Why banks are switching to Consilient’s federated machine learning AML/CFT model
Outdated AML systems are costing you more than just time. Industry frustration is at boiling point.
Traditional AML solutions are overwhelmed, drowning compliance and investigation teams in false positives while missing sophisticated financial crime. The operational strain, regulatory pressure, and financial risk are clear—yet many banks remain tethered to these failing systems.
It doesn’t have to be this way.
Consilient’s new advanced AML/CFT Model offers a smarter, more precise way to strengthen compliance, reduce operational costs, and detect financial crime with unparalleled accuracy. Built using the most advanced machine learning approach and technology and backed by real-world results—including an 88% reduction in false positives and a 300% improvement in detection rates—our model is designed to meet the demands of modern risk management.
If you’re ready to stop fighting inefficiencies and start strengthening your AML approach, read on to discover how our model can transform your compliance efforts—without disrupting your existing systems.
The high cost of outdated AML systems
Traditional AML systems are no longer fit for purpose. Designed for a static, rules-based world, they struggle to keep pace with the complexity and speed of modern financial crime. The result? A system that costs more than it delivers.
False positives drain your resources
Legacy systems flag thousands of transactions as suspicious, it is a startling fact that up to 95% of these are false positives. This overload diverts compliance teams from high-priority risks, inflating operational costs and leaving genuine threats undetected.
Criminals exploit gaps
Money launderers have adapted their tactics to bypass rigid, rules-based models. From mule accounts to cryptocurrency transactions, these emerging threats slip through the cracks, putting your institution at risk of fines, reputational damage, and regulatory scrutiny.
Operational inefficiency holds you back
False positives aren’t just a resource drain—they damage customer trust. Legitimate transactions are delayed, accounts are flagged incorrectly, and inefficiencies erode your ability to respond quickly to real risks. Meanwhile, operational costs keep climbing, with no measurable improvement in outcomes.
If any of this sounds familiar, you’re not alone. Banks worldwide are grappling with these same challenges, but there’s a way to break free.
Consilient’s advanced AML/CFT Model is built to solve these problems—dramatically reducing false positives, improving detection, and giving compliance teams the tools they need to focus on what matters most.
Why Consilient’s advanced AML/CFT model is different
Traditional systems react. Ours anticipates.
The Federated AML/CFT Model goes beyond meeting compliance requirements. It’s a breakthrough solution designed to eliminate inefficiencies, reduce risk, and empower banks to stay ahead of financial crime.
Here’s what sets it apart:
1. Risk scoring with explainability
Instead of vague alerts, our model provides dynamic risk scores based on 12 months of transactional behavior, patterns, and interactions. Compliance teams gain clear insights into why an account was flagged, enabling faster, more informed decision-making.
2. Continuous learning
Criminals adapt, and so does our model. Using advanced federated machine learning, it evolves to detect new money laundering tactics, from cryptocurrency flows to complex mule account networks. Regular updates refine accuracy and reduce false positives over time.
3. Privacy-first collaboration
Federated learning ensures banks can collaborate securely across institutions without sharing sensitive customer data. This privacy-first approach strengthens detection by leveraging global insights while maintaining local data security.
4. Unmatched precision through advanced modelling techniques
Bold statement? Yes. Let me explain:
🟣Local precision meets global insights: Combines insights from diverse sources to create highly accurate and scalable models.
🟣Risk and typology-based detection: Instead of relying solely on SAR data, our model identifies patterns of high-risk behaviors and unusual activity (e.g., money services businesses or activity) to uncover risks missed by static systems.
🟣XGBoost technology: Fast, accurate, and scalable machine learning ensures reliable performance for high-volume transaction monitoring.
5. Seamless integration
Worried about disruption? Don’t be. The model integrates effortlessly with your existing systems, complementing your current setup to deliver immediate results without the need for a costly overhaul.
By combining the latest technology with privacy-first collaboration, Consilient’s advanced AML/CFT Model helps banks identify risks faster, cut down false positives, and focus resources where they’re needed most.
Real results: What leading banks have achieved
Don’t just take our word for it. Our Federated AML/CFT Model has delivered measurable results for institutions like yours. Here’s how it’s shaking up compliance processes:
✅️88% reduction in false positives
Imagine what your compliance team could accomplish if they weren’t drowning in irrelevant alerts. By cutting false positives by nearly 90%, our model enables teams to prioritise genuine risks, improving operational efficiency and reducing resource strain.
✅️300% improvement in detection rates
Legacy systems miss what truly matters. Our model identifies complex, hidden patterns that static rules simply can’t detect, leading to a threefold increase in detection accuracy. Banks using our solution are uncovering threats that previously went unnoticed.
✅️Strengthened regulatory confidence
Precision matters—not just for catching illicit activity, but for building trust with regulators. With explainable, transparent risk scoring and unparalleled detection accuracy, our model ensures compliance teams can demonstrate confidence in their AML efforts, reducing regulatory risk and penalties.
✅️Streamlined costs and operations
By reducing false positives and improving detection efficiency, banks are seeing significant cost savings. Teams spend less time on dead-end investigations, reallocating resources to high-value compliance activities instead.
With results like these, it’s clear: you need Consilient’s AML/CFT Model to modernize its compliance strategy and safeguard against financial crime.
Seamless integration: Results without disruption
Upgrading your AML system doesn’t have to mean overhauling your entire infrastructure. Consilient’s Federated AML/CFT Model is designed to integrate seamlessly with your existing processes, ensuring you can start seeing results quickly—in as little as four weeks.
Works alongside your current systems
Our model complements your existing transaction monitoring setup, enhancing detection and reducing false positives without requiring a full system replacement. This means no lengthy implementation timelines, no costly disruptions, and no downtime for your compliance operations.
Immediate impact
Unlike solutions that take months (or years) to deliver measurable results, Consilient’s Federated AML/CFT Model begins improving your risk detection and operational efficiency almost immediately. Your team will feel the impact from day one.
Minimal effort for maximum gain
We’ve taken the complexity out of adoption:
🟣No need for dual systems or manual workarounds.
🟣Easy deployment within your institution’s existing tech stack.
🟣Rapid configuration to align with your specific compliance needs.
Future-proof technology
As financial crime evolves, so does our model. Its continuous learning capabilities ensure it stays ahead of new typologies and threats, so your institution is always equipped with the most advanced compliance tools available.
Have concerns? This might help:
Addressing common concerns
“Will this disrupt our operations?”
No. The model integrates effortlessly with your current systems, so there’s no downtime or impact on daily operations.
“What about data security?”
With federated learning, your data stays local and secure. Only aggregated insights are used to inform the models, eliminating the risk of data breaches and maintaining compliance with privacy regulations.
“Is Consilient’s AML/CFT Model right for your institution?”
If you’re facing the constant challenges of high false positives, missed risks, and rising compliance costs, the answer is simple: yes.
“Who benefits most?”
The AML/CFT Model is ideal for:
🟣Banks struggling to manage high false positives and inefficient processes.
🟣Institutions under pressure to improve compliance without increasing operational costs.
🟣Organizations committed to data security but looking for more collaboration and precision in their AML efforts.
With seamless integration and immediate results, Consilient’s Federated AML/CFT Model gives you the tools to modernize your AML approach without the headache of a disruptive transition.
Bottom line: If your institution is ready to elevate its compliance strategy and achieve measurable results, Consilient’s AML/CFT Model is the solution you’ve been looking for.
The future of AML starts now
Traditional AML systems aren’t just outdated—they’re a liability. They drown compliance teams in false positives, miss sophisticated threats, and inflate operational costs, leaving your institution exposed to unnecessary risks.
Consilient’s AML/CFT Model changes all this. With proven results, including an 88% reduction in false positives and a 300% improvement in detection rates, this advanced solution provides the precision, efficiency, and adaptability banks need to tackle today’s compliance challenges.
Why wait? Every day spent relying on legacy systems is another day of wasted resources, undetected risks, and mounting costs. With Consilient, you can modernize your compliance strategy without disruption, enhance your risk controls, and stay ahead of financial crime. Take the next step today: Talk to us—we’d genuinely love to help.
