The role of freight forwarding companies in detecting and investigating trade-based money laundering

Abstract

Purpose

This study aims to investigate the role of freight forwarding companies in detecting and reporting trade-based money laundering. The proximity of freight forwarding companies to shipping-related trade-based money laundering red flags places them in an ideal position to detect suspicious transactions.

Design/methodology/approach

The study used semi-structured interviews with expert participants in freight forwarding shipping and compliance aspects around freight forwarding. This study focuses on the South African context.

Findings

Freight forwarding companies are well-positioned to detect, investigate and report on trade-based money laundering schemes. However, the companies are not always aware of the guidelines designed to assist in identifying trade-based money laundering schemes. Thus, freight forwarding companies develop internal processes to identify trade anomalies but are often unable to link trade anomalies to illegal financial flows and trade-based money laundering schemes.

Research limitations/implications

The current regulations on money laundering can be extended to freight forwarding companies by the respective regulators for enhanced anti-money laundering protection. This study is limited to freight forwarding companies in a South African context.

Practical implications

Increased awareness among staff in freight forwarding companies can assist them in identifying trade-based money laundering red flags to detect and prevent trade-based money laundering schemes.

Social implications

This paper assists other role players and policymakers in the trade process to create a better awareness of trade-based money laundering. The limited obligations on freight forwarding companies to comply with anti-money laundering regulations lead to a more volunteer-like compliance practice.

Originality/value

To the best of the authors’ knowledge, this is the first paper that offers insight into the role of freight forwarding companies in detecting trade-based money laundering in South Africa.

Citation

Makkink, I.M., Steyn, B. and Bezuidenhout, H.C. (2024), "The role of freight forwarding companies in detecting and investigating trade-based money laundering", Journal of Money Laundering Control, Vol. 27 No. 7, pp. 26-42. https://doi.org/10.1108/JMLC-04-2024-0069

1. Introduction

With the banking system classified as “the front door of money laundering” strongly regulated, “the back door” international trade, remains wide open (Zdanowicz, 2009, p. 1). Money laundering has a global impact, with international trade deemed the largest threat (Umar, 2023). The fight against money laundering remains a concern, especially given that South Africa ranked 13th among developing countries concerning illegal financial flows (IFFs), which includes trade-based money laundering (TBML) (Rapanyane and Ngoepe, 2020).

TBML allow perpetrators to transform criminal proceeds into “clean money” through figurative “laundromats”, causing the trail associated with dirty money to vanish (Liao and Acharya, 2011). The typical cleaning steps in money laundering are placement, layering and integration (Menz, 2019). International trade platforms make money laundering an enticing option, especially in countries with a high risk of capital flight, where political and economic turbulence are present (Schlenther, 2016). The increased focus on detecting financial crimes through various institutions has given rise to perpetrators exploring illegal options, like TBML, outside the financial systems (Tiwari et al., 2024).

TBML is a “process of disguising the proceeds of crime and moving value through trade transactions to legitimise their illicit origin” (FATF, 2018). IFFs are defined by the organisation for economic co-operation and development as “flows generated by methods, practices and crimes aiming to transfer financial capital out of a country in contravention of national or international laws” (Organization for Economic Co-operation and Development, 2014). The misrepresentation of trade transactions in IFF allows funds to move between international jurisdictions as a layering mechanism to hide funds’ illegal origin (Hetzler, 2022).

The remainder of the article is structured as follows: Section 2 provides a background into TBML schemes, highlighting the identification challenges. Section 3 conceptualises the literature review into the IFFs and misinvoicing in South Africa and the financial action task fource (FATF), anti-money laundering (AML) guidance. The country’s inability to curtail money laundering is outlined with several examples. Section 4 addresses the methodology adopted for the study, and Section 5 is followed by the results and discussion of findings. Finally, the conclusion and recommendations of the study are presented in Sections 6 and 7.

2. Background to trade-based money laundering schemes

Legitimate international trade systems can be used to move dirty money by misrepresenting the price, quality or type of goods using falsified documentation (Raza and Weirauch, 2021). Techniques by which TBML can be perpetrated include the under- and over-invoicing, over- and under-shipment of goods, multiple invoicing, ghost invoicing and falsely described goods and services (Tiwari et al., 2024).

The under- and over-invoicing of goods and services refers to where the price of goods and services are misrepresented to enable perpetrators to transfer the proceeds of illegal dealings across borders (Beverly, 2017). Over-invoicing for goods is popular with government purchases, where the value of the equipment is inflated so more government funding can be expatriated (Liao and Acharya, 2011). Unless freight forwarding companies (FFCs) and financial institutions can compare prices with the goods’ market value, under- and over-invoicing will likely remain undetected. Over- and under-shipment of goods is when more or fewer goods are shipped from the exporter to the importer than documented, resulting in a misrepresentation of the value of goods moved between jurisdictions (FATF, 2020).

Multiple invoicing is when the same invoice is used multiple times to move funds and, in the process, launder money (Hataley, 2020, p. 655). Multiple invoicing can be used successfully over an extended period by submitting duplicate invoices with minor changes to the invoice number that will not be easily detected (FATF, 2020). Ghost shipping is a technique where fraudulent documents are produced to make it appear as if the goods have been shipped (Tan, 2023). Ghost shipment can be combined with multiple invoicing, where supporting documentation relates to multiple shipments, but only one shipment is associated with the actual goods (FATF, 2020). Finally, falsely described goods and services are used to avoid paying duties and taxes or conceal the nature of exported goods, such as endangered wildlife (FATF, 2020). Forbidden or sanctioned goods can be moved by manipulating the goods’ descriptions on the trade documents (Morgan, 2020, p. 2). The above techniques are all typical layering techniques to hide funds’ illegal origin and value (Masrom et al., 2023).

FFCs are integral in shipping, customs processes and documentation that the South African Revenue Services (SARS) requires to collect duties and taxes (Kasif, 2021). FFCs’ knowledge and insight ideally position them to identify trade anomalies and red flags related to TBML (Chung et al., 2020). Despite the central role FFCs fulfil in the movement of goods, these companies have limited obligations to comply with AML measures or counter the financing of terrorism and unknowingly facilitate TBML (Chung et al., 2020). TBML is generally challenging to detect due to the volume and complexity of trade transactions, the use of multiple jurisdictions and the inability to obtain information on beneficial owners posing as trade partners (Geldenhuys, 2019). Table 1 summarises the challenges of identifying TBML schemes.

The value of IFFs that left South Africa in the past 10 years is estimated at US$20bn annually (Curson, 2021). The value of IFFs is expected to reach US$62bn (ZAR 1tn) by the end of 2023; this approximates 11% of the total losses attributable to TBML outflows in all developing countries (Cokayne, 2023). The impact of the high occurrence of IFFs is evident in the country’s financial instability and the high level of unemployment, which is currently at 32.1% (Bisseker, 2018; Cokayne, 2023). The FATF highlighted the inability to detect IFFs and corruption as contributors to South Africa’s grey-listing (FATF, 2020). If South Africa had kept abreast with other emerging economies, the country would have been 30% (or ZAR 1tn) wealthier, with 2.5 million more job opportunities available (Bisseker, 2018). The ongoing IFFs, political manipulation and after-math of state capture weaken the South African economy and erode opportunities for citizens’ betterment (Rapanyane and Ngoepe, 2020); there is a clear need to improve the detection of TBML if only to limit the flow of IFF.

3. Literature review

The literature review expands on IFF and mis-invoicing, followed by a discussion of the FATF’s guidance for AML while focusing more on TBML. Finally, the section unpacks South Africa’s shortcomings in TBML as an AML strategy.

3.1 Illegal financial flows and mis-invoicing in South Africa

In South Africa, where US$78bn (ZAR 1.5tn) was lost to corruption from 2014 to 2019, most losses have been attributed to state funds embezzled through state capture (Buthelezi, 2021). Labuschagne (2017) describe state capture as a state being captured by external third parties manipulating primary government functions at the expense of social welfare. A study conducted by Global Financial Integrity (GFI) assigns the composition of IFFs to three main contributors, with corruption contributing 5%, the proceeds of commercial tax avoidance at 65% and criminal activities at 30% (Mustafa et al., 2019). However, financial losses due to criminal activity, including corruption, likely contributed more than the estimated 30% (Mustafa et al., 2019). An inability to curtail the high volume of IFFs and a lack of active measures to curb this trend are attributed to poor governance (Rapanyane and Ngoepe, 2020).

The measurement of trade mispricing refers to the bilateral discrepancies in trade data when comparing partner-country reported trade statistics (UNCTAD, 2021). The measurement compares the average world price to the average country price for every product (Tiwari et al., 2024). GFI quantified the average annual value gaps between South Africa and their trade partners from 2010 to 2014 as US$7.3bn (GFI, 2018). Since TBML is included in IFFs, the value lost through TBML is incorporated in the IFF statistics. The value gaps are the difference between the average import value of US$92m and the average export value of US$88m.

3.2 The FATF anti-money laundering guidance

The FATF is a global inter-governmental body that develops policies to protect international financial systems against money laundering and terrorist financing (FATF, 2020). The FATF provides comprehensive AML guidelines and issued risk indicators that encapsulate indicators that suggest the likelihood of any unusual or suspicious activity pointing to TBML schemes (FATF, 2021b). Red flags and risk indicators cannot be used in isolation, though and require additional information regarding shipments and the parties to the transaction to confirm a transaction is illegal and that TBML is taking place (Hasita, 2022).

The FATF red flags are all equally important indicators of TBML schemes, but not all indicators fall within FFCs’ reach (Chung et al., 2020). The FATF’s risk indicators group the red flags into four categories: structural risk, trade activity risk, trade document and commodity risk and account and transaction activity risk indicators (Neverdauskas, 2021). Some indicators relating to financial transactions and company structures fall more within the reach of financial institutions. Indicators linked to shipping-related red flags pointing to TBML schemes fall within the reach of FFCs and companies in the shipping industry (FATF, 2021b). Table 2 highlights the TBML risk indicator guidelines and defines the differences between the various FATF guidelines in italics under each section. The table further summarises examples of the various indicators.

The table demonstrates the unusual and suspicious activities indicative of possible TMBL schemes. One or more unusual activity do not necessarily indicate the existence of TBML schemes but could be a red flag of a scheme and should be investigated. The role of the respective institutions is highlighted in the table, as institutions do not see all indicators and only have see indicators within their area of responsibility. For example, account and transaction activity risk indicators fall within the reach of financial institutions, whereas trade activity, trade documents and commodity risk indicators fall within the reach of FFCs. Risk indicators relating to structural aspects and corporate structures only point to possible red flags if analysed with the entity’s trade activity and/or the economic reasons for the transactions. The table highlights the need for a collaborative approach in investigating red flags across all spheres of customers’ trade movements.

3.3 South Africa’s shortcomings in trade-based money laundering anti-money laundering strategies

Despite a solid legal framework to combat money laundering and terrorist financing, strategic deficiencies were identified in South Africa’s ability to abide by the FATF’s AML guidelines (National Treasury, 2023). Identified shortcomings predominantly include the country’s inability to investigate and successfully prosecute perpetrators of financial crimes. Additional shortcomings are the country’s inability to proactively seek international cooperation and a lack of transparency in identifying prominent politically exposed persons (PEPs) (FATF, 2021b). Table 3 summarises the main shortcomings of the FATF’s recommendations and the occurrence of these areas, substantiated by quotes and extracts from media reports and publications on South Africa’s grey-listing.

The above table highlights that crimes are free to occur when the shortcomings highlighted by FATF are not addressed. Synergies exist between the shortcomings in combatting corruption, including TBML schemes and the strategic deficiencies highlighted by the FATF as part of South Africa’s grey-listing. One of the concerning facts reported by the FATF is the low conviction rate of prosecutors of money laundering-associated crimes, where only an average of 15% of investigations led to convictions in the period assessed by the FATF (FATF, 2021c).

4. Research methodology

There is a lack of research examining the prevalence and awareness of FFCs on the occurrence of TBML schemes and their underlying red flags. This study addresses this gap by interviewing experts to contribute to the body of knowledge. Expert interviews were conducted and analysed using a thematic analysis. Expert interviews allow for exploring theoretical concepts by linking them with practical experiences to gain new insights. Qualitative description (QD) is a qualitative research design that offers a comprehensive summary of an event in everyday terms (Sandelowski, 2000). The event refers to FFCs’ perceptions of and ability to detect and report TBML schemes. QD answers research questions by addressing the most pertinent questions about any event: who, what and where (Kim et al., 2017). This study followed face-to-face, semi-structured interviews with the participants in Table 4. The participants’ experience and industry knowledge were pertinent to the fact that all participants had extensive knowledge of the industry.

The interviews were guided around the interview questions in Table 5. The questions focused on identifying participant’s perceptions regarding their role in detecting and reporting TBML schemes.

The interviews were structured to gain insight into participants’ knowledge of TBML and the related techniques used. Results were obtained by asking the research questions, as shown in Table 5.

4.1 Semi-structured interviews

The study uses seven steps to conduct the semi-structured interviews in line with Adeoye-Olatunde and Olenik (2021). Semi-structured interviews focused on participants’ perceptions of and experience with trade anomalies or unusual trade transactions that can point to TBML. Interviews were conducted using open-ended questions to identify themes related to the detection and reporting of TBML. The seven steps followed in this study are summarised in Table 6.

The information obtained from interviews was analysed and coded using open coding. All pertinent issues were captured, and the results synthesised the interview responses.

5. Results

The research results were summarised in the three sections, flowing from the interview questions. Section 1 addresses the FFCs’ ability to identify TBML schemes and various techniques. Section 2 addresses the awareness of the FATF’s red flags and the presence of internal processes. Finally, Section 3 deals with the perception of collusion to commit TBML and reporting platform availability. Despite the participant’s years of experience in the field of freight forwarding and their involvement with FFC companies, the outcome from most participants was the same.

5.1 Section 1

5.1.1 The inability of FFCs to identify trade-based money laundering schemes.

The interviews with FFCs found that no or limited knowledge of TBML exists and that participants only became aware of TBML during the research interviews. Some participants became aware of TBML when state capture (the Estina Dairy Farm scandal) was reported in the media in December 2021. The evidence of state capture made FFCs aware for the first time that the trading platform was used as part of state capture. The overarching theme from interviews was that FFCs’ ability to detect TBML schemes could be improved; they need additional capacity and training to identify trade anomalies. The sentiment of Estina Dairy Farm raising awareness of TBML was highlighted by Participant 6:

I had a very strong suspicion that the goods being declared were overvalued, and at the time it didn’t make sense, and now I joined the dots to all those years ago. When we look at the Estina case, it is so overvalued to extract money from the Republic.

5.1.2 The prevalence of falsified documentation.

The ability of perpetrators to falsify documentation to affect illegitimate trade transactions emerged. As TBML schemes are coupled with complex company structures, using fake documentation was identified as one of the simplest but most effective techniques. Participant 4 had an insight into this practice:

They produce a dummy invoice to give to customs, you know, give customs a different invoice to the real one. I have come across that they have two versions of the invoice; the only difference is the value, and the one with the lower value is the one they present to customs.

5.1.3 Tax avoidance rather than the knowledge of underlying money laundering.

The perception was that TBML, especially under- and over-invoicing, were linked to avoiding duties and taxes, not money laundering. FFCs believed the primary objective of SARS is to detect tax avoidance, with the combatting of IFFs ranking second. FFCs’ view is that SARS does not treat incorrect invoicing as TBML. The measure SARS uses to rectify incorrect invoicing is to levy fines and penalties for the mis-valuation and misclassification of goods rather than investigate the possibility of TBML. Participant 2 made this comment: “SARS is purely tax; money laundering is far more complex because the banks should be involved in money laundering, and the banks have been pretty weak on that”.

5.2 Section 2

5.2.1 Awareness of the FATF red flags and the presence of internal processes.

A minority of participants knew about the FATF and associated red flags. However, all the participants agreed with the content of the red flags and agreed on their value and relevance in the detection of trade anomalies. Participants highlighted internal red flags implemented at the companies they were associated with, which were closely related to the content of the FATF red flags. The ability to verify beneficial ownership for the importer and exporter was possible for FFCs with larger global footprints and sophisticated control systems. In many cases, the local-based client’s shareholding structure could be verified, but verifying the ultimate shareholding structure was challenging. Participants agreed that verification should extend to the importer, exporter and all role players in the trade supply chain to verify beneficial ownership effectively. Multiple FFCs indicated that verifying complex company structures and instances with numerous overseas shell companies is challenging.

5.3 Section 3

5.3.1 Collusion between role players and the prominent exposed persons are instrumental in trade-based money laundering.

The consensus among participants was that collusion facilitates IFFs and TBML. It was opined that customs officials and other parties in the trade supply chain receive bribes to allow IFFs and TBML to be perpetrated, and bribes are escalated to the ultimate decision maker, often PEPs. The overarching perception among participants was that PEPs were often the instigators behind trade anomalies and IFFs. FFCs believe significant work is required to implement anti-fraud strategies and corrective measures to combat corruption. Due to the separation of duties, working together is not possible. “When you deal with large, organised crime groups or with PEPs, the initial court proceedings might be opened, but they don’t always proceed into full-blown court proceedings” (Participant 8). The aspect around collusion with the FFC’s involvement was raised by Participant 2:

If it’s a phantom shipment, it is going to be transported; it must be cleared and transported. Someone has got to pick it up in the dock and move it. The people who do phantom shipping have to control the clearing agent.

6. Recommendations

A higher detection rate can be achieved when a collaborative approach is followed, by which customs and shipping information are shared among role players (Hataley, 2020). Inconsistencies can also best be investigated when input is incorporated from foreign jurisdictions to compare import and export documentation and detect value gaps (GFI, 2018). Efforts have increased globally to develop social network analytics and artificial intelligence (AI) solutions to identify unusual activities and trade anomalies (Sinno et al., 2023; Delston and Walls, 2009) claim digitalisation and software are required to assist companies and law enforcers detect trade anomalies and red flags.

FFCs require further development to identify and report suspicious transactions to align with the global trend of innovative solutions. Amendments to financial intellegence centre (FICA) Act No. 38 of 2001 that became effective on 29 November 2022 included FFCs in classifying accountable institutions (Itzikowitz and Gunning, 2022). The result is that FFCs are included in the definition of Section 1 of the South African financial intelligence unit, the Financial Intelligence Centre (FIC), with additional obligations to report suspicious activities potentially linked to money laundering or terrorist financing (South Africa, 38/2001). These companies’ inclusion as accountable institutions of the FIC places a responsibility on FFCs to report unusual financial transactions to SARS and the FIC, in terms of Section 29 (South Africa, 38/2001). This additional reporting responsibility was a requirement only one participant alluded to.

A machine-learning platform using AI technology should be developed and implemented to allow for early prediction. AI will allow all parties within the trade supply are obliged to report suspicious activities. The proximity of SARS to all customs transactions and importer and exporter details places them in the best position to develop sophisticated analysis methods like AI. To allow for the detection and prevention of TBML, a starting point is required from where investigations can be initiated. Skilled resources with access to the necessary data, including data on PEPs and beneficial ownership, are needed to ensure successful prosecutions.

7. Conclusion

The limited knowledge amongst FFCs of the existence of TBML and the FATF is concerning, given the high prevalence of corruption and IFFs. However, detection of TBML is hampered by the volume and complexity of trade transactions and the lack of knowledge to identify schemes. The disconnect between role players and the inability to identify beneficial ownership adds another layer of challenges. If FFCs were more knowledgeable of the characteristics of TBML, early detection could be achieved.

Training programmes should be developed to create awareness of FFCs of TBML and the underlying red flags. To enable FFCs to detect and report TBML, an awareness of the characteristics and challenges of TBML schemes should be understood. Appropriate reporting processes should be adopted, including reporting to the FIC and SARS. A digital platform should be developed, allowing all role players to report anomalies and have access to skilled staff members who can collaborate with information from all parties. A collaborative approach is needed between financial institutions, customs regulators and FFCs to address the challenges and work towards a sustainable solution.

TBML is an area of future research in South Africa, as there is a limited understanding of the risks and red flags linked to this crime. The ability of financial institutions and SARS to detect and report on TBML can benefit South Africa. TBML has a crippling effect on the South African economy and its ability to improve the lives of all South Africans. The only way to reduce the embezzlement of funds is by concise action and a more active approach by FFCs.

Table 1.

Challenges in identifying TBML schemes

	Challenges	Discussion	References
1.	A lack of awareness of the existence of TBML	FFCs facilitate the movement of goods with a limited connection to the movement of the associated funds Role players are unaware of the FATF’s TBML trends and associated red flags	(FATF, 2020) (FATF, 2021a)
2.	Trade processes are paper-based	The detection of suspicious transactions using digital forensic data analysis is impossible if documents are paper-based Paper-based documents create opportunities to manipulate trade documentation	(Casanova et al., 2022)
3.	Large sections of the trade system are unregulated	The trading system is largely unregulated, making compliance with anti-money laundering (AML) or financing of terrorism laws less critical FFCs can unknowingly be involved in facilitating TBML just by their involvement in facilitating the movement of goods	(Chung et al., 2020)
4.	An inability to identify beneficial ownership	Ownership structures can be fabricated using complex structures and shell companies in various jurisdictions Falsified customer information will not flag trade anomalies. The use of shell companies with ownership below 5% will result in an exemption from the declaration of beneficial ownership information	(Naheem, 2015; Gilmour, 2022) (CIPC, 2023)
5.	A disconnect between multiple domains	Investigative authorities monitor predicate offences FFCs focus on the movement of goods with a limited focus on the movement of funds Financial institutions focus on the movement of funds, and customs authorities focus on collecting correctly calculated taxes	(FATF, 2020) (Greenburg et al., 2023)
6.	Advanced import payments	Advanced import payments can proceed without visibility of the goods As money moves between jurisdictions, a disconnect is created between the movements of goods and funds	(Neale, 2019; Gilmour, 2022)
7.	Customs officials are unable to verify the content of all containers	Less than 5% of all containers are inspected at the ports Criminals can hide the true nature of goods, opening the door to various illicit strategies	(Sinno et al., 2023)

Source: Authors’ compilation

Table 2.

TBML Risk indicator guidelines

Structural risk indicators
1.	When the search business activity differs from the business line stated or the entity is not present online
	Structural risk indicators refer to the complexity that TBML schemes create using corporate structures, such as shell companies
Trade activity risk indicators
2.	The entity’s transactions, shipping routes and general processes are inconsistent with standard business practices
3.	A newly formed/re-activated trade entity engages in high-volume and high-value trade activities. In contrast, an unknown entity engages in trade activities in sectors with high barriers to market entry
4.	Trade activity is inconsistent with the stated line of business of the entities involved, e.g. a car dealer that is exporting clothing
	The trade activity risk indicators refer to trade activities inconsistent with the stated line of business and complex trade deals involving numerous third-party intermediaries in incongruent lines of business
Trade document and commodity risk indicators
5.	Contracts, invoices or other trade documents vaguely describe the traded commodities
6.	Trade or customs documents supporting the transaction are missing and appear counterfeit. The documentation includes false or misleading information and is frequently modified and amended, including documents previously rejected
7.	Where commodities are imported into a country under the temporary importation and inward processing regime, they are exported using false documents after the import
8.	Goods and commodities are routed to jurisdictions and destinations that do not make commercial sense and cannot be justified
	Trade documents and commodity risk indicators refer to trade and customs documentation with vague descriptions or altogether missing documentation
Account and transaction activity risk indicators
9.	An entity makes payment for imported goods using a shell company or company other than the consignee of the goods and commodities. The outside company’s involvement cannot be justified, and there are no economic reasons for the party’s involvement
	Account and transaction activity risk indicators include high-value transactions that are processed relatively quickly, followed by dormancy

Source: Authors’ compilation developed from FATF (2021b), Jancsics (2018) and Neverdauskas (2021)

Table 3.

Strategic deficiencies and media coverage of crimes

Shortcomings in South Africa combatting TBML	Quotes and extracts from media reports and publications	References
(1) The country’s inability to pursue money laundering and terrorist financing is not aligned with its risk profile
The Judicial Commission of Inquiry, headed up by Judge Raymond Zondo, investigated allegations of State Capture from 2018 to 2022. The amount lost to state capture is estimated at US$17bn. A meagre attempt has been displayed to prosecute perpetrators and recover losses associated with state capture.	South Africa "lost R1.5 trillion to corruption in five years and continues to bleed” “Past poor policy decisions, inadequate maintenance, mismanagement, and state capture have left our electricity system in a state of real disrepair”. “The president says almost R3bn has been recovered from companies that had captured the power utility, while a further R5bn is being clawed back through legal processes.” “Whilst the conviction rate is high for money laundering cases prosecuted, the number of money laundering cases prosecuted from the referrals made is relatively low, averaging 15%.”	(Andrews, 2018; Buthelezi, 2021; FATF, 2021c; Madisa, 2022)
(2 )The country’s inability to proactively seek international cooperation
During the period of state capture, funds were expatriated to various jurisdictions without consideration of the suspicious nature of the transaction. The Bank of Baroda, based in India, failed to report highly suspicious activity on the respective accounts, enabling them to continue money laundering activities crippling the South African economy. The South African Reserve Bank (SARB) subsequently detected this activity. Limited international cooperation was visible in avoiding or flagging the fraudulent crimes linked to state capture and the repatriation of illegal financial flows.	“Paul holden testified to the commission and submitted thousands of pages of evidence that tracked, in fine detail, the flow of funds out of state-owned entities through corrupt contracts, into the guptas South African money laundering vehicles, and then offshore through laundering networks in jurisdictions like Hong Kong and the UAE.” “Estina was paying companies in the United Arab Emirates with no experience in farming. Much of the money was purportedly for a Free State farming venture.” “HSBC was central in providing the banking facilities—particularly to Tequesta and Regiments Asia in Hong Kong—that facilitated laundering the kickbacks from the Transnet deal for 1,064 locomotives.”	(Ensor, 2023; Marchant, 2022)
(3) An inability and lack of transparency in identifying PEPs
The FATF found that accountable institutions have a limited responsibility to identify PEPs. Financial institutions do not consider clients’ risk profiles at onboarding. This factor, coupled with the inability to verify beneficial ownership and transparency over corporate ownership, contributes to corruption.	“Parliament failed to exercise effective oversight between 2009 and 2017, and the majority of members largely chose to ignore the many red flags and did not hold the President and Ministers to account.” “The worst legacy of state capture is that it not only changed the culture of the public service… but also weakened the state's ability to make and implement decisions.” “Vrede dairy farm project: The case against ex-minister Zwane and co-accused has been transferred to the High Court”. “Outa (Organisation Undoing Tax Abuse South Africa) has filed a criminal complaint against the Deputy President with the NPA’s Investigating Directorate. It accuses David Mabuza of being involved in an R35bn land claims scam and crimes such as theft, fraud, perjury, and intimidation.”	(FATF, 2021c; Mitchley, 2022; Momoniat, 2023; NCA, 2022)
(4 )The country’s inability to detect illicit cash flows
The FATF reported high crime in South Africa, including tax crimes, corruption, etc., as part of their Mutual Evaluation Report (MER) in 2021. South Africa’s role as a regional hub for sub-Saharan Africa places the country at the forefront of foreign proceeds of crime, providing a gateway for illicit cash flows to flow from South Africa to the rest of the world. The amount of funds lost through state capture, estimated at roughly US$100bn, is evidence of the country’s inability to detect illegal cash flows.	“How the Guptas received their billions and moved it around, especially after they became unbankable, has mostly been a mystery. An extensive investigation by Scorpio and News24 into SARS and the Guptas’ VAT debacle pointed directly to the abuse of Bank of Baroda, SARS, third-party pay agents and shelf companies to artfully dodge financial regulators… according to insiders in two of the big banks of South Africa, the Hawks have never reacted to any of these suspicious transaction reports or threshold reports filed by the bank with the unit’s offices.”	(Buthelezi, 2021; FATF, 2021c; Van Wyk and Cowan, 2018)
(5) The country’s inability to improve the transparency of beneficial ownership for companies and trusts results in criminals hiding illegal activities behind various business or legal arrangements
The FATF found that limited access to accurate beneficial ownership information hinders the identification of legal entities and PEPs, especially when using trusts, founders and beneficiaries. Another limiting factor is that only the accuracy of South African directors is verified, mainly through financial institutions and credit databases. Beneficial ownership information is not promptly accessible by authorities, delaying detection.	“The evidence to the Zondo Commission demonstrates that the President already had a plan to capture Transnet within a month of taking office and, together with the Gupta family, started to implement a systematic plan for the state capture of key state-owned entities by November 2010. Implementation was affected by the appointment of a willing Minister to oversee state-owned entities, Eskom (power), Transnet (logistics and freight), PRASA (commuter trains), Denel (defence) and SAA (airline) contracts.”	(FATF, 2021c; Momoniat, 2023)

Source: Authors’ compilation

Table 4.

Details of participants

Participant	Gender	Years of experience in freight forwarding	The industry where participants emerge from
P1	Male	46 years	Freight forwarding and logistics
P2	Male	38 years	Freight forwarding and logistics
P3	Female	28 Years	Customs and international trade – legal compliance
P4	Male	26 years	Freight logistics and supply chain management
P5	Male	26 years	Freight forwarding and logistics
P6	Male	16 years	Customs compliance, freight forwarding
P7	Male	11 years	Freight forwarding and logistics
P8	Male	18 years	Forensic accountant, anti‐fraud programmes and controls

Source: Authors’ compilation

Table 5.

Interview questions

No.	Interview questions
Section 1	FFCs’ ability to identify TBML schemes and various techniques
Q1	Have you ever heard of TBML?
Q2	Have you come across these TBML techniques:
Q2.1	The under- or over-invoicing of goods
Q2.2	The over- or under-shipping of goods
Q2.3	Multiple invoicing for goods
Q2.4	Phantom/ghost shipping
Q2.5	The inclusion of false descriptions for goods and services
Section 2	Awareness of the existence of the FATF’s red flags and the presence of internal processes
Q3	Are you aware of the FATF red flags that will assist in identifying TMBL schemes?
Q4	Do you have processes to detect trade anomalies, like illogical shipping routes, pointing to TBML schemes?
Q5	Do your internal processes verify beneficial owners?
Section 3	Perceptions about collusion to commit TBML and the availability of reporting platforms
Q6	Is collusion and PEPs’ involvement in exporting goods contributing to the commitment of TBML?
Q7	Are reporting platforms available where trade inconsistencies can be reported to law enforcement?
Q8	Are the identities of whistle-blowers kept anonymous?
Q9	Has any feedback been received from law enforcement where cases were reported?

Source: Authors’ compilation

Table 6.

Data collection and analysis steps

No.	Interview steps	Description of the step
1	Assess the appropriateness of semi-structured interviews and determine the best method to address the research objectives	Individual semi-structured interviews were conducted to address research objectives as they best address complex social-behavioural research questions Social-behavioural research refers to how people behave in certain situations. Participants’ perspectives help researchers better understand the status quo and areas for improvement
2	Sampling and participant recruitment	Recruitment was purposive, also known as judgement, subjective or selective sampling The rigour and quality of data were promoted by ensuring the data’s authenticity and the trustworthiness of the sampling process
3	Data collection design	Data were collected based on the interview guide, which contained questions to address the research objectives The participants’ demographic information regarding age, gender and background could be considered to categorise participants but was deemed irrelevant
4	Conducting interviews, transcription, data transmission and storage	Interviews were conducted in person, via video call and audio recorded to capture data effectively Data were transmitted securely and stored in the cloud
5	Data analysis	The data analysis strategy was determined before data were collected, ensuring that all pertinent issues were captured Interview data were analysed and coded using open coding. A key coding frame labelled topics, commonalities and differences
6	Concluding	A conclusion was reached based on interview information. Pertinent questions were asked, derived from common themes from existing literature The strength of the conclusion was aligned with the rigour of the study’s design and data collection method
7	Reporting results	Reference was made to the study’s guidelines, ensuring all pertinent issues were addressed. Qualitative results displayed supporting data (quotes) in the text

Source: Authors’ developed from Adeoye-Olatunde and Olenik (2021) and Sargeant (2012)