Discai has been recognised by Everest Group in its 2026 Top 50 Financial Crime and Compliance (FCC) Technology Providers report

Discai has been recognised by Everest Group in its 2026 Top 50 Financial Crime and Compliance (FCC) Technology Providers report, specifically as a leader within the category Modernising transaction monitoring for precision and scalability.

This recognition validates what Discai has already built but it also confirms a deeper change underway across the industry.

For years, AML (anti-money laundering) transaction monitoring has operated on the simple premise that rules mean more protection.

But in reality, it has created the opposite.

• False positives can routinely exceed over 90%
• Analysts spend more time clearing alerts than uncovering risk
• Detection models struggle to adapt to new typologies

As transaction volumes increase, the problem compounds rather than gets resolved. Operational costs rise, investigations slow and ironically, exposure to financial crime increases.

“This recognition by Everest Group reinforces what we’ve believed for a long time – that the future of transaction monitoring is about better decisions. For our clients, this translates into something more tangible with less bias, faster investigations and a better view of actual risk. This is both a tech and operational change that will ultimately lead to businesses building a strategic advantage.” – Fabrice Deprez, Discai CEO

For years, systems have been built around the idea of defining the risk upfront, codifying it into rules and flagging anything that matches. Now, with the use of AI, professionalised cross border criminal networks and the rise of poly criminality (multiple crimes interconnected with organised networks), criminal behaviour is evolving faster than regulators can keep up.

We need to move away from such rigidity.

Instead of relying solely on static rules, leading approaches are becoming more adaptive, contextual and intelligence-led. They draw on a broader set of principles, including behavioural patterns and network relationships, to build a more complete picture of what ‘normal’ looks like.

This adjustment changes the role of monitoring by moving from a binary system to something more subtle. A system that helps prioritise risk, hunt for meaningful patterns and give investigators a starting point that already has analysed context.

In practical terms, that often translates into:

• Fewer low-value alerts overwhelming operations
• Better prioritisation of genuinely suspicious activity
• Comprehensive context for AML analysts
• Greater flexibility to respond to emerging typologies without constant rework

There’s still a place for rules. But they are increasingly just one layer within a broader detection framework, not the foundation holding everything up.

The end goal is a sophisticated monitoring capability that evolves alongside the threats it is designed to detect.

Built for scale, not strain

Of course, precision without scale is irrelevant.

Modern financial ecosystems run on high-speed, high-volume transaction flows. Legacy systems struggle under that weight. They slow down, fragment or require constant manual intervention just to stay operational.

Discai has been ruthless in its drive to solve this tension head-on.

Its architecture is designed to process large volumes of data in real-time, without sacrificing analytical depth. Decisions are made faster but not at the expense of accuracy. And critically, the system improves as it scales because more data feeds better intelligence.

But even more broadly, in AML we need to ensure that compliance isn’t just about proving you have controls in place, but about ensuring that those controls actually work.

That requires a move away from static, siloed systems towards more connected, intelligent platforms that can adapt in real-time. Discai is firmly positioned on that side of the divide.

Looking ahead

It’s clear that financial crime is becoming more sophisticated.

With rising transaction volumes and greater regulatory expectations, the old model can’t bend far enough to handle all of these pressures at once.

What’s emerging in its place are systems that are fundamentally built to be more adaptive and connected. This modernisation of transaction monitoring is about rethinking the foundations of how risk is identified, prioritised and ultimately, acted upon.

Everest Group is a leading global research and insights firm delivering independent analysis and benchmarks to support better decision-making across multiple sectors.