What is Causing the Rapid Rise in Fraud?

How AI Is Transforming Financial Crime Prevention

In a recent episode of FinTech Focus TV, host Toby welcomes Alyssa Iyer, Head of AML at Lynx Tech, for an eye-opening discussion about how artificial intelligence is revolutionising the fight against financial crime. The episode delves deep into the evolving world of AML (Anti-Money Laundering), the rise of AI-driven fraud detection, and how FinTech companies can navigate the increasingly complex regulatory and risk landscape.

As a FinTech recruitment business working with the innovators driving this change, Harrington Starr is proud to highlight this critical conversation, which explores both the current challenges and future solutions in AML technology. Every insight shared in this blog comes directly from the episode transcript, ensuring full accuracy and alignment with the expertise shared by Alyssa and Toby.

A Career Built on Compliance, Innovation, and Transformation

Alyssa Iyer opens the discussion by walking through her career journey, which began with hands-on investigative work at a major US bank during a time of heightened regulatory scrutiny in 2013. From there, she moved into consulting with PwC, where she advised numerous financial institutions on best practices in AML compliance. Eventually, she transitioned into product management, where she now leads AML solutions at Lynx Tech.

What makes Alyssa’s background especially compelling is the range of perspectives she brings, from working within institutions dealing with enforcement action to consulting across diverse client types, and finally, to productising those solutions with modern technology. As Toby notes, the rise of product as a C-suite function has become increasingly evident across financial services. Alyssa’s role is a perfect example of how AML leadership now demands both technical know-how and business vision.

Financial Crime in FinTech: A Shape-Shifting Threat

From the outset, Toby frames the conversation by acknowledging that financial crime is one of the most pressing issues in the FinTech space today. As he puts it, financial crime is “a shapeshifter”, constantly evolving and becoming more sophisticated. Alyssa agrees and adds that the reason we're seeing a rise in money laundering is because we're seeing a rise in crime itself.

She explains that today’s criminal organisations are not only larger and more organised but also more resourceful. Many now operate literal compounds dedicated to scamming individuals, often using trafficked victims to carry out their schemes. They’re leveraging a range of tools, crypto, prepaid cards, and synthetic identities, to launder funds across various platforms and jurisdictions.

Alyssa makes it clear that these organisations no longer need to show up at banks with bags of cash. They move funds fluidly between fiat and crypto environments, often passing through synthetic digital identities to create a layer of anonymity. However, since criminals still need to interact with the fiat system to complete transactions, there’s still an opportunity for financial institutions to intervene, if they’re equipped with the right tools.

The Onboarding Dilemma: Convenience vs. Security

One of the central tensions discussed is the balance between seamless customer onboarding and effective fraud prevention. Toby notes that financial institutions are under pressure to deliver “friction free” customer experiences, but Alyssa points out that this very convenience can become a weakness.

Criminals exploit the same low-friction onboarding systems that customers value. To combat this, Alyssa argues that organisations must invest in technologies that can identify AI-generated documents, synthetic identities, and stolen information at scale. But it doesn’t stop at onboarding. Continuous monitoring is essential to ensure that a customer’s activity remains consistent with legitimate profiles.

This real-time, ongoing monitoring must be done across millions of customers. Even small firms with limited teams face substantial challenges in implementing this effectively. Alyssa’s point is clear: rules-based systems can’t keep up. AI must be used to detect anomalies and adjust to new threats dynamically.

Case in Point: Pig Butchering Scams and Wire Fraud

Alyssa brings up a compelling real-world example: a recent investigative report by ProPublica on “pig butchering” scams. In these schemes, scammers open multiple bank accounts using fake details and wire millions from defrauded victims to offshore accounts. It’s a prime example of how crucial it is for banks to know their customers, not just during onboarding, but at every stage of the relationship.

She poses a rhetorical question: Would it make sense for a schoolteacher in Brighton to be wiring hundreds of thousands of dollars to unknown Cambodian entities? Clearly not. But without AI, banks cannot identify this type of activity at scale. Criminals are using AI, and if financial institutions don’t fight fire with fire, they will fall behind.

Adapting in Real Time: Lynx Tech’s Approach to AI-Driven AML

Alyssa then dives into what makes Lynx Tech different. While many financial institutions have models in place, she points out that most of these models degrade rapidly once they are deployed. Criminals don’t wait six months to adjust their behaviour; they evolve every day.

Lynx Tech combats this with adaptive AI models that update daily. These models incorporate both genuine and fraudulent behaviour patterns from the previous day, allowing them to evolve in lockstep with criminal tactics. This ensures that financial institutions can continuously prevent fraud while minimising false positives that disrupt legitimate customer activity.

Toby calls it a “battle royale” between good and evil, with some of the world’s smartest technologists working on both sides. Alyssa agrees and reinforces the importance of speed and adaptability. Lynx Tech’s daily model refresh cycle is designed precisely to stay ahead of the criminal curve.

AML Compliance in FinTech: The Regulatory Shift

Turning to regulation, Toby asks Alyssa how compliance functions are evolving. She explains that AML, unlike fraud detection, has always been heavily regulated. This has historically made institutions hesitant to innovate. However, regulators are now beginning to embrace risk-based approaches, particularly in the UK.

This shift has opened the door for greater adoption of AI in AML. Regulators are no longer satisfied with one-size-fits-all policies. They want firms to understand their specific risks and apply appropriate technologies to address them. Alyssa shares that Lynx Tech uses natural language processing (NLP) to enrich sanctions lists and match name variations with high accuracy, an essential tool in reducing false positives and improving operational efficiency.

Garbage In, Garbage Out: Why Data Integrity Matters

Alyssa returns to the idea that AML systems are only as good as the data that feeds them. She warns that without high-quality intelligence, even the most advanced AI models will produce poor outcomes. That’s why Lynx Tech focuses on both ends of the pipeline: enriching the data that enters the system and optimising the models that process it.

She explains how traditional name screening often leads to analysts being flooded with false positives because of overly cautious thresholds. By tailoring those thresholds based on portfolio risk, Lynx Tech helps clients maintain strong compliance without overwhelming their teams. The key is a combination of precise screening and intelligent model application.

Predictive Intelligence: The Future of AML in FinTech

Alyssa and Toby explore what’s next for the industry. One of the most promising areas is the unification of fraud, AML, and cybersecurity intelligence. Alyssa notes that these domains have historically operated in silos, with different mindsets, technologies, and data sets. But when unified, they can provide powerful, predictive capabilities.

She cites money mules as a key example. Because they often transfer small sums, their activity is hard to detect through AML systems alone. But if financial institutions combine cyber signals (like device fingerprinting) and fraud analytics with AML intelligence, they can begin to see the full picture.

Toby agrees, highlighting his passion for data visualisation and actionable insights. It’s not enough to generate graphs and dashboards. What matters is whether those visualisations lead to smarter, faster decisions. Both he and Alyssa stress that the ultimate goal of any AML system should be to produce usable intelligence, something that’s especially vital in a world moving at breakneck speed.

New Product Launches and What’s Next for Lynx Tech

As the episode nears its end, Toby asks Alyssa to share what’s coming next for Lynx Tech. She reveals that the company is preparing to launch a new AML transaction monitoring capability. This product will complement their fraud prevention and sanctions screening tools, offering a holistic, integrated suite for clients.

Some customers are looking for best-in-class point solutions, while others want an end-to-end AML package. Lynx Tech is positioning itself to deliver on both fronts, using machine learning and a flexible platform to meet varying client needs.

Toby praises this approach, noting that the era of legacy technology, where clients are forced to adapt to rigid platforms, is over. Today’s FinTech firms expect tailored solutions that adapt to their evolving challenges. Lynx Tech’s customer-led, innovation-first approach is exactly what the industry needs.

AML Solutions for FinTech: Who Should Be Talking to Lynx Tech?

To wrap up, Toby asks Alyssa who should be reaching out to Lynx Tech. Her answer is straightforward: any organisation with fraud or money laundering risk, from FinTech startups to tier-one financial institutions, can benefit from Lynx’s capabilities. While the company isn’t currently focused on crypto analytics, Alyssa is watching that space closely and appreciates the breakthroughs being made by specialised firms.

She notes that Lynx prefers to focus on doing one thing extremely well rather than spreading itself too thin. For now, that means excelling in the fiat space, but the lessons learned from crypto could eventually inform future innovations.

Final Thoughts: FinTech Recruitment in AML and Compliance

At Harrington Starr, we understand that behind every great AML system is a team of exceptional people. The rise of AI in compliance has created a surge in demand for professionals who understand both the regulatory environment and the technical landscape. Whether it’s AML product managers, fraud data scientists, or AI governance specialists, FinTech firms need talent that can lead them into the future.

This episode of FinTech Focus TV is a powerful reminder of the challenges and opportunities facing the industry. With leaders like Alyssa Iyer and organisations like Lynx Tech at the forefront, the FinTech sector is better equipped than ever to tackle financial crime with innovation, intelligence, and integrity.

If you’re building out your AML, compliance, or fraud teams, or if you’re a candidate looking to make a meaningful impact in this space, Harrington Starr is here to help. Reach out to our FinTech recruitment team to explore how we can support your growth.