The fight against financial crime continues to pose major challenges to regulators and organisations worldwide.
Money laundering is estimated to be 2-5 % of global GDP, which is translated to up to EUR 1,87 trillion each year.*
In this article, Dan Sjöholm, Chief Strategy Officer at Trapets and founder of Trapets back in 2000, reflects on anti-money laundering efforts throughout the years, the most common challenges and lessons learned in this complex field.
About 15 years ago, the third EU AML Directive was introduced, significantly expanding the scope and requirements of anti-money laundering regulations.
This change affected many businesses, not only in the financial sector but also in other industries exposed to money laundering risks.
Since then, the anti-money laundering landscape has continued to evolve, with new regulations, standards, and best practices regularly emerging.
The threats and methods of money launderers have also become more sophisticated and diverse, requiring constant vigilance and adaptation from the regulated entities.
However, despite progress, companies still need help complying with and understanding regulations and obligations to combat financial crime effectively.
Challenges remain and grow even bigger due to four main factors:
Looking ahead, Dan Sjöholm identifies four key initiatives that still remain central in shaping effective anti-money laundering operations and can offer new ways to overcome the challenges mentioned above:
1. Reducing system dependencies
Companies will seek to reduce their dependence on internal and external parties for their anti-money laundering and know-your-customer solutions.
This will require more flexibility and autonomy, from software vendors such as Trapets, to companies and users managing and updating their systems and processes.
2. Using data in new ways
Companies must leverage more data sources, both from their own customers and external providers, to enhance their anti-money laundering capabilities and accuracy.
Proactively using data in their transaction monitoring and risk assessment activities will be crucial to stay ahead.
3. Automating AML processes
Companies must pursue, explore and implement more automation in their anti-money laundering operations, such as customer due diligence, alert investigation, and reporting functions.
Reducing time, resources, and money will be necessary to improve compliance performance and quality to operate more efficiently.
4. Adoption of artificial intelligence and machine learning
Companies must continue experimenting with and adopting artificial intelligence and machine learning techniques in their anti-money laundering solutions, especially for pattern recognition and anomaly detection.
While these technologies offer great opportunities, companies must ensure that these techniques live up to transparency, explainability, and accountability to regulators and themselves.
While significant progress has been made against financial crime in the past few years, much work remains to be done.
Companies must continue to innovate and adapt their anti-money laundering solutions to keep up with the changing landscape of financial crime.
By embracing new technologies, automating AML processes, and using data in new ways, companies can reduce the burden of compliance while enhancing their ability to prevent and detect financial crime.
Ultimately, the success of the anti-money laundering field will depend on the collaboration and cooperation between stakeholders, from regulators and law enforcement to businesses and technology providers.
Sources:
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