial institutions to develop robust anti-money laundering (AML) programs and meet compliance requirements.

AML compliance officers understand the importance of keeping one step ahead of criminals trying to find weak points in their financial systems to exploit. Continuous discussions by industry leaders at the forefront of combating financial crimes agree that more needs to be done sooner to detect and prevent money launderers from misusing systems. Thought leader Kevin Buehler from McKinsey wisely points out that “the stakes in this fight have never been higher for financial institutions. Money launderers are using increasingly sophisticated methods to avoid detection, and regulators are pressing for improved efficacy in anti-money laundering (AML) programs.” 

However, it is proving a more significant challenge to keep up with the new inventive ways criminals are testing their AML systems while ensuring they comply with AML regulations. In this article, we’ll examine the challenges anti-money laundering professionals face when making a more robust AML program to combat the increase in financial crime. 


What challenges are slowing the progress of more effective and efficient AML programs? 

It is widely known that financial institutions are undergoing vast digital transformations to remain competitive and innovative with the types of financial services provided to customers. Legacy systems are one aspect slowing their progress to adopt innovations and digitalise internal processes. Inherently, legacy systems affect AML programs’ potential to detect and identify the source of money laundering or the ability to prevent it. 

Legacy systems are one of the several major challenges slowing the prioritisation of an effective and efficient AML program. Here are four of the significant difficulties further slowing change. 

1. Regulatory pressures and the cost of compliance  

Anti-money laundering professionals all believe in the need for regulations to help prevent the misuse of their financial institution’s services. It is challenging to ensure that AML programs sufficiently meet the increasing volume and complexity of regulations.

In addition, institutions are estimated to spend billions each year in combatting financial crime. A survey commissioned by Refinitiv, one of the world’s largest financial markets data and infrastructure providers, reported that 3.1 per cent of annual turnover is spent combating financial crime, representing a sum of $1.28 trillion for organisations surveyed from 19 countries. 

Conversely, failure to comply can result in hefty fines. According to Global Investigations Review, enforcement actions and penalties for non-compliance with AML regulations continue to increase. They state that globally, there were 58 AML penalties in 2019 at a total of US$8.14 billion, compared to 29 penalties totalling US$4.27 billion in 2018. In 2020, global AML fines for financial institutions increased again to more than US$10.3 billion.

As this shift occurs, financial institutions are further challenged to meet stringent regulatory and compliance requirements while remaining fiercely competitive and providing a trusted service. 


2. Expensive false positives not detecting authentic illicit activities

Financial institutions must have many layers of defence for their AML programs to detect potential illicit activities. Customer Due Diligence (CDD) is at the centre of an effective AML program. Magazine ACAMS Today highlights that, “banks need to conduct due diligence on business operations, industries, customer characteristics and regions, in order to obtain adequate, complete and truthful customer information as the basis of analyses.” 

The second is continued monitoring and screening of those customers and their transaction habits to identify any illicit transactions. Despite institutions setting these measures in their systems, the current controls in place to monitor customer behaviour are not evolved enough and, in some cases, are too sensitive in their detection of potential illicit activity. 

This leads to innocent customers incorrectly being flagged as performing suspicious activities. As a result, institutions face costly false positives yearly and struggle to reduce those. Reportedly on average, 55 per cent of ‘false positives’ and inefficiencies can be eradicated by the most modern systems, accounting for 42 per cent of institutions’ AML costs. That equates to £2.7bn.


3. Inability to detect certain criminal activities  

In 2020, the EU expanded their AML regulations to include more offences that fall under money laundering. The EU sixth anti-money laundering directive (6AMLD) now requires institutions to acquire data to meet new transaction monitoring that can better spot money gained from human trafficking. 

This presents a challenge for AML compliance officers who, according to BusinessWire, admitted to having to report and investigate criminal financial activity linked to human trafficking. Almost three-quarters (75 per cent) aren’t confident in their ability to identify human trafficking signs amongst transactions.

It is becoming hard for institutions to keep up with newer criminal methods and the use of technology to go undetected. Criminals continue to take advantage of the loopholes in regulations and AML programs


4. Institutions left vulnerable to crime during the pandemic 

During the most challenging moments of the pandemic, many industries, particularly financial institutions, had to close their physical stores and rapidly adapt their systems to deal with the increased use of digital services. Unsurprisingly, there was an increase in fraud and cybercrimes. The Financial Action Task Force (FATF)  COVID-19-related Money Laundering and Terrorist Financing report state that, “the increase in COVID-19-related crimes, such as fraud, cybercrime, misdirection or exploitation of government funds or international financial assistance, is creating new sources of proceeds for illicit actors.”  

Institutions challenged to improve older AML programs are faced with an increase in smarter criminal activity and advanced attacks. 


AI and machine learning improving AML programs

Regulators are encouraging financial institutions to move towards a risk-based approach faster and encourage the use of AI and machine learning. 

For instance, in 2020, on the gathering of experts from the Spanish and European banking sector, Global Head of Supervisors, Regulation & Compliance at BBVA, Eduardo Arbizu pinpointed that technical challenges facing institutions must improve in the fight against money laundering. Arbizu explained, “[w]e must leverage technology, especially artificial intelligence and big data, in our anti-money laundering efforts. There is a long way to go; there are still legal hurdles we need to overcome, but, undoubtedly, we have to rely on technological solutions that help us improve”. 

As we lean more towards the ever-increasing use of data, conventional AML programs cannot keep up with criminals using even more sophisticated methods. To allow AML compliance officers to effectively and efficiently future proof their institutions, artificial intelligence (AI) and machine learning can help in the fight against financial crime.  

If you would like to learn more about how AI and machine learning can help build better AML programs, you can read more about it on our blog.