Fighting Financial Crime Effectively – Are we getting it wrong?
July 19th, 2021
Over the span of the last decade, there has been a seemingly unstoppable growth in financial crime and the predicate crimes that feed it. This has caused anti-money laundering (AML) efforts to become a top priority for financial services organisations (FSOs). However, financial crimes and money laundering techniques have become far more sophisticated and continue to evolve. The stakes for FSOs have never been higher.
The question we all need to ask ourselves is whether or not the current technology stacks used by FSOs are effective at fighting financial crime – after all, the people involved in AML efforts have the right intentions and work extremely hard. It would not be correct to say, however, that current efforts are stopping financial crime in a major way. The top echelons of organized criminal groups are still, in the majority of cases, getting away with it – with their lavish lifestyles, expensive cars, luxury yachts and extreme indulgences – all funded with dirty money.
As a matter of fact, it’s estimated in a report by the United Nations Office On Drugs and Crime (UNODC) that illicit wealth makes up between 2 to 5 percent of global GDP around the world, which accounts for up to 3.5 trillion USD per year. Despite the best efforts of FSOs and law enforcement to detect illicit wealth, only 1 percent is identified and the vast majority goes through to circulate in the economy. In other terms, according to data provided by the National Crime Agency (NCA), as much as $100 billion USD is laundered annually through the UK. Of that, UK law enforcement has seized only £216 million GBP in the years 2018 and 2019.
The Problem With Encouraging a Tick Box Approach
It is not a stretch to say that part of the reason why current approaches have been rather ineffective when it comes to fighting financial crimes is because of the prevalence of tick box culture when it comes to policing and filing SARs. In 2018 in the UK, 463,938 SARs resulted in only 28 direct cases and 40 arrests. The number of SARs filed is ballooning; in 2020 there were over 570,000 SARs filed and in 2021 nearly 750,000 SARs were filed to UK law enforcement. This is a significant increase in filings and, in short, law enforcement don’t have the resources to action all of these SARs. Furthermore, based on information which came out of the FinCEN leaks, a number of these SARs will be unusable by law enforcement as they will likely contain insufficient intelligence to do any real preventative crime fighting.
The current system encourages a bureaucratic tick box approach to filing cases. In fact, some people would even call this “defensive filing.” The risk of not filing is potential regulatory or criminal litigation, yet on the contrary, there is no penalty for overfilling. With this, Money Laundering Reporting Officers (MLROs) and Bank Secrecy Act Officers (BSAs) do not see a downside in filing, so they do it despite not having sufficient information on the case.
Out of the 150,000 police officers in the UK, only a small percentage are dedicated to financial crime. Hundreds of thousands of SARs being handled by only a thousand or so police officers presents some clear problems.
SAR quality could be increased quickly if all financial services authorities followed the same principles as law enforcement when obtaining and recording information. This is known as the 5WH model. The questions to be asked and answered in a SAR are:
- Who is involved in the transaction(s)?
- When did the suspicious activity occur?
- What have the subjects done?
- Why are you suspicious?
- Where did it happen (jurisdictions, organisations involved or other identifiable locations)?
- How is the reporting organisation involved?
Unless there is sufficient governance around SAR filings within FSOs that requires this basic information to be understood and reported by investigation teams, then a large number of SARs are simply not going to be useful in stopping financial crime.
A Holistic and Data-Driven Approach Moving Forward
In order for efforts for identifying and stopping financial crime to be effective, the processes and IT systems that are directly involved cannot be siloed. A bank may have a Know Your Customer (KYC) system, as well infrastructure for financial crime detection with AI and machine learning, but that doesn’t mean very much when these processes are isolated from each other.
To get the best out of AML solutions, FSOs must manage the lifecycle risk of the customer with the holistically. It is imperative that the customer is understood and their risk assessed at the first point they try to access services, all the way through to the time the customer exits the relationship. We call this Customer Lifecycle Risk Management. This can be done with a few key approaches, which are as follows:
Approach # 1: A More Effective Onboarding Process
The same way you would not let a stranger into your house through the front door, you should not openly let people have access to your FSO. This is the absolute most effective approach to stopping criminals from pushing their dirty money into the legitimate economy.
Having a data-driven approach to stopping criminals at the front door does not only mean using internal data of the customer based on the information that is given to you, external data such as those that can be found through social media platforms, adverse media sites, credit agencies and other intelligence content also need to be considered.
Approach # 2: Data-Driven Ongoing Monitoring
Even though stopping criminals at the onboarding process is the most effective approach, it is inevitable that some will get through because money laundering techniques have become more sophisticated and continue to evolve. That’s why there is a need for constant monitoring.
Organizations should adopt a contextual monitoring and alerting approach, introducing advanced technology solutions containing advanced algorithms such as AI and machine learning. This technology will be able to tell whether a customer’s profile and behavior is normal or abnormal. There’s also a need to get a fully accurate risk profile for the customer, not just based on traditional metrics but with a more contextual understanding of the customer, their behaviour, their activity and ultimately their risk across the entire organisation. This understanding should not just be based on internal information held on the customer, but also third-party, external information.
Approach # 3: Transaction Monitoring with AI and Machine Learning
As mentioned above, FSOs need to take advantage of the rapid progress in machine learning and AI. One can even say that the tech stack of an FSO cannot be complete without using machine learning algorithms to detect suspicious transactions.
The novelty of AI and machine learning stems from its ability to provide, better, higher quality alerts. This technology is proven to eliminate the noise and reduce false positive alerts by as much as 60. These algorithms can also be used to predict the likelihood of an alert resulting in a SAR, ensuring the efforts of investigation teams are focused on the truly suspicious activity. Lastly, machine learning algorithms constantly refine themselves and learn as alerts are investigated and dispositioned, driving continued improvements in the effectiveness of the detection engine.
All of these approaches used in sync, matched with machine learning, AI and better data, will lead to improved detection, better investigations and higher quality outcomes, in a fully compliant and effective way. Systems cannot be siloed – KYC, transaction monitoring and screening all need to be connected and work in harmony. If these systems work harmoniously together, law enforcement officers will get what they need in a timely manner, helping them make more informed decisions and stop the criminals in their tracks. Not only will this help law enforcement fight crime, but it can also reduce customer friction and enhance experience of innocent customers in the organization by allowing the genuine customers to continue to use services without being delayed due to false compliance alerts.
Intelligent Solutions with a Human Touch
Of course, as effective as having a modernized technology stack that makes use of AIis, this is not the only answer. Compliance officers and front-line staff at FSOs need to be well educated on new typologies and threats, ensuring they’re alert to spot issues. Training needs to be ongoing and accessible to all relevant staff, reducing the risk that activity will be missed or not escalated. There needs to be a greater focus on outcomes and not just focusing on ‘am I complying with the regulations?’.
For every one of us in financial crime compliance, the future of AML and the fight against the criminals is in our hands. We most start assessing and obtaining relevant data and information and use have solutions that provide us with the clarity and consistency to use that information in an appropriate and accurate way. Smarter solutions, after all, require a human touch to truly make an impact. With the right tools in place, constant controls, shared commitment to improving outcomes and the better use of data, it won’t matter too much that money laundering efforts have evolved — efforts to stop these criminals will evolve faster. Together, we can move the needle and be much more effective in the fight against financial crime.