As global trade shifts due to political and economic upheavals, companies face increasing risks of illicit financial flows and trade-based money laundering. Experts advocate for integrated, AI-driven systems that link logistics and financial data to enhance detection and compliance amid rapid industry changes.
Global shifts in politics and trade are creating fertile conditions for trade-based financial crime, forcing companies that move and finance goods to shoulder new...
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responsibilities for detecting illicit flows, according to analysis by the World Economic Forum and related industry studies.
The WEF assessment, authored by Hassan Zebdeh of Eastnets, warns that money laundering has swollen to roughly US$5.5 trillion annually , about 2%–5% of global output , and that Europe alone saw around US$750 billion pass through illicit channels in 2024 despite tougher rules. Rapid changes in tariffs, sanctions and sourcing decisions are reshaping supply chains faster than many compliance systems can follow, the report says, enabling organised criminals to hide unlawful payments inside otherwise ordinary shipments and corporate structures.
Those criminals are increasingly sophisticated. Industry analysis and WEF commentary note organised groups are building out automated processes and AI-driven tooling, creating shell companies that mimic legitimate suppliers and routing trade through multiple jurisdictions to complicate oversight. At the same time, banks and corporates often remain wedded to static rules, manual document checks and siloed case systems that struggle to reconcile physical cargo records with payment trails as routing and counterparties change week by week.
The mismatch between operational logistics data and financial controls is now a systemic vulnerability. Shipment manifests, bills of lading and customs filings exist principally to move goods, not to vouch for the authenticity of counterparties or the fairness of declared values; when those records diverge from invoices and payment flows, they can signal trade-based laundering, sanction evasion or beneficial-ownership obfuscation. The WEF argues that reconciliations carried out after the fact are insufficient; instead, timelines of movement and payment must be compared in near real time.
To close that gap the report proposes a layered, intelligence-led approach. Automation should perform routine cross-checks across invoices, shipping documents and customs entries to expose obvious mismatches in quantities or prices. Machine learning can then detect subtler behavioural anomalies , for example, recurring small deviations in declared weights or frequent routing through higher-risk transhipment hubs. Finally, integrated dashboards that bring together route data, sanctions lists, tariff changes and vessel movements can turn disparate signals into actionable alerts for both operations and compliance teams.
This repositions logistics, procurement and trade-compliance functions as core elements of anti-money-laundering architecture. According to the WEF, data maintained by operations provides the only ground truth of what actually moved and when; marrying that stream with financial records creates some of the most powerful indicators of criminality. The argument is echoed in broader industry research: Kroll’s 2025 report found more than 70% of executives expect financial-crime risks to rise, yet fewer than a quarter rate their compliance programmes as highly effective, while PwC’s regional surveys continue to flag procurement fraud as a persistent corporate threat.
Cyber-enabled fraud compounds the problem. A WEF press release on cyber threats noted that 73% of organisations reported direct impacts in 2025 and that concern about third-party and supply-chain cyber risk is rising. That convergence of cyber and trade risk means trafficking in falsified documents, bogus freight contracts and thefts of cargo can be weaponised to create cover stories, manipulate insurance claims or insert unvetted actors into chains of custody , all of which multiply avenues for laundering.
Operational and technology change is therefore both necessary and strategic. The WEF and other commentators urge companies to replace fragmented transport-management and ERP landscapes with converged architectures that link shipment milestones, trade documentation and financing data. Recent industry reporting on trade digitisation shows growing investment in electronic trade documents, vessel analytics and network-risk scoring to support real-time exception management. Firms that embed continuous reconciliation between physical and financial records stand to convert volatility into an intelligence advantage, improving supplier selection, strengthening ESG credence and securing better terms with banks and insurers.
Policymakers and private sector leaders are also urged to broaden cooperation. According to the WEF, coordinated information sharing across governments, carriers, banks and insurers, alongside stronger incentives for digitisation, would make it harder for transient shell entities and disposable beneficiaries to exploit jurisdictional patchworks. Where controls lag, geopolitical turbulence will remain an exploitable opening for sophisticated adversaries.
The imperative is clear: as trade routes and commercial partnerships continue to realign, companies can no longer treat logistics as a purely operational concern. Integrating operational signals into the anti-financial-crime toolkit is now central to protecting balance sheets, reputations and the integrity of global trade.
Source: Noah Wire Services
