Canadian institutions are under greater pressure than ever to improve anti-money laundering (AML) operations. Adopting advanced technology is no longer just an opportunity but an imperative if banks are to close operational gaps and avoid financial penalties. A proactive approach also opens the door to cost-efficiencies and international growth.
Canadian banks can no longer ignore the pressure to improve AML operations. The facts speak for themselves. FinTRAC, Canada’s national financial intelligence agency, has recently levied fines against major institutions for deficiencies in AML compliance. Some Tier one banks have faced publicly announced fines, while others, are grappling with undisclosed penalties in Canada and the US.1,2
While modest on a global scale, recent fines such as the $7.4CAD million levied against a Tier one bank in 2023 stand as the largest in Canadian history – and signal a more aggressive regulatory stance and a decreased tolerance for backlogs and inadequate transaction monitoring.3 With a Financial Action Task Force (FATF) evaluation of Canada’s AML policies scheduled for 2025, FinTRAC CEO Sarah Paquet has stated clearly that the regulator will no longer tolerate lax compliance.4,5
The sector is also digesting the findings of the Cullen Commission inquiry into money laundering in British Columbia. The Commission’s final report exposed weaknesses in AML controls and is expected to shape upcoming federal legislation.6 Last year’s Consultation on Strengthening Canada's Anti-Money Laundering and Anti-Terrorist Financing regime highlighted examples of how these measures may unfold.7
Alongside regulation, banks must also come to terms with a surge in criminal activity targeting the financial sector. Estimates of so-called ‘snow washing’ suggest that $45billion to $113billion of dirty money is laundered in Canada each year.8 Cryptocurrencies and artificial intelligence are increasingly being used by criminals for illegal activities.9
To make things worse, many banks still struggle with inefficient transaction monitoring. Traditional systems often generate a high volume of false positives, overwhelming AML investigators and hindering their ability to identify suspicious activity. A lack of robust feedback mechanisms within AML programs also makes it difficult to assess their effectiveness.
All this suggests that financial institutions are likely to face stricter enforcement mechanisms, mirroring those in the US and Europe where stricter rules and hefty fines are part of the landscape.
Addressing these concerns is key, but banks should also seek to integrate their compliance strategies within broader digital transformation initiatives. This includes leveraging artificial intelligence technologies that can not only support compliance, but also offer long-term strategic and operational advantages in other areas of the business.
How can Canadian banks step up? Temporary fixes will not satisfy regulators with a keen eye for inadequate surveillance, large backlogs, and understaffing. Instead, banks will need to make significant investment in AML resources to avoid fines and reputational damage.
Obstacles remain, however. Many banks persist with inadequate KYC and customer due diligence procedures, where insufficient customer background checks or verification of source of funds create vulnerabilities that money launderers can exploit.
Another issue is the widespread presence of data silos and disparate systems that can result in data errors while impeding company-wide initiatives. Underinvestment in personnel and technology is also a challenge in environments marked by stringent cost controls. Low employee awareness of regulatory developments is common, especially in large organizations with high employee turnover.
By acting with clarity and determination, banks can embrace the business opportunities afforded by an effective AML program. Strategic investment in people, processes and technology opens the door to significant cost reduction and expansion.
Banks should also harness the latest AI tools to boost their AML efforts. Canadian institutions are well-positioned in this respect thanks to their experience with machine learning (ML) software. These initiatives have demonstrably improved fraud detection, largely through enhanced accuracy, reduced false positives, and faster detection in real time or near-real time.
However, this is just the tip of the iceberg. Transaction fraud is characterized by large datasets or labelled data, so there is an untapped opportunity for unsupervised learning. AI also has potential in the field of predictive analytics. By leveraging historical data, ML models can forecast future trends and identify potential money laundering activities. This proactive approach enables banks to strategically allocate resources and tailor compliance strategies to emerging threats.
Generative AI also offers exciting possibilities. While it cannot yet be considered sufficiently mature for primary detection, it has exciting potential at the secondary stage. This includes assisting investigators tasked with completing suspicious transaction reports (STRs). It is not hard to imagine a large language model trained to collate digital sources in order to help complete Part G (where banks are expected to detail the narrative for suspicion).10
Additionally, GenAI could be used for quality control, flagging missing details or areas for improvement within the report itself. It could also be deployed to screen large, unstructured datasets, such as newsfeeds, to identify negative coverage of the subject of an STR.
While we are not there yet, some vendors are developing solutions that provide explainable AI, a crucial feature if decisions are ever fully automated and challenged. However, any responsible implementation of AI in AML still requires collaboration between financial institutions, technology providers, and regulators to address data privacy concerns and navigate regulatory hurdles.
Building on advancements in AI, banks may also need to leverage external resources and expertise to optimize their AML operations. Activities where a strategic partner brings value include regular assessments of a bank's Target Operating Model (TOM) and existing AML/CTF (combatting terrorism financing) capabilities. This is crucial when identifying areas for improvement and ensuring compliance. Seamless integration of innovative solutions and vendor transitions are also vital for maintaining program effectiveness.
Optimization is also key to maximizing the efficiency and effectiveness of any AML/CTF program. Banks should seek guidance in order to improve data quality, implement remediation strategies, and ensure clear data lineage. GenAI solutions tailored to specific needs, such as customer risk rating or investigation functions, can further enhance the program's efficiency and consistency, especially when dealing with large datasets. But they require the input of an expert for successful deployment.
External resources can also help address backlogs of alerts, cases, and KYC. Techniques such as ‘rules on rules’ automation can streamline backlog refinement, while a combination of manual investigations and effective models for onshore, nearshore, and offshore operations ensures a comprehensive approach. Quality assurance processes throughout this remediation process guarantee accuracy and efficiency.
To better manage the cost of their AML transformation, banks should also consider outsourced Managed AML Services. These services encompass onboarding, screening, customer data refresh, and managing alert and investigation backlogs. This approach not only helps maintain compliance but also enhances operational efficiency and reduces overhead costs, allowing the bank to focus on its core business.
In conclusion, financial institutions are poised to enter a new era of AML security, where they can equal or even surpass their global counterparts – but they need to act now. Putting off AML investments is a false economy that leads to higher costs overall while increasing exposure to criminal activity and financial penalties. Investing early offers the opportunity to tackle efficiency issues, stay on the right side of the regulators and accelerate digital transformation including AI initiatives.
Furthermore, partnering with a trusted advisor with proven expertise in AML best practices can provide invaluable guidance and support throughout the transformation journey. This collaborative approach empowers financial institutions to not only meet compliance requirements but also optimize their AML operations for long-term efficiency and effectiveness.
References
1 https://fintrac-canafe.canada.ca/new-neuf/nr/2023-12-07-eng
2 https://fintrac-canafe.canada.ca/new-neuf/nr/2023-12-05-eng
3 https://www.cbc.ca/news/business/rbc-financial-intelligence-agency-penalty-1.7049479
4 https://www.torys.com/about-us/news-and-media/2023/12/canadas-antimoney-laundering-policies-set-to-be-evaluated-in-2025
5 https://www.theglobeandmail.com/business/commentary/article-trudeau-government-financial-crime/
6 https://cullencommission.ca/files/reports/CullenCommission-FinalReport-Full.pdf
7 https://www.canada.ca/content/dam/fin/consultations/2023/Consultation-amlatfr-rclrpcfat-eng.pdf
8 https://publications.gc.ca/collections/collection_2021/scrc-cisc/PS61-39-2020-eng.pdf
9 https://www.prnewswire.com/news-releases/study-reveals-annual-cost-of-financial-crime-compliance-totals-61-billion-in-the-united-states-and-canada-302064989.html
10 https://fintrac-canafe.canada.ca/guidance-directives/transaction-operation/Guide3/str-eng#s6