The future of AML teams: 3 lessons from AML Arena 2025

What happens when criminals move faster than your monitoring systems? Are your compliance tools built for yesterday's risks or tomorrow's? And how can AML teams keep pace with both evolving regulations and skyrocketing customer expectations?

These are some of the questions Niklas Rosvall, Chief Product Officer at Trapets, addressed during his session at AML Arena 2025, held in Helsinki, Finland. 

His session focused on how financial crime teams can respond to a digital landscape defined by speed, scale, and growing expectations from both customers and regulators. 

From the importance of automation to the growing need for real-time surveillance, Rosvall explained how AML teams can move beyond just compliance and step into a more adaptive, tech-empowered role. 

Here are three takeaways from his presentation. 

1. Compliance needs to be smarter, not just faster 

Rosvall began by highlighting the changes in financial services over the past decade.

The amount and variety of data that AML teams work with have increased sharply, thanks to mobile-first platforms, new payment types, and tech-savvy users. 

Criminals are now exploiting the same tools and trends, such as instant transfers, digital assets, and peer-to-peer services, but without any regulatory constraints.  

Meanwhile, customers expect fast and smooth digital experiences, while regulators are pushing for more timely and technology-driven oversight. 

To meet these demands, AML teams must work across multiple disciplines, including product expertise, strategy, and technical fluency.  

Rosvall emphasised that effective monitoring starts with knowing your business and mapping relevant typologies and risks to specific data points.  

"If your rules aren't aligned with your risks, you're just automating the wrong things faster," he cautioned. 

2. AI's role is growing - so is the need for transparency 

Rosvall also discussed how artificial intelligence impacts the way AML teams detect and prevent financial crime.  

While most organisations still rely heavily on rule-based systems, many are now combining these with AI and machine learning to filter out false positives, identify patterns, and prioritise alerts. 

We're entering a phase where AI tools are starting to handle tasks beyond simple support. In some setups, they can scan wide sets of behavioural and biometric data and respond in real time. Some can even adjust monitoring rules dynamically based on what they observe. 

However, this shift brings new challenges. AI explainability and transparency are essential in decision-making.  

“Technology and AI must support decision-making, not replace it”, said Rosvall.  

AML teams need clear visibility into how AI decisions are made, and they must be ready to explain them to auditors, regulators, and customers. 

3. Real-time monitoring is becoming the standard 

Rosvall’s final message focused on monitoring speed. 

Batch-based monitoring is falling short. Real-time monitoring, where transactions are assessed and flagged immediately, is becoming the standard for many AML teams. 

This shift is also driven by regulation. Regulatory developments, such as Payment Services Directive 3 (PSD3) and the Instant Payments Regulation, require dynamic, instant risk assessments and customer screening, especially for high-risk transactions and sanctioned entities. 

“If your systems wait until the end of the day, you’re already late,” Rosvall said.