For all those involved in the fight against financial crime, FATF’s latest report, Opportunities and Challenges of New Technologies for AML/CFT, is an important read to help shape the future of AML and compliance.
The resounding message from FATF is loud and clear: new technologies enhance overall anti-money laundering (AML) and countering the financing of terrorism (CFT) capabilities. Technology improves the ability to monitor criminal activity and collect and visualise data while using resources more efficiently.
In particular, the application of machine learning and other artificial intelligence (AI) based tools can offer a solution to the costly phenomenon of defensive compliance that much of the private sector adopting a rule-based approach struggles to shake. This is because AI and machine learning tools allow for real-time, quick and more accurate data analysis – all of which saves time and cost in compliance programs.
All 70 pages of the report are a worthy read but if you don’t have time, here are our key takeaways:
1. AI can automatically monitor transactions and reduce the need for initial human review
FATF recommends the use of AI-enhanced transaction monitoring as it can allow regulated entities to comply with greater speed, accuracy, and efficiency. AI and machine learning are especially useful when applied to big data to strengthen ongoing monitoring, distinguish normal from suspicious activity in real-time, and filter cases that require additional investigation.
Machine learning, which is the currently the best-known form of AI, also provides the ability to automate the process of risk analysis partially or fully by analysing a greater volume of data and identifying emerging risks. This can increase the degree of confidence when applying risk-based measures.
2. Natural Language Processing and fuzzy matching tools overcome data quality issues and help reduce false positives in AML
FATF describes Natural Language Processing (NLP) as a branch of AI that enables computers to understand, interpret, and manipulate human language. NLP uses fuzzy logic, a logical technique that takes imprecise or approximate (fuzzy) data and processes it using multiple values to produce a useable (but imprecise) output.
Applying NLP and fuzzy matching tools to AML compliance allows issues associated with poor data quality (such as incomplete or distorted data) to be overcome and false positives and negatives to be efficiently reduced.
3. Distributed Ledger Technology may improve the traceability of transactions
FATF cautiously puts forward the use of distributed ledger technology (DLT) owing to its several potential benefits, including:
- The ability to make identity verification easier by improving transaction traceability on a cross border and even global basis.
- Increased monitoring possibilities because transactions could be managed via a single ledger and shared among several institutions across jurisdictions, or via interoperable ledgers.
- Improved management of customer due diligence requirements as well as greater cost effectiveness and a more accurate, quality-based data pool.
That said, FATF acknowledges DLT continues to pose challenges and raises significant concern from an AML/CFT perspective. Its use therefore needs to be closely monitored and further considered.
4. Digital solutions for customer due diligence will streamline onboarding processes
Applying new technologies, including digital ID and client screening/matching onboarding tools, can facilitate more streamlined onboarding processes adapted to the risk, context, and individual. Not only can this facilitate more effective compliance, but it can also improve customer experience.
Client screening and matching tools benefitting from NLP and advanced fuzzy matching tools allow elements of identification to be differentiated, like similar names. They can also overcome language differences and identify cross-references with adverse media information and different databases.
5. Application Programming Interfaces are essential to AML/CFT efforts
For AML/CFT, APIs (application programming interfaces) can connect KYC software to monitoring tools or risk assessment tools to customer risk profiles. Connecting such software can generate alerts and even alter risk classifications as behaviour changes.
APIs are particularly important in helping financial institutions overcome the difficulty of integrating many different - and often incompatible - systems, including specialised tools and legacy tech created by different developers.
6. Technology implementation challenges for AML can be overcome
The FATF report acknowledges the adoption of new tech is not without challenges, largely relating to regulatory or operational. Going forward, the need for clear support from FATF and national competent authorities for innovation in AML/CFT is paramount to increase private sector interest, investment and trust in new tech.
To help secure this support, FATF highlights that interpretability and explainability of tools for AML/CFT is key. Not only do regulated entities need to explain and remain responsible for their operations, but supervisors themselves must be able to understand the models used by AI tools to determine their accuracy and relevance.
7. Technologically active AML supervisors are integral to new tech adoption
FATF acknowledges that if it, along with supervisors, shows more active support for new technologies then this would help respond to the outstanding risk and trust concerns expressed by regulated entities. The role of technologically active supervisors, as is already the case in many jurisdictions, therefore becomes integral to new tech adoption.
FATF also acknowledges the need for greater collaboration between supervisors and regulated entities, specifically in the form of ongoing exchanges and cooperation rather than at specific events.
Final thoughts about FATF’s new technologies recommendations…
We at Napier are delighted to see this report and its support for technologies like AI, which powers everything that we do and helps our clients build robust AML/CFT programs that exceeds regulatory requirements.