Navigating Sanctions in a Faster Payments World: 4 Key AML Insights

The essential takeaways from Lynx’s Fireside Chat at the 2024 Financial Crime 360 Conference, featuring insights from experts Caroline Kennedy (Head of Risk & Compliance, PagoNxt) and Oliver Achkar (Sales Director, Lynx).

26 Nov 2024

AI
In the fast-paced world of instant payments, financial institutions (FIs) face evolving AML challenges including changing sanctions lists, high false positives, and inflexible legacy systems. It’s increasingly difficult to find balance between compliance, risk management, and customer experience.These dynamics set the stage for Lynx’s fireside chat “Navigating Sanctions in a Faster Payments World” at the Financial Crime 360 conference in London on November 19. Lucy King, Director of Global Alliances at Lynx, moderated a conversation with Caroline Kennedy, Head of Risk & Compliance at PagoNxt, and Oliver Achkar, Sales Director at Lynx.The conversation covered critical topics including false positives, common names, frequent watchlist updates, inflexible systems, evolving risks, and changing transaction formats. Here are the experts’ top four insights:

Insight 1: Reduce False Positives with High Quality Data and Advanced AI

False positives- names which are incorrectly identified as matching those on watchlists- are a widespread issue in AML watchlist screening. They often occur due to low quality data from customers or watchlists that makes it difficult to accurately match names.

Many AML vendors concentrate on developing detection methodologies like fuzzy matching- which returns names that are similar but don’t exactly match- without addressing the quality of the underlying data. In the context of faster payments and constantly evolving watchlists, this leads to more false positives and a higher investigative burden.

Addressing the False Positive Problem

Without a suite of legacy data to lean on- a common scenario for many smaller payment services providers (PSPs) and FinTechs- PagoNxt uses a variety of tools and data to reinform its screening engine, improve performance, and reduce false positives.

From the vendor side, Lynx leverages machine learning to tackle the false positive problem by first enriching watchlists with a host of name variations, creating a larger database of names to scan before cleansing and standardizing names across multiple languages and formats. Lynx’s advanced AI then calculates similarity scores in milliseconds. FIs using Lynx’s solution can customize this process based on their risk tolerance and compliance objectives, enabling quick and refined matching that lowers false positives.

Insight 2: Adapt to Changing Watchlists with Tailored List Rescreening

Another key AML challenge is effectively managing watchlist changes. Watchlists are frequently updated with new entries and updates as governments and global agencies develop new intelligence about risky customers and business entities. For example, recent sanctions against Russia in response to its invasion of Ukraine have caused numerous watchlist updates. Incorporating all watchlist changes and rescreening names after every update is a recipe for high false positives and overwhelmed investigation teams.

FIs need the ability to flexibly select which lists to screen and rescreen against. They also require capabilities to manage hits (matched names) efficiently. FIs that rely upon inflexible or outdated screening solutions are at a disadvantage here, as they can’t keep up with the pace of change.

Curated Watchlists and Rescreening

Lynx gives FIs the ability to curate watchlists and create watchlist filters specific to countries, channels, customer profiles, data types, and products, all while aligning with their compliance policies. In addition, Lynx AML’s Tailored Delta List feature allows firms to outline specific attributes that trigger rescreening. This ensures that only unique updates are received on the delta list, reducing false positives and improving alignment with each FI’s risk profile.

Insight 3: The Limitations of Rigid Systems and the Need for Real-Time Configurability

Legacy AML systems often require extensive software development and long wait times to adjust settings and integrate policy changes. This rigidity means that FIs using these systems can’t respond quickly to new risks or adjust their approach as their risk profile evolves.

More configurable screening solutions are needed in today’s ever-changing payments environment. This is particularly important for FIs offering new products and services, entering new or emerging markets, or experiencing rapid growth, as they constantly face evolving risks and need to adapt their controls.

Configurable Solutions

Fully configurable AML platforms help FIs update the watchlists they screen against, screening rules, and workflows in real time to deliver better performance. Streamlined self-service configurability is essential and helps firms respond and adapt to changing risks immediately while maintaining alignment with their risk tolerance and compliance needs.

For example, screenings of UK-based consumers and entities need to hone in on real-time authorized push payment fraud (APPF) risks given the high incidence of this type of fraud in the region, while screenings across the European Union must account for instant payments requirements and associated risks due to recent regulatory changes. FIs can use configurable solutions to quickly adapt to unique contexts, driving more accurate and compliance-aligned outcomes.

Lynx AML’s configurable watchlist management capabilities enable immediate screening changes. In addition, the solution’s case management features deliver adaptable workflows that can be updated directly from a web interface. This automates manual tasks and gives investigators more time to focus on high-impact alerts, while enabling executives to make data-driven decisions based on real-time metrics and organizational needs.

Insight 4: Use Scalable, Flexible, and Data-Agnostic Architecture to Achieve Compliance with Less Friction

FIs are screening more transaction and customer data than ever due to the massive volume of instant and cross-border payments. It’s difficult to manage so much data without slowing down the user experience, and customers often face long wait times as payment servicers investigate a growing number of false positives. FIs need solutions that accurately process data in real time to achieve compliance in a timely manner.

Scalable and Flexible Architecture

High-speed, large-volume screening demands a scalable and flexible architecture which can process thousands of transactions per second and respond immediately.

Lynx AML’s advanced AI-enabled similarity scoring matches names in milliseconds and the solution’s Watchlist Management module helps FIs tailor watchlist sources according to factors like country or business line. This flexible architecture helps firms quickly identify relevant risks in a fast-paced and high-volume transaction environment.

Data-Agnostic Interfaces

FIs also need to process cross-border payments across various data formats including ISO20022 and legacy messaging like SWIFT MT. While firms globally are moving to the ISO20022 standard, many- including Tier 1 firms- are unlikely to make the full transition by late 2025 when the format is scheduled to become the new standard.

A converter approach, whereby solutions convert incoming transactions to a standard format, can create problems including data loss and incorrect formatting. AML platforms which process various transaction formats natively offer the most streamlined approach.

Lynx’s AML solution is ISO20022 native and data-agnostic, giving FIs the ability to ingest any transaction data format. This helps firms easily update formats and accelerate their data transformation journeys.

Conclusion

As FIs take on emerging screening challenges in the age of faster payments, they must incorporate cutting-edge approaches and technologies to drive the best outcomes for financial crime detection, compliance, and customer experience. The most effective AML screening solutions:

  • Utilize AI to facilitate comprehensive coverage and reduce false positives
  • Offer tailored watchlist and screening methodologies to incorporate list changes without producing too many false positives
  • Leverage flexible architecture and self-service configurability
  • Are data-agnostic and process common transaction formats natively

Acknowledgements

Thank you to Lucy King for moderating the fireside chat and to Caroline Kennedy and Oliver Achkar for sharing their expert perspectives on key screening challenges and best practices.

Lucy King, Director of Global Alliances at Lynx,

Lynx AML

Lynx AML leverages advanced AI to detect financial crimes and streamline compliance operations, with core capabilities including transaction screening, name screening, and automated case management.

Interested to learn how you can improve AML detection, compliance, and operations with Lynx’s AI-driven solution? Request a demo today. 

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