Understanding AMLA and the Strategic Role of AI in the Fight Against Money Laundering

Each year, between 2% and 5% of the global GDP is laundered through complex schemes—over USD 2 trillion. In Germany alone, estimates reach €100 billion annually. The impact is severe: money laundering undermines financial systems, distorts competition, and fuels organized crime.

How will the new European Anti-Money Laundering Authority (AMLA) intensify the fight? And what role will artificial intelligence (AI) play in this transformation?

In this article, we explore how technology and regulation will converge over the coming years—and why financial institutions must prepare now.

The EU’s Overhaul of Its Anti-Money Laundering Framework

The European Union is undertaking a structural reform to its AML and counter-terrorism financing regulations. Starting in 2027, a €10,000 cash transaction cap will be enforced EU-wide to reduce anonymous transactions. At the heart of this transformation is AMLA—a new centralized supervisory authority.

By mid-2025, AMLA will coordinate national supervisory bodies, especially in cross-border cases. Its mission includes defining technical standards and procedures that ensure consistent AML enforcement across Europe.

⚠️ Rising Pressure on Financial Institutions

Each new regulation increases the burden on banks and payment providers. Institutions must now manage stricter processes, more detailed documentation, and advanced risk analysis.

Today, financial institutions are frontline actors in detecting financial crime. In Germany, the BaFin reported that over 90% of 320,000 suspicious activity reports in 2023 originated from the financial sector.

However, many still operate on legacy systems where KYC, transaction monitoring, and watchlist screening are fragmented. This makes comprehensive risk analysis—especially in cross-border transactions—very difficult.

With millions of transactions processed daily, the challenge is clear: identifying anomalies requires speed, precision, and scale. Many compliance teams are overwhelmed by case volumes and false positives that require manual review.

🧭 A New Approach Is Needed

The answer isn’t more manual resources—it’s a smarter approach. One that can scale with growing regulatory complexity. This is where AI comes in.

🤖 AI: A Strategic Ally in AML Compliance

The potential:

AI is transforming the compliance landscape. Traditional rule-based systems fall short when processing high-volume, high-velocity financial data.

AI can:

• Detect suspicious patterns in massive data sets

• Learn from past cases to improve accuracy

• Reduce false positives significantly

According to McKinsey, AI can boost suspicious transaction detection rates by up to 30%—a game-changer for resource-constrained teams.

Modern AI platforms also unify data across compliance functions: customer profiles, transaction history, watchlist screening, and more—building dynamically updated risk profiles.

Hybrid models, combining AI with expert rules, are proving effective. They’re explainable (which regulators demand), and they integrate with existing control structures—making them viable in highly regulated environments.

The barriers:

Despite its promise, many institutions hesitate to adopt AI. The main reason? Regulatory uncertainty.

Supervisors remain cautious about “black box” AI models that lack transparency. This leads many institutions to stick with outdated but predictable systems.

There’s also a lack of clear guidance on acceptable AI use for AML:

• What level of explainability is required?

• What should be documented?

• Which models are compliant?

🏛️ AMLA: A Catalyst for Innovation

Beyond supervision, AMLA will define and enforce technical standards—potentially unlocking AI adoption across the financial sector.

A unified, data-driven regulatory framework would eliminate legal ambiguity and empower institutions to move forward confidently.

If successful, AMLA could accelerate AI adoption in AML—offering early adopters a significant competitive edge.

🔮 The Future of Financial Crime Prevention

The creation of AMLA doesn’t mark the beginning—it marks an acceleration of a path already underway: increasing regulatory pressure and greater institutional responsibility.

The question is no longer if we need to modernize AML strategies—but how fast we can act.

AI is no longer a trend—it’s a tool for real impact.It helps anticipate risks, streamline compliance, and meet new requirements without sacrificing efficiency.

And the tech is ready. Proven, flexible AI platforms are available, built to integrate with legacy infrastructure. And modernization methodologies—like those we implement at WAU—allow gradual transformation without interrupting operations.

With rising transaction volumes and tighter regulation, AI is not just compliance—it’s a strategic investment in operational resilience and competitive advantage.

🌎 What About Latin America?

Europe is leading in AML regulation through AMLA. But Latin America is also advancing—at different speeds.

• Brazil: Central Bank initiatives around Open Finance and fintech regulation are strengthening traceability frameworks.

• Mexico: Strengthening its Financial Intelligence Unit (UIF) and issuing AML guidelines for fintechs, exchange houses, and banks.

• Colombia & Chile: Combining digital transformation with transparency reforms—but most legal frameworks remain fragmented or reactive.

This creates a strategic opportunity: institutions that adopt global best practices before local mandates take effect will be better positioned to lead.

They’ll not only meet compliance—they’ll build trust with clients and regulators while optimizing efficiency.

🧱 Modernizing the Core Banking System: The Foundation for AML Compliance

Many institutions across Latin America (and globally) still operate on rigid, monolithic legacy core systems. These systems block the integration of technologies like AI or RPA into AML workflows.

This infrastructure:

• Slows innovation

• Increases operational costs

• Makes real-time traceability and reporting nearly impossible

New compliance frameworks demand interoperability, transparency, and agility—none of which legacy cores can deliver.

That’s why core modernization is now a business decision—not just an IT project.

At WAU, we specialize in building modern, API-based, microservices-driven cores that integrate seamlessly with AI and compliance systems. These cores enable fast adaptation to new regulations, automation of key tasks, and reliable reporting—without disrupting daily operations.

✅ Conclusion

The fight against money laundering is evolving fast—with tougher regulations and smarter technology leading the charge.

AMLA reflects a global shift toward stricter, more integrated supervision.

Financial institutions can’t afford to wait. Regulatory pressure will only grow. The answer is clear:👉 Adopt AI.👉 Modernize your core.👉 Build sustainable, scalable, and future-proof AML systems.

In Latin America, regulation is still evolving—but the direction is clear. Institutions that act now will lead tomorrow.

At WAU, we help financial institutions take this leap—with proven technology, practical methodology, and zero disruption.