Criminals move an estimated $2 trillion through the global financial system every year.
Trade-based money laundering is one of the most effective methods they use to avoid detection. The multiple layers and complex paperwork act as a shield, allowing financial criminals to exploit loopholes. As a result, illicit money often passes through supply chains unnoticed.
Over the years, banks have made significant progress in detecting suspicious payment behaviors; nevertheless, they struggle to maintain a robust system. The biggest reason is the nature of global trade itself; its many layers are often misused by criminals as cover. Outdated systems are one of the major reasons behind this ongoing failure. To overcome this growing threat, banks need a solid foundation capable of tackling these challenges.
Where Legacy Controls Fail in Trade-Based Laundering Detection
The dependency on legacy systems is one of the biggest challenges that is being leveraged for trade-based money laundering. However, these systems are not built for today’s evolving technology and sophisticated crimes. These outdated systems are not only rigid and reactive but disconnected from the current landscape. Here are some of their loopholes that make them inefficient:
- Limited Cross-border Visibility: Legacy control systems often operate by geography, business line, or entity. This makes it difficult to access the complete trade journey, which results in hidden circular flows.
- Manual Interventions: One of the biggest drawbacks is that in traditional systems, the suspicious activities detection still relies on human reviews and paper trails. This slows down the process and leaves room for errors.
- Static Pre-set Rules: Criminals use advanced ways to attack that fall outside the defined boundaries of outdated systems, because the preset thresholds and static rules often miss the nuanced behaviour.
- Lack of learning capacity: Legacy systems lack flexibility, which means, once a laundering pattern is spotted, there are no mechanisms to feed awareness back into detection workflows.
Scaling Detection Without Rebuilding Your Entire Tech Stack
Banks and other financial institutions often find it challenging to replace outdated systems with new infrastructure. However, that is not really the case nowadays. Modern AI-driven risk models are advanced enough to be integrated with the existing systems. Hence, organizations don’t have to go through the arduous process of creating everything from scratch. Be it core banking platforms, compliance tools, or vendor trade finance modules, the scalable AI layers can act as an extension to enhance detection logic, read existing data, and automate risk scoring in real time. These are some of its qualities that make its scalability flexible:
- The API-driven models that seamlessly connect with the existing platforms of the institutions.
- It has modular architectures that enable teams to scale from a pilot use case to enterprise-wide adoption.
- Another great advantage is the cloud-based deployments that avoid the cost of heavy infrastructure.
By rebuilding the existing systems, banks and institutions can amplify their compliance capabilities without interrupting their operations. With the support of modern AI-driven risk models, organizations can focus on the strategies that work and upgrade those that don’t.
How Odyss Global Enables AI-Driven Trade Risk Intelligence
At Odyss Global, we assist organizations wishing to modernize their trade-based risk detection strategies. With the help of practical, scalable, and compliance-ready models, our team enables them to leverage these emerging technologies and make their systems more efficient. Here’s how our team supports:
- Custom-built AI risk models
We have custom-built AI risk models trained to detect and identify patterns across the invoices, counterparties, shipping records, and payment trails, tailored to the structure of global trade.
- Data unification for risk clarity
Our data engineering aims to unify the scattered datasets. Whether it is trade finance or third-party logistics, systems get access to the complete risk picture.
- Modular integration frameworks
We offer Modular integration frameworks that enable AI layers to plug into existing infrastructure, without requiring major system overhauls or downtime.
- Compliance-ready models
With our explainable model architecture, your compliance teams can easily make document decisions, respond to the audits, and align with evolving regulatory standards.
- End-to-end model lifecycle support
Our support is across the development to validation, which covers model designs, testing, governance, tuning, and operational rollouts to ensure AI systems stay relevant over time.
Instead of offering disruptive changes, Odyss Global’s approach supports clients in strengthening their existing capabilities, improving visibility into trade risks, and seamlessly transitioning from static to highly advanced monitoring.
Final Words
There are still many organizations addressing trade-based money laundering with outdated systems. Considering the constantly evolving nature of this financial crime, where even advanced models can miss subtle traces, it’s time for businesses to invest in more sophisticated solutions. As global trade becomes increasingly digitized and interconnected, the ability to see through layers of transactions, counterparties, and documentation is no longer optional.
With the support of Odyss Global’s scalable AI models, businesses can not only gain real-time insights but also turn fragmented data into actionable intelligence. We’ve been helping organizations bridge this gap by supporting their shift from reactive controls to proactive risk management.
