RelyComply at MoneyLIVE 2026: AI, fraud, and the future of financial crime

Last year, we made our debut at MoneyLIVE Summit as part of StartUp City – and walked away with the award for Best Use of Emerging Technology. This year, we returned with even bigger ambitions: as a Gold Sponsor, hosting a thought-leading panel and creating an interactive experience at our stand that drew the biggest crowds and sparked insightful conversations.

How AI has turned fraud into a fully automated criminal economy

Panel highlights:

Our panel, featuring our CEO, Bradley Elliott, and  Rish Tandapany (COO, Purple Group) and Leon Ifayemi (Director of Coalitions and Research at CFIT), explored how AI is reshaping fraud and financial crime, effectively creating the first automated economy of fraud. Key trends emerged from the discussion:

1. AI is accelerating the scale and speed of fraud

Fraud is no longer limited by human capacity. Generative AI allows fraudsters to execute hundreds of thousands of attempts in minutes, from identity manipulation to phishing campaigns. Techniques such as jailbreaking devices, bypassing ID verification systems, and mass-manipulating documents are happening faster than ever, putting enormous pressure on traditional fraud prevention measures.

One case cited during the panel involved 100 stolen identities being used in 160,000 fraud attempts – an operation impossible without AI. This means financial institutions must not only respond faster but anticipate fraud in real-time, integrating AI-driven detection tools that can scale with the threat.

2. The barrier to entry for fraud is collapsing

Historically, committing fraud required significant expertise and resources. Now, AI has democratised the ability to perpetrate financial crime, making it cheaper, faster, and easier to access. This trend is especially concerning because it allows individuals with limited technical skills to conduct sophisticated attacks.

Organisations can no longer assume that only “highly skilled” fraudsters pose a threat. Instead, they must design systems that raise the cost and complexity of fraud, making it unprofitable for attackers.

3. Fraud prevention must move earlier in the value chain

Traditionally, fraud detection has been a reactive, back-office function. But as AI-driven attacks accelerate and barriers to entry collapse, prevention must be embedded throughout the customer journey, from onboarding to ongoing monitoring.

This involves:

• Proactive onboarding checks: leveraging shared, authoritative data sources to validate identities in real-time.
• UX & UI design considerations: creating user flows that inherently reduce risk while keeping friction low for legitimate customers.
• Continuous monitoring: using AI to identify suspicious patterns and intervene before fraud escalates.

We also discussed the cultural and systemic AML challenges:

• Ethical norms.
• Fines and reputational risks exist, but for many, they’re seen as “part of doing business.”
• Many fraud prevention schemes are voluntary, fragmented, and lack consensus across banks and policymakers – raising the question: shouldn’t there be common standards, from data collection to onboarding?
• Financial institutions are increasingly using the same AI tools as fraudsters, raising questions about model risk, potential collusion, and system vulnerabilities.
  

Our panel underscored the need for collaboration, shared data, and robust digital ID frameworks – tools that enable proactive fraud prevention while respecting privacy and consumer rights.

Implications for financial institutions

The trends highlighted at MoneyLIVE 2026 aren’t just academic – they have real-world consequences for banks, fintechs, and payment providers. Here’s what institutions should be thinking about:

1. Adopt AI-driven fraud prevention tools

Traditional rule-based systems are no longer sufficient. Institutions need real-time AI and machine learning solutions that can detect patterns across vast datasets and respond at the speed of automated attacks.

2. Embed prevention throughout the value chain

Fraud detection can’t be an afterthought. From customer onboarding to ongoing monitoring, anti-fraud measures must be built into every touchpoint, including UX and UI flows, account verification, and transaction screening.

3. Reduce barriers to collaboration

Fragmented data sharing limits effectiveness. Institutions should push for shared standards, interoperable data schemes, and digital ID frameworks, ensuring that insights from one organisation benefit the wider ecosystem.

4. Educate, but don’t overburden consumers

While consumer awareness is important, overloading users with complex instructions is counterproductive. Instead, provide simple, actionable guidance and leverage automated protections to minimise reliance on individual vigilance.

5. Proactively assess AI and model risk

Financial institutions are increasingly using the same AI tools as fraudsters. Organisations should test their own systems, monitor for potential model collusion, and implement safeguards to ensure that defensive technologies do not inadvertently introduce new vulnerabilities.

By taking these steps, financial institutions can stay ahead of accelerating threats, protect customers, and maintain trust in an increasingly automated and AI-driven financial ecosystem.

At the stand: AML risk-spotting challenge

While the panel sparked debate on stage, our stand created a different kind of conversation on the exhibition floor.

Our booth concept was a playful yet thought-provoking highlight: a claw machine turned into a risk-spotting game, challenging visitors to identify fraudulent activity. It was a hit, generating the most buzz on the floor, sparking conversations, and helping us connect with potential partners, clients, and curious minds eager to understand the future of fraud prevention.

But the experience didn’t stop there.

For those who took part, we captured the moment with instant Polaroid photos – a playful nod to identity verification in the real world. In an age where fraudsters are increasingly using manipulated images, deepfakes, and synthetic identities, it was a simple reminder that identity is still at the heart of financial crime prevention.

The Polaroids became a small keepsake from the event, but they also sparked an important conversation:

In a world of AI-generated identities and automated fraud, how do we ensure we’re verifying real people, not just digital artefacts?

Key takeaways from MoneyLIVE 2026

• AI is both a tool and a threat in financial crime – its adoption requires proactive strategies and ethical oversight.
  
• Fraud prevention must be integrated across the value chain, not just a reactive back-office function.
  
• Collaboration and standardised data frameworks are essential for scalable, effective fraud mitigation.
  
• Engaging, interactive experiences – like our claw machine game – can spark meaningful connections in a crowded event space.

MoneyLIVE 2026 reminded us that financial crime is evolving faster than ever – but with innovative technology, collaboration, and proactive thinking, we can stay one step ahead.

If you missed us at MoneyLIVE 2026 but would like to continue the conversation, we’d love to hear from you. Let us know your AML and fraud prevention priorities, and if you’d like to see how RelyComply can help, you can arrange a demo with our team here.