When it comes to monitoring transactions for money laundering and financial crime risk, the devil is in the details. Regulations require financial institutions to implement an extensive anti-money laundering (AML) programme, including suspicious activity monitoring. But who decides what is considered suspicious? And how can financial institutions ensure they are mitigating their risks?
Financial institutions have historically taken a broad remit, positioning themselves to address ongoing tech limitations and changes in regulatory guidance. However, this approach has resulted in false positives, overwhelmed AML teams, and provided near-zero visibility into unknown risks.
What’s the solution? Anti-financial crime professionals must transform how they monitor and detect money laundering and put a laser focus on making effectiveness a top priority. And the good news is evolution is relatively straightforward.
We don’t need to accept the repercussions of an aggressive approach to maximise efficiency and effectiveness. The industry landscape has evolved. AML teams can reset their performance expectations beyond compliance to focus on the truly suspicious activity instead.
The latest advances are crucial to establishing a transaction monitoring (TM) system fit for purpose in 2023. How can an AML programme created years before Teslas, iPhones, and ChatGPT combat sophisticated financial crime today? It can’t. Fortunately, TM technology has come a long way since then, as has regulator acceptance of these technologies.
Thanks to recent innovations, FIs can take an entity-centric approach to understanding and monitoring customer risks. By cultivating a holistic understanding of each entity and its network, FIs can detect previously undetectable suspicious activity and turbocharge alert quality.
Technologies like AI and machine learning are head-turners when it comes to detecting more suspicious activity, but they’re not infallible. It’s paramount that organisations use advanced analytics to complement existing rules-based detection instead of replacing it. Why? Because rules check AI biases, ensuring complete coverage of all known typologies. Rules can also enrich machine learning development as engineered features, providing more robust detection and explainability. Organisations must be able to address new threats quickly – rules can instantaneously meet that need, often outweighing the development and training time needed for new machine learning models.
AML teams’ understanding of their customer will become increasingly comprehensive over the next five years. State-of-the-art data enrichment, entity resolution, and network analytics capabilities can settle duplicate records, resolve message counterparties, enrich profiles with relevant third-party risk information, and identify non-explicit entity relationships. This comprehensive understanding will allow institutions to dig deeper into indirect and hidden risks and extend coverage to detect complex or previously unseen money laundering typologies.
While privacy concerns can hinder data sharing, without collective industry insights into financial crime, emerging threats, and typologies, the most competent criminals will always find ways to gain the upper hand. Technology will unlock privacy-safe collaboration where other programmes fall short, breaking down industry silos and skyrocketing the prevalence of federated learning, suspicious entity sharing, and cross-industry networks.
Effectiveness doesn’t stop after detection. As organisations adopt advanced analytics to zero in on suspicious activity, feedback after investigations will become pivotal. With this intelligence, machine learning, and simulation teams can refine detection models and customer segmentation, lowering false-positive rates. Teams can also use historical data to minimise manual work and investigation times by shaping workflow, alert escalation, and alert hibernation procedures.
It’s inevitable: The evolution of transaction monitoring will change the face of compliance organisations. Advancements in technology will streamline the alerting process. As a result, there will be less demand for junior-level investigators involved in triaging the alerts. Solutions will auto-close many false positives that these investigators are addressing today. And in other cases, they no longer generate these alerts.
The introduction of new analytics will increase the number of true positives. The analytics will identify schemes that current methods are not flagging today. The complexity of these alerts will increase, driving the demand for more senior-level investigators.
However, no technological innovation comes without a cost. They’re complex. They require knowledgeable resources and data science experts. AML know-how will prove to be essential to implementing current technologies effectively. As a result, compliance organisations will begin to create new technology functions dedicated to their organisation.
On the other hand, less is more. As technologies shift to the cloud, fewer compliance-focused IT individuals will be needed to maintain technology infrastructure. Solutions providers will start carrying that expertise in place of FIs.
We’re at a turning point in transaction monitoring. We have all the tools needed to detect money laundering more accurately and focus on genuinely suspicious activity. It’s time to stop chasing false positives in the name of compliance and fight financial crime!
If you’d like to find out more about the future of transaction monitoring and how technology can drastically improve your transaction monitoring detection, check out this video or contact NICE Actimize today.
This editorial was initially published in the Financial Crime and Fraud Report 2023 which dives into the captivating world of fraud management, digital onboarding, and financial crime in the financial services industry. You can download your free copy here.
Ted Sausen, CAMS, is an AML SME at NICE Actimize. He has 25+ years of experience implementing global enterprise solutions. Before Actimize, he was an SVP at a large financial institution and led the Global Compliance Analytics and Technology group.
NICE Actimize is the largest provider of financial crime, risk, and compliance solutions for financial institutions. The company offers real-time, cross-channel fraud prevention, anti-money laundering detection, and trading surveillance products that address payment fraud, cybercrime, sanctions monitoring, market abuse, customer due diligence, and insider trading. Find us at www.niceactimize.com.
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