Last year, $3.1 trillion in illicit funds flowed through the global financial system, fueled by hundreds of billions of dollars generated by predicate crimes, from drug trafficking to human trafficking, terrorist financing and fraud. As this global epidemic of financial crime unfolds, a lack of effective solutions for predicate crime detection, paired with an increasingly complex regulatory landscape, is limiting our ability to defend the integrity of the financial system. As an industry, we must recognize the challenges inherent in today’s regime and align with a new vision, focused on effectively detecting critical criminal typologies identified by the AML/CFT National Priorities, to stem the global financial crime epidemic.
The Imperative for a New Vision
“It has been an important priority for Treasury to issue this proposed rule that promotes a more effective and risk-based regulatory and supervisory regime that directs financial institutions to focus their AML/CFT programs on the highest priority threats.”
The release of FinCEN’s AML/CFT National Priorities ushered in a regulatory imperative for financial institutions to effectively detect and disrupt predicate crimes for money laundering. On June 28, FinCEN acted to reinforce this legislation, issuing a proposed rule that “would amend those regulations to explicitly require that [financial institution’s AML/CFT programs] be effective, risk-based, and reasonably designed”, increasing pressure on financial institutions to bolster their compliance programs at a time when resources are limited. In a recent survey, only 53% of respondents said they had adequate resources and technology to combat financial crime — a worrying number as criminals grow bolder and more connected than ever.
As our industry fights to keep pace, fettered by regulatory and operational challenges, billions of dollars in illicit funds flow to the most heinous crimes imaginable – and countless innocent people shoulder lifechanging consequences. But for many institutions whose investigation teams are inundated with false positives from current transaction monitoring approaches and disparate systems, effective detection is a daunting prospect, and substantial time and effort is often required to identify any suspicious activity. The world’s multi-trillion-dollar financial crime problem cannot be tempered by this status quo. Change is unavoidable — with an onus firmly on financial institutions to demonstrate effective monitoring, a new approach is desperately needed to uncover predicate crimes with precision.
A Targeted Approach to Detection
With pressure mounting, our industry needs a paradigm shift toward a targeted approach to AML/CFT that focuses on criminal typologies, enabling investigators to pinpoint activity indicative of predicate crimes and provide better insight to law enforcement while meeting ever-evolving compliance requirements. Targeted Typology Analytics is that solution — combining the latest advances in artificial intelligence (AI) with big data for a step change in detection.
Analyzing a range of consortium and behavioral data with advanced AI and machine learning, Targeted Typology Analytics look for patterns of criminal activity with exceptional proficiency, with typology-specific monitoring that delivers exceptional detection for predicate crimes such as human trafficking and terrorist financing. Together with important context-rich insights such as geographic maps and peer comparison charts, the result is improved investigations and enriched reporting to law enforcement, with fewer false positives and alert-to-SAR ratios as low as 1 in 7, far outperforming conventional transaction monitoring approaches.
Leveraging Decades of Expertise
For over 20 years, Nasdaq Verafin has embraced the vision for a targeted approach to detecting predicate crimes — helping financial institutions across the country respond proactively, not reactively, to emerging threats. With decades of experience and deep domain expertise, we’ve pioneered a growing library of Targeted Typology Analytics designed to drastically improve predicate crime detection and empower investigators to quickly ascertain risk and likelihood of suspicion.
Harnessing advanced AI approaches trained and tested on our immense consortium data set from across 2500 financial institution customers, Nasdaq Verafin’s Targeted Typology Analytics deliver context-rich insights and best-in-class performance. Our Targeted Typology Analytics for human trafficking and terrorist financing have already helped thousands of financial institutions detect and disrupt these predicate crimes, with 82% of human trafficking-related SARs filed to FinCEN in 2022 being submitted from our AML/CFT platform.
As financial crimes continue to evolve and the industry awaits further guidance from FinCEN on monitoring for predicates crimes, Nasdaq Verafin is also developing Targeted Typology Analytics for drug trafficking detection, money mule detection, and more that will also offer outstanding detection – all while continuously improving our current library of analytics based on red flags identified by FATF, law enforcement and other inputs.
Visioning Ahead
From billions of dollars in predicate crimes to rising costs and regulatory complexities, the financial industry is facing historic challenges in our efforts to protect the financial system. A shared vision is paramount. Our industry must embrace new technology that empowers AML teams to safely automate compliance tasks and realize efficiencies in investigation processes, liberating resources to be refocused on combating predicate crimes. This shift should occur in concert with embracing a targeted approach to detecting and disrupting predicate crimes, underpinned by advanced AI and consortium data, allowing financial institutions to achieve a step change in predicate crime detection and prevention.
For more information on Nasdaq Verafin’s Targeted Typology Analytics for predicate crimes, download our Feature Sheet.
About the Author:
FOUAD HASSOUNEH
Head of AML Product Strategy, Nasdaq Verafin
Since joining Nasdaq Verafin in 2013, Fouad has excelled in a wide range of roles. In his current role as Head of Product Strategy for AML, Fouad is responsible for defining the product vision, strategy, and roadmap. He helps Nasdaq Verafin deliver solutions that leverage artificial intelligence to effectively detect money laundering, while helping institutions maintain compliance. Working in close collaboration with Nasdaq Verafin colleagues, customers and senior stakeholders, Fouad applies his extensive knowledge of the AML/CFT and fraud landscapes to guide innovations and enhancements to product management and analytics. Fouad is passionate about creating value for customers and society by combating financial crime with cutting-edge technology.
