Card Fraud

How Argentina’s Policy Impacts AML Controls 

Posted on by Nuria Herranz

Alyssa Iyer

Argentina’s latest financial policies are making headlines, particularly the government’s effort to draw hidden dollars out of the shadows and into the formal banking system. Central to that effort is a significant shift: raising the thresholds for reporting large cash deposits and purchases of real estate or vehicles. But what does this mean for banks and why should everyday citizens care?  

To encourage Argentines to deposit previously undeclared cash, the government has nearly doubled the reporting threshold. Under the updated rules, banks are now required to notify authorities only when a person deposits more than 40 times the monthly minimum wage in cash, as outlined in Ley 25.246. Similar adjustments have been made for cash-intensive purchases, such as property and vehicles. Additionally, financial institutions can no longer rely solely on tax returns to confirm a customer’s identity during onboarding.

At first glance, these resolutions might seem to indicate that regulatory requirements are relaxing. But the foundational obligations under Argentina’s anti-money laundering (AML) regime remain firmly in place. Banks are required under Argentina’s AML regulation to monitor all their customers’ transactions, including all cash transactions, not just those at or above the government reporting threshold. And they must investigate transactions that deviate from expected financial behavior. Though changes will need to be made to policies and systems to reflect the new reality, the foundational AML requirements remain intact.  

This continuity is especially important in light of broader economic policy shifts. The government’s cash normalization plan is expected to increase the flow of physical currency into the banking system, reintroducing cash into formal channels. While this move can support financial inclusion and economic stability, it also heightens exposure to the inherent risks of cash: limited traceability and a degree of anonymity that make it attractive for money laundering. 

It’s important to recognize that holding cash is not illegal. Many individuals do so for entirely legitimate reasons, such as safeguarding their savings against inflation. However, cash may in some cases  originate from illicit sources, and individuals involved may be unwilling to provide information that could reveal the true origin of their funds. To avoid detection, some may engage in “structuring”, a practice involving repeated cash deposits just below mandatory reporting thresholds or spreading deposits over several days. 

These behaviors are among the high-risk typologies outlined in Resolution 14/2023, which remain relevant in today’s context. For financial institutions, having a comprehensive view of the customer across behavior, transaction history, and expected activity can support stronger assessments of whether the volume, frequency, and patterns of cash movement reflect legitimate use or indicate elevated risk. 

Furthermore, because banks can no longer rely on tax documents for client onboarding or verification, they must adopt alternative methods to confirm a customer’s identity and financial profile. In addition to Know Your Customer (KYC) practices, critical components of that holistic risk profile include understanding the customer’s line of business to better gauge the potential source of funds, as well as screening customers for sanctions, adverse media or PEP (Politically Exposed Person) status. Having these insights helps to assess whether cash activity aligns with the customer´s risk profile and source of funds.   

These policy changes present both an opportunity and a challenge. They offer a chance to bring more funds into the formal economy, while also requiring financial institutions to sharpen their oversight. These changes may prompt banks to review their  AML controls, enhance customer due diligence and invest in tools that provide an understanding of customer behavior and risk in an effective manner.  

By taking a proactive, risk-based approach, financial institutions can help ensure that this new chapter in Argentina’s financial policy leads to sustainable growth, not unintended exposure.  

 

Lynx mentioned in a Gartner report

Posted on by davidsanchez
Emerging AI technologies are transforming the fight against financial crime with real-time detection and prevention capabilities, improved risk scoring, and reduced false positives. New paradigms define which solutions make the largest impact in protecting global financial systems: AI-enabled technology must not only demonstrate accuracy but also must meet explainability and regulatory demands to resonate with customers. Trust, transparency, and privacy are at a premium.

AI is Transforming Financial Crime Prevention

In the age of real-time financial crime, reactive and rigid approaches are no longer viable. Fraud and money laundering can occur digitally in just seconds. Illicit accounts and payments operate in real time. Constant watchlist changes, complex screening demands, and stringent AML regulations add to the challenges. AI technologies present a path forward to staying a step ahead of criminals. Pre-crime platforms proactively address financial crimes by using AI to analyze historical data and identify criminal patterns in real-time data. However, these innovations face several obstacles. AI and machine learning (ML) technologies must integrate a vast amount of threat intelligence data from varied sources in real time. Pre-crime solutions must also be tailored to meet industry and organization-specific needs. At the same time, robust AI data governance is necessary to ensure that AI models use high-quality training data in an explainable manner to mitigate bias, excessive false positives, and unintended risks. Privacy and transparency have become essential to developing trust, a key element of successful adoption and impact. Lynx’s AI-enabled solutions proactively detect financial crimes, with data governance and model transparency at the foundation of our approach.

Enterprise-Wide Fraud and Money Mule Detection with Daily Adaptive Models and Lynx Flex

Lynx Fraud Prevention and Money Mule Account Detection leverage Daily Adaptive Models (DAMs), self-learning AI models that update daily to stay ahead of the latest fraudster and money mule techniques, customer behaviors, and payment technologies. DAMs utilize supervised ML to learn from past fraud and money muling and, once deployed, detect suspicious transactions and customer patterns in real time. DAMs are tailored to each organization and deliver highly accurate real-time risk scoring with low false positives. Lynx’s approach to AI model training prioritizes strong data governance. We curate high-quality training datasets from each organization’s transactions, and our efficient training algorithm performs feature selection, allowing DAMs to learn from all available features to mitigate bias and improve performance over time. Our solutions comply with PCI-DSS, ISO 27001, and SOC2 standards to ensure security and privacy. Lynx’s solutions address the critical need for unified enterprise-wide detection as well. Our Flex technology enables dynamic payloads: organizations can incorporate new payment channels in under 60 minutes, propagating new data fields to models, rules, and reports. The combination of DAMs and Flex provides a fully configurable 360-degree view of risk across all transactions, channels, customers, and devices: a centralized detection platform integrating all fraud and money mule threat intelligence and data.

Lynx’s AI-Enabled AML Technology: Explainable Real-Time Performance and Stronger Compliance

Lynx’s AI-enabled AML solutions are architected for transparency and explainability to address ‘black box’ and compliance concerns while optimizing performance. Our AML modules maintain a clear audit trail to meet regulatory requirements and are fully configurable for risk-aligned outcomes. Our Customer Screening and Payment Screening modules utilize a sophisticated AI-enabled name screening model that intelligently applies natural language processing (NLP) algorithms based on each incoming name’s structure. Organizations can select screening methodologies and develop rules aligned with their risk appetite. Our screening solutions provide highly accurate real-time name similarity scoring and lower false positives. In addition, Lynx’s innovative ‘AI with guardrails’ approach allows organizations to implement risk-based AML strategies aligned with their specific needs and regulatory demands. Our Tailored Delta List module filters watchlists and generates custom delta lists based on the company’s policies and risk tolerance, ensuring accurate watchlist reconciliations. Plus, our AML Transaction Monitoring module offers configurable unsupervised ML models and data agnostic integration for enhanced anomaly detection. Organizations can create and immediately deploy complex rules to assess unusual transaction patterns, resulting in risk and compliance-aligned outcomes.

Request a Proof of Concept

Our AI innovations and our collaboration with organizations to prevent financial crimes and safeguard global financial systems. This is further proven by the success of our customers’ experience. Companies working with Lynx save $1.6B annually* using our advanced AI-enabled fraud, money mule, and AML solutions. Ready to take the next step and transform your financial crime detection and prevention strategy? Reach out and schedule a Proof of Concept (POC).
*12 month trailing
Gartner, Emerging Tech Impact Radar: 2025, Tuong Nguyen, Danielle Casey, 23 January 2025 Gartner Disclaimer GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designations. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

Lynx Launches Next-Generation Fraud Prevention Models 

Posted on by davidsanchez
  • Lynx unveils next-generation Daily Adaptive AI models, shifting from individual transaction analysis to detecting entire fraud networks.
  • The new technology has achieved a 460% uplift in money mule value detection and identifies up to 35% more Authorized Push Payment Fraud (APPF), while reducing false positives, according to internal testing.
  • Unlike traditional static models, Lynx’s solution continues to improve over time, adapting to new fraud patterns.
Madrid, April 24 2025: Lynx Tech, S.A. (“Lynx” or the “Company”), a leading provider of Artificial Intelligence (AI) software that detects and prevents fraud and financial crimes, today announces the launch of its next generation of its Daily Adaptive Models (DAMs), a fraud detection solution. This significant upgrade marks a pivotal moment in the company’s ongoing mission to protect financial institutions and their customers from increasingly sophisticated fraudulent activities. With fraud cases rising by 16 percent and fraudsters stealing more than £3 million a day according to UK Finance, it is essential banks are armed with the technology to prevent fraud in real-time. Unlike static Machine Learning (ML) models commonly used in fraud prevention, Lynx’s Daily Adaptive Models combine daily retraining and data extensibility to drive increased fraud savings and reduced friction for financial institutions. The new models represent a shift from identifying isolated fraudulent transactions to detecting entire fraud networks. By analyzing patterns within these networks, Lynx’s technology enhances its ability to identify complex patterns of fraudulent behavior with high precision. Looking at the next-generation model in action, as ACI Worldwide predicts global Authorized Push Payment Fraud (APPF) losses will surpass $6.8 billion by 2027, it can identify up to 35% more APPF cases compared to previous Lynx models, according to internal testing. It also significantly improves money mule detection, with some financial institutions reporting notable increases in money mule identification rates. Lynx’s new models are currently being deployed in markets around the world, with financial institutions in America expected to benefit from the technology first, followed by those in Europe. Due to the no-code nature of the models, integration takes as little as two weeks, enabling the technology to reach its optimal value detection rate within three to six months as it learns from new data. Unlike traditional static models on the market that suffer from data drift and degradation over time, the technology maintains an optimal value detection rate thanks to Lynx’s proprietary DAMs. These continuously adapt to new fraud patterns without compromising their initial impactful performance, setting a new standard in long-term fraud prevention. Carlos Santa Cruz, Chief Technology Officer at Lynx, stated:
“This breakthrough is the culmination of two years of rigorous research. We’ve developed state-of-the-art in-memory databases, algorithms, and low-level code that make our solution incredibly fast to integrate while keeping costs down and downtime at zero. In internal tests, our technology has demonstrated the ability to analyze up to 40,000 data points in real time to identify fraudulent activities with remarkable precision, representing a quantum leap in detection.”
The upgraded models have demonstrated significant improvements in performance:
  • Enhanced understanding of financial behaviors across all accounts connected to a financial institution, leading to a substantial reduction in false positives and an increase in the value detection rate.
  • Improved adaptability through DAMS ensuring sustained performance over time and quick responses to new fraud tactics.
  • Superior performance compared to static consortium models, particularly in detecting APPF.
 Dan Mcloughlin, a financial crime expert and member of the team at Lynx, adds:
“The next-generation models will make a big difference in preventing Authorized Push Payment Fraud. We can now spot tricky fraud patterns long before they cause harm. This means we can help banks protect their customers’ money better than ever, staying significantly ahead of sophisticated fraudsters. With the UK’s new APPF reimbursement regulations, it’s imperative that banks embrace emerging technologies such as AI to fortify their fraud detection systems.”
To accompany the launch of its next-generation fraud models, Lynx has published a whitepaper on its Daily Adaptive Model. To read more, please visit https://landing.lynxtech.com/daily-adaptive-model-whitepaper.    

About Lynx   

Lynx Tech is an AI-driven software company designed to solve clients’ most significant fraud and financial crime challenges. utilize advanced AI technology to proactively identify and prevent fraud and financial crimes in real time, setting new standards for accuracy, speed, and scalability across multinational organizations. Lynx is dedicated to helping its clients move from a reactive to a proactive response by harnessing the power of AI to illuminate risk and deliver actionable insights. Lynx continues to set the standard for accuracy, speed, and scalability for multinational financial institutions (FI) and payment providers around the globe. Learn more at https://lynxtech.com/  

Enhancing Compliance and Customer Experience for PSPs

Posted on by Sara Garcia
Alyssa Iyer | Head of Product – AML

Empowering PSPs with Comprehensive Strategies for AML 

The Compliance Challenge for Payment Service Providers

Just as a busy highway needs efficient traffic management to prevent congestion and accidents, the world of digital payments requires robust compliance measures to ensure safe passage from sender to receiver. Payment service providers (PSPs) are at the forefront of this financial ecosystem, facilitating transactions across borders in real time. However, their role as intermediaries also makes them prime targets for illicit financial flows, including money laundering, sanctions evasion, and terrorist financing. Criminals exploit the speed and accessibility of digital payments to launder money and move funds undetected. Regulators are increasing their scrutiny on PSPs as well, with the UK Financial Conduct Authority’s (FCA) recent “Dear CEO” letter emphasizing the need for payments firms to bolster their AML and sanctions controls. Non-compliance can lead to severe penalties, reputational damage, and even regulatory intervention. To navigate these challenges, PSPs need adaptable AML screening solutions that effectively identify and mitigate risks in proportion to their exposure while ensuring a smooth customer experience.

Challenges in Detecting High-Risk Customers and Payments

Understanding the regulatory landscape is critical for PSPs, and these challenges are at the forefront of their compliance strategies:
  1. High Transaction Volumes: PSPs process millions of transactions daily, making manual AML checks impractical and prone to error.
  2. Evolving Sanctions and Watchlists: Global sanctions lists and politically exposed person (PEP) databases are constantly changing, requiring real-time updates.
  3. False Positives and Operational Overhead: Rigid compliance systems apply generalized approaches, generating high volumes of false positives, thus increasing investigation time and compliance costs.
  4. Cross-Border Transactions: Payments spanning multiple jurisdictions must comply with varying regional regulations, complicating AML processes.
  5. Criminal Innovation: Criminals continuously refine tactics to exploit PSPs, requiring solutions that adapt and evolve with emerging threats.
Recognizing these challenges is essential for PSPs aiming to enhance their compliance framework. To address these pressing issues and elevate compliance strategies, Lynx AML Screening provides key capabilities that redefine how PSPs manage financial crime risks.

Lynx AML Screening: A Smarter Approach to Compliance

Lynx AML Screening is an advanced AI-powered solution that enables PSPs to detect and prevent illicit transactions while ensuring a frictionless payment experience for legitimate customers. Our platform is designed to address the unique compliance challenges of payment providers through:

Real-Time Payment Screening for Proactive Risk Mitigation

  • Monitors both senders and beneficiaries in real-time and in batch to detect high-risk entities.
  • Provides instant transaction-level risk assessment, allowing firms to block suspicious payments before they are processed.
  • Handles large-scale, high-speed transactions with millisecond-level response times.

Customer Screening for Secure Onboarding and Ongoing Monitoring

  • Conducts thorough AML checks on new customers against global sanctions, watchlists, PEP databases and internal lists.
  • Allows custom rescreening triggers, aligning updates with the organization’s risk appetite to prevent unnecessary alerts.
  • Uses AI to intelligently apply the most optimized Natural Language Processing (NLP) algorithms for name scoring, driving down false positives.

Advanced Watchlist and Workflow Management

  • Configurable rule builders tailor screening to geography, product, and customer risk, pinpointing risk effectively and proportionally.
  • A no-code interface enables business users to modify screening rules in real time without IT or vendor reliance.
  • An intelligent workflow manager automates case assignments based on your specific processes and priorities, streamlining operations and eliminating the need for manual task allocation.
  • Real-time Key Performance Indicator (KPI) dashboards provide compliance teams with full operational visibility.

Seamless API Integration for Rapid Deployment

  • Our cloud-native platform integrates effortlessly into existing PSP workflows via a two-way API.
  • Fully compatible with ISO 20022, aligning with global payment messaging standards.

Aligning with FCA AML Priorities for Payments Firms

The FCA has emphasized the need for payments firms to strengthen their financial crime controls. Lynx AML Screening helps PSPs align with these regulatory expectations by implementing robust sanctions screening, enhancing transaction monitoring to spot suspicious patterns indicative of money laundering, and ensuring effective governance and oversight with audit trails and detailed compliance reporting. Additionally, Lynx offers flexible, configurable watchlist management, allowing firms to apply controls that are proportionate to the nature, scale, and complexity of their business and the risks to which they are exposed. By minimizing operational disruption through automated and scalable AML processes, Lynx enables PSPs to maintain compliance efficiently while delivering value for their customers.

Future-Proof Your Compliance Strategy with Lynx

With regulatory scrutiny on the rise and financial criminals becoming more sophisticated, PSPs must invest in AML solutions that deliver both compliance and operational efficiency. Lynx AML Screening empowers payment providers to stay ahead of regulatory changes, prevent financial crime, and build trust with customers and regulators alike. As the digital landscape evolves, so too must our strategies for compliance. Lynx AML Screening offers PSPs the tools to not only comply but thrive, fostering trust and security in a fast-paced world. Stay compliant. Stay secure. Protect your business with Lynx AML Screening. Take the Next Step in Strengthening Your Compliance Strategy Transform your risk management and compliance operations with Lynx AML Screening. Explore real-world insights into AML risks and mitigation strategies for payment providers in our latest collaboration with Fintrail. DOWNLOAD the Fintrail White Paper WATCH the Webinar Recording If you’re ready for a deeper conversation after reviewing the insights, our team is here to help.