Shell companies siphon US$450m from Zimbabwe, SA

Published: 1 hour ago

A network of 23 shell companies operating between Zimbabwe and South Africa has been implicated in laundering US$450 million through illicit financial flows (IFFs), part of an estimated US$3 billion in combined annual losses to the two countries.

The findings come from a study published in the Journal of Risk and Financial Management, which analysed 1.8 million transactions using data from South Africa's Financial Intelligence Centre (FIC), the Reserve Bank of Zimbabwe (RBZ) and SWIFT. Researchers deployed an artificial intelligence tool known as FALCON, developed at India's National Forensic Sciences University, to detect cross-border laundering patterns with a reported accuracy of 98.7 percent.

According to the 18-page report, Disruption in Southern Africa's Money Laundering Activity by Artificial Intelligence (AI) Technologies, the AI system uncovered extensive trade-based money laundering, particularly gold export mis-invoicing and cryptocurrency layering, used to disguise proceeds from smuggling operations. These schemes exploit regulatory loopholes, high-volume cash transactions and fragmented enforcement between the two countries.

The study revealed that Zimbabwe's official systems fail to detect up to 42 percent of cross-border laundering linked to mis-invoiced trade and cash-based transactions, suggesting that significant volumes of illicit gold shipments and other smuggling proceeds are moving undetected. Weaknesses identified include over-reliance on rule-based reporting, which criminals bypass, and the absence of integrated analysis connecting transaction patterns with networks of linked companies.

In trials, FALCON outperformed both human auditors - who achieved an accuracy rate of 64.5 percent - and older machine-learning models such as Random Forest (72.1 percent). It also reduced false positives to 1.2 percent and can process up to two million transactions per second at a cost of just US$0.002 per 1,000 transactions, making it a cost-effective option for developing economies. The model meets Financial Action Task Force (FATF) compliance standards and has 92 percent judicial admissibility, enabling it to produce court-ready evidence.

The study warned that tackling the laundering problem requires robust bilateral cooperation and real-time data sharing between Zimbabwe and South Africa. Without this, the AI tool's detection capabilities will be limited.

The revelations add to a growing body of evidence highlighting the scale of economic haemorrhage from Zimbabwe's porous borders. Last year, the Zimbabwe National Chamber of Commerce reported that smuggling hotspots had contributed to an estimated 18,000 job losses.

Economist Eddie Cross this week described the scale of illicit financial activity along the Zimbabwe–South Africa corridor as a "drain on potential state revenues" and called for advanced detection systems to bolster enforcement.

Financial Intelligence Unit data shows that between 2019 and 2024, Zimbabwe lost US$920 million through smuggling, US$880 million from illegal gold and precious stone trading, US$730 million from corruption, US$500 million from fraud, US$300 million from tax evasion, and US$170 million from drug trafficking. Total illicit proceeds over the period may have reached US$6.15 billion.

The RBZ's 2024 Financial Stability Report also flagged large-scale illicit flows through real estate and motor vehicle dealerships, in addition to the minerals trade. "Real estate, car dealers and precious stone or precious metal dealers are the sectors that are most susceptible to money laundering," the report stated.

If implemented, experts say FALCON could give Zimbabwe and South Africa a significant edge in disrupting high-value smuggling operations and curbing industrial-scale looting.
- The Independent