Money20/20: How SEON Uses AI to Transform Fraud Detection

It’s no secret that fraud and compliance is a big part of finance – and one that’s evolving quickly thanks to AI.

In this space, AI has become both a powerful defence mechanism and an accelerating threat vector.

Speaking with FinTech Magazine at Money20/20 Europe, Nauman Abuzar, VP of Risk and Compliance at SEON, outlined how the company is reframing fraud prevention as an intelligence-led discipline rather than a rules-based exercise.

Building an intelligence hub for risk

At the core of SEON’s latest product evolution is its newly launched MCP-enabled AI capability, designed to transform how compliance teams interact with risk data.

Nauman explains: “We have been working closely with our customers to understand their challenges and we see that, for compliance teams and analysts, the challenge is not just managing alerts, but having a more contextual view of those customers and transactions. 

“With our launch, they can now configure and integrate with AI tools like Claude, Gemini. 

“This will give them a much stronger context, generate a more thorough narrative and provide a pretty holistic view of the customer and analysis.”

This shift reflects a broader industry trend: moving away from fragmented tooling toward unified intelligence environments. 

SEON’s platform now enables AI-driven charting, network detection and rule creation, signalling a move toward what Nauman describes as “more of an intelligence hub rather than just a solution”.

Interoperability as a strategic priority

A defining feature of SEON’s approach is its compatibility with major AI ecosystems.

Rather than building closed systems, the company is leaning into interoperability.

Nauman explains: “These are pretty much open-source tools, accessible to most companies and AI is now embedded in most financial institutions.

“Our customers are heavily involved in AI, but they have no visibility on how to implement it, how to use it or how to bring it into their day-to-day operations.

“Our launch helps them to enable that right away and it gives more efficiency and support them in their process.”

By integrating directly with tools such as ChatGPT, Claude and Copilot, SEON is reducing operational friction. 

He adds: “It’s quite time-consuming for them to run some sort of analysis – copying and pasting from their existing tools into ChatGPT or Claude. 

“But with this MCP integration, it will help them to contextually review and conclude anything much faster.”

Balancing innovation with governance

Adopting AI does not come without its challenges, particularly in a heavily-regulated space like finance.

Concerns around data security and regulatory compliance are at an all-time high, with SEON addressing this with a governance-first approach.

“AI can be incredibly helpful in fighting financial crime, but it also supports criminals in generating more sophisticated fraud patterns,” Nauman notes. 

“We are making sure to set up the right governance and explainability around that – how it can be used and how it should be used.”

He adds that regulatory scrutiny is shaping product design: “We made sure about how we’re going to utilise our AI features, ensuring compliance not only from a data protection perspective, but also from an AML regulation perspective – because regulators like FinCEN, the ECB and other global regulators are very much focused on how AI needs to be utilised within the financial crime space and how we can secure data.”

Human-in-the-loop remains critical

Despite the growing capabilities of AI, SEON is firmly advocating for a hybrid model that combines automation with human oversight.

“Rule-based monitoring is of course going to stay there,  it’s not going to go away,” Nauman confirms.

“It’s going to be a hybrid approach for most fraud teams, or even AML teams. AI can summarise what has happened, but you are the one who is going to make the decision – whether it’s fraud or whether it’s a true positive or a false positive.

“AI cannot make a decision on its own – a human in the loop is really important. That’s why a hybrid approach is something we have taken.”

Network intelligence and operational visibility that creates ecosystem value

SEON is also investing heavily in network intelligence and visual analytics to combat increasingly complex fraud schemes.

“Using AI to generate a narrative to detect fraud patterns – using our network intelligence as well as our chart features – will give our customers a full, holistic view of the patterns and connected accounts,” Nauman says. “They can see the full picture of fraud rings, analyse those patterns, and take whatever specific action needs to be taken.”

The company’s AI chart builder extends this visibility beyond analysts to leadership teams. “They can generate any sort of data view they want… it’s going to support not only analysts, but also leadership and business stakeholders.”

Beyond technology, SEON is building value through shared knowledge and industry-specific playbooks.

“It’s not like we're trying to hoard that knowledge – it’s part of the community to support,” Nauman concludes. “From day one, the goal has been the same: fighting fraud, fighting financial crime.”