Uncovering Trade-Related Money Laundering and Financial Networks in the Horn of Africa

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Using macroeconomic data, trade records, social network analysis, and interviews, the article illustrates how practices such as trade misinvoicing, commodity smuggling—particularly gold, fuel, and livestock—and informal value transfer systems enable money laundering. Key methods include employing third-party intermediaries, exploiting free zones and diaspora routes, and leveraging country-specific vulnerabilities, such as Ethiopia's market risks, Somalia's clan-based IVTS, Eritrea's covert pathways, Djibouti's role as a transit hub, and Sudan's patronage linked to extractive industries. TBML remains a widespread challenge worldwide; enforcement in one nation often shifts illicit activities elsewhere. Money launderers adapt to evolving global AML/CFT regulations. To combat TBML effectively, strategies should include regional cooperation, enhanced trade transparency, reform of customs procedures, and the development of community-based IVTS that extend beyond enforcement. Cross-border smuggling Diaspora remittances Illicit financial flows Informal value transfer systems (IVTS) / hawala Trade-based money laundering INTRODUCTION Cross-border financial activities are essential to the global economy and encompass both legitimate trade and illicit transactions (Prasad, 2023 ). Shadow networks, such as IVTS (e.g., hawala), pose risks but also facilitate remittances (ASSESSMENT, 2025 ). Practices such as TBML exploit regulatory gaps, enabling illicit flows that threaten stability and trust (Webb, 2025 ). Organizations, including the UN and the FATF, emphasize the importance of international cooperation in combating smuggling and financial crimes (Ohinok & Kopylchak, 2024 ). Although diaspora remittances support households, their informal transfers often avoid regulation, increasing the risk of organized crime (Rodima-Taylor, 2022 ). The Horn of Africa is highly vulnerable to trade-based money laundering (TBML) because of its key maritime corridors, land borders, and widespread diaspora networks (Iyandaa, 2024 ). TBML operates as a regional system that integrates illicit financial activities with legitimate trade in commodities such as gold, fuel, and livestock (Sivaguru & Tilakasiri, 2023 ). Issues such as weak customs enforcement, inadequate AML infrastructure, and reliance on informal remittance channels exacerbate these laundering pathways (Jayasekara, 2023 ). This article examines practices, financial inclusion, and security, emphasizing a cross-border approach to TBML, as policies in one country impact laundering elsewhere. It addresses three questions: standard TBML methods; how capacity and conflicts shape networks; and strategies to reduce risks while protecting remittances. Using trade analysis, social network mapping, and interviews, it aims to inform policies for regional cooperation and customs reforms. The article reviews theories, country comparisons, network analyses, policy options, and proposes a roadmap to enhance remittance security and capacity, urging policymakers to balance economic and security priorities. THEORETICAL AND EMPIRICAL LITERATURE REVIEW Cross-border financial activities impact the global economy through both legitimate trade and illegal transactions (Bojic, 2022 ). Informal value transfer systems (IVTS), such as hawala, support essential remittances but pose risks, including trade-based money laundering (TBML), regulatory gaps, and large illicit financial flows (IFFs), which can threaten economic stability (Webb, 2025 ). The UN and the FATF highlight the importance of international cooperation to combat economic crimes, acknowledging that diaspora remittances are crucial to household well-being yet are often unregulated, raising concerns about potential criminal activity (Muse, 2025 ). The literature describes trade-based money laundering (TBML) in the Horn of Africa as a complex and adaptable system that involves trade misinvoicing, commodity smuggling, and informal value transfer systems (IVTS) (Fakih, 2022 ). It underscores the importance of mixed detection strategies, regional cooperation, and engagement with remittance channels (Olivie & O'SHEA, 2022 ). Insights from political economy, network theory, and informal finance illuminate TBML's resilience by highlighting legal gaps, social legitimacy, and flexible networks (Malik, 2025 ). Empirical studies identify trade misinvoicing and commodities such as gold and fuel as primary TBML techniques, with country-specific research highlighting unique vulnerabilities and operational dynamics (Carbonnier & Marur, 2024 ). In Africa, remittances and IVTS both demonstrate community resilience and reveal system vulnerabilities (Webb, 2025 ). The African Union estimates that IFFs siphon more than USD 50 billion annually and supports regional efforts through initiatives such as the AU Convention on Preventing Corruption (Ayalew, 2026 ). Sub-regional groups, such as the East African Community, aim to standardize regulations to protect legitimate funds and to close gaps in the criminal justice system (Kibochi, 2022 ). Recent studies combine trade gap analysis, social network mapping, and fieldwork despite limited data (Taha & Abdallah, 2025 ). Evidence indicates laundering techniques adapt with enforcement, often involving intermediaries and larger cash transfers (Makmur, 2024 ). These findings underscore the need for further research, especially on transaction-level IVTS data and long-term analyses (Hamadeh et al., 2025 ). They also emphasize the interconnectedness of these issues and call for balanced policies that address both economic and security concerns (Cramaro, 2024 ). METHODOLOGY This methodology employs a mixed-methods comparative approach to identify trade-based money laundering (TBML) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. It combines mirror trade analysis, customs audits, social network mapping, and fieldwork, with a focus on reproducible indicators and the safeguarding of informants. Covering 2010 to 2024, it compares similar systems and examines trade misinvoicing, commodity laundering, and their connections to informal value transfer systems (IVTS). The research produces a CSV matrix of illicit flow estimates, including country, year, estimate, confidence, quality, methods, and notes from UN COMTRADE, IMF, and the World Bank. Data collection involves macro trade data, customs audits, interviews, and open-source investigations. Analytical techniques include quantitative detection, social network analysis, process tracing, and qualitative comparative analysis (QCA). The study maintains reliability and reproducibility through detailed codebooks and dual independent coding. Ethical practices encompass informed consent and bias reduction via triangulation. Results comprise case reports, vulnerability indices, and policy briefs, which are validated through back testing and audits. RESULTS AND DISCUSSIONS This framework analyzes trade data, customs audit records, and insights from Ethiopia, Somalia, Eritrea, Djibouti, and Sudan from 2010 to 2024, highlighting trade anomalies and institutional issues. It covers: 1. Macro Trade Data (2010–2024): Identifies misinvoicing and irregularities, like Ethiopia undervaluing coffee and livestock, Somalia's phantom trade, Eritrea's opaque mineral exports, Djibouti’s invoicing issues, and Sudan’s underreporting of fuel and machinery to evade sanctions. Indicators include price gaps, trade spikes, and trade-to-GDP discrepancies. 2. Customs Audits: Focus on cargo and financial checks. Ethiopia’s ASYCUDA detects undervaluation; Somalia relies on external audits; Eritrea’s customs are rarely audited; Djibouti’s digital, risk-based port audits are improved; Sudan reforms target gold and fuel. Findings include undervaluation, phantom shipments, and misclassification. 3. Qualitative Insights: Cover institutional and social networks like Ethiopia’s trader groups and diaspora remittances; Somalia’s clan-based hawala networks; Eritrea’s family remittances; Djibouti’s shipping firms; and Sudan’s gold traders and smuggling routes, highlighting reliance on informal systems and hotspots for TBML. 4. Cross-Cutting Insights: Ethiopia and Sudan show mispricing; Somalia’s flows are opaque. Djibouti has stronger audits; Somalia’s are weakest. Networks underpin TBML in Somalia, Eritrea, and Sudan. 5. Protective Measures: Suggest linking customs data with UN Comtrade, increasing audits, applying social network analysis, and regional joint audits. Overall, Sudan and Somalia face high risks; Djibouti and Ethiopia have better capacity but are vulnerable. Eritrea’s opacity raises mineral trade risks. Table 1 Comparative Matrix for TBML Detection in the Horn of Africa Country Key Vulnerabilities Detection Mechanisms Institutional Capacity Regional Cooperation Ethiopia - Large informal trade networks - Weak customs valuation controls - High cash-based economy - Customs modernization (ASYCUDA system) - FIU under the National Bank of Ethiopia - FIU operational, but with limited resources - AML laws are aligned with FATF, but there is weak enforcement - Member of ESAAMLG - IGAD cooperation on AML/CFT Somalia - Predominantly informal economy - Hawala networks dominate - Weak border control - Limited customs oversight - Reliance on informal reporting - UN-supported AML frameworks - FIU exists but is fragile - AML law (2016) is weakly enforced - IGAD member - Regional AML training initiatives Eritrea - Isolated financial system - Heavy reliance on cash - Weak trade transparency - Customs oversight is limited - FIU under the Ministry of Finance - AML/CFT framework recently evaluated (2025 MER) - Weak compliance culture - ESAAMLG member - Limited regional integration Djibouti - Strategic port hub vulnerable to over/under-invoicing - High volume of transshipment - Customs risk profiling - FIU under the Central Bank - Port monitoring systems - FIU is relatively stronger - AML law aligned with FATF - ESAAMLG member - Regional AML/CFT projects Sudan - Sanctions legacy → informal trade - Gold smuggling - Weak customs valuation - FIU under the Central Bank - Customs reforms are ongoing - AML law exists, but enforcement is weak - FIU capacity limited - ESAAMLG member - IGAD AML/CFT cooperation Source: Completion Author,2026 Table 1 outlines key indicators of Trade-Based Money Laundering (TBML), including over- and under-invoicing, phantom shipments, misclassification of goods, circular trade routes, and informal systems such as hawala. It also presents a comparative matrix that analyzes TBML vulnerabilities and detection strategies in the Horn of Africa. Common weaknesses in these countries include informal trade networks, inadequate customs procedures, and a high degree of dependence on cash economies. Detection methods, including customs modernization and Financial Intelligence Units (FIUs), differ by country, with Ethiopia and Djibouti demonstrating greater capacity. While all countries participate in regional initiatives such as ESAAMLG and IGAD, their institutional capacity and enforcement of Anti-Money Laundering (AML) laws remain limited, particularly in Somalia and Sudan, where frameworks are poorly implemented. The methodology combines trade analysis, audits, network mapping, and fieldwork for effective TBML prevention. The region faces challenges such as weak customs infrastructure, informal economies, limited resources for FIUs, and political instability. Areas for improvement include regional data sharing, capacity building for customs and FIU staff, the use of technology, and the fostering of public-private partnerships. Ethiopia and Djibouti have stronger arrangements, whereas Somalia and Eritrea are more vulnerable due to their informal economies. Sudan faces specific risks related to gold smuggling and sanctions, underscoring the need for regional cooperation to enhance the detection of TBML. This framework presents strategies to identify and prevent trade-based money laundering (TBML) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. It encompasses trade analysis, customs audits, social network mapping, and field investigations. Core activities include identifying anomalies in trade values and routes, validating invoices and shipments through customs checks, mapping TBML networks, and confirming trade flows through field research. Additional safeguards include regional data sharing and engaging local communities. Table 2 Comparative Matrix for the TBML Detection and Protection Framework Method Ethiopia Somalia Eritrea Djibouti Sudan Trade Analysis Use ASYCUDA customs data to compare declared vs. global market prices; monitor coffee & livestock exports. Focus on hawala-linked trade flows; monitor consumer-goods imports relative to remittance inflows. Limited transparency; track discrepancies in mineral exports High-volume port trade; monitor transshipment & re-export patterns Gold exports & imports of machinery; compare declared vs. actual flows Customs Audits Randomized audits of invoices; cross-check with banks Weak customs → rely on NGO/UN-supported audits State-controlled customs; limited external audits Stronger port customs; risk-based audits possible Customs reforms underway; audits needed for gold & fuel Social Network Mapping Map trader networks in Addis Ababa & border towns; identify clusters of repeated undervaluation Hawala operators & clan-based trade networks; map remittance corridors Map diaspora-linked trade flows; identify family-based networks Shipping companies & freight forwarders; map links to regional hubs Map gold traders & informal networks; identify cross-border smuggling routes Fieldwork Border studies (Kenya, Sudan, Djibouti) to observe informal trade Field surveys of hawala operators & traders in Mogadishu On-the-ground interviews are limited; diaspora fieldwork abroad Port observation & interviews with freight handlers Fieldwork in gold markets & border towns (Darfur, South Sudan) Reproducible Indicators - Price gaps vs. UN Comtrade - Repeated undervaluation - Cash-heavy transactions - Hawala remittance vs. trade mismatch - Phantom shipments - Mineral export discrepancies - Cash vs. declared trade - Over/under-invoicing - Transshipment anomalies - Gold export mismatch - Sanctions evasion patterns Protective Measures Strengthen FIU & customs IT systems Build AML capacity via UN/World Bank projects Increase transparency & external audits Enhance port monitoring & FIU cooperation Focus on gold trade transparency & sanctions compliance Source: Completion Author,2026 Table 2 presents key insights into the reproducibility of trade analysis, comparing customs value data across five countries. It features a matrix for the TBML (Trade-Based Money Laundering) detection and protection framework involving Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Core strategies include using customs data, monitoring remittance-related trade, and identifying export discrepancies. Customs audits vary from Ethiopia's random procedures to Sudan's need for reforms. Social network mapping involves tracing trader networks and remittance paths. Fieldwork encompasses border studies and interviews to observe informal trade. Preventive efforts focus on strengthening financial intelligence units and enhancing transparency across sectors, with indicators such as price gaps and trade mismatches being key for reproducibility. It highlights the significance of conducting randomized audits despite varying capacity levels. Mapping social networks is crucial for identifying trade-based money laundering (TBML), particularly in Somalia and Eritrea, with fieldwork corroborating the observed patterns. Indicators like price differences and phantom shipments are measurable. To address these challenges, it is advisable to share data across regions to standardize customs databases, strengthen training for customs officials, upgrade trade-monitoring technology, and involve communities to build trust. Table 3 Comparative Matrix (2010–2024) of Trade Misinvoicing, Commodity Laundering, and Informal Value Transfer Systems (IVTS) Country Trade Mis-invoicing Commodity Laundering IVTS Interactions Trend 2010–2024 Ethiopia Persistent undervaluation of coffee & livestock exports; over-invoicing of imports (machinery, fuel) Laundering via agricultural commodities (coffee, khat); some gold smuggling Hawala networks linked to diaspora remittances; overlap with trade flows Gradual customs modernization (ASYCUDA); FIU capacity improved, but enforcement is uneven Somalia Phantom imports/exports common; weak customs → misinvoicing rampant Laundering through livestock exports & consumer goods imports Hawala dominates; clan-based IVTS central to trade & remittances AML law (2016) was introduced but weakly enforced; reliance on informal systems persists Eritrea Limited transparency; misinvoicing in mineral exports (gold, copper) Commodity laundering via the state-controlled mining sector Diaspora remittances via hawala-like channels; family-based IVTS Isolation limited external audits; AML/CFT framework slowly evolving post-2015 Djibouti Over/under-invoicing in port transshipment; misdeclared re-exports Laundering via shipping & logistics, the fuel/oil trade is vulnerable IVTS is less dominant; formal banking is stronger, but informal cash is still used Port modernization strengthened customs; FIU is relatively stronger than its neighbors Sudan Mispricing in gold exports; under-invoicing of imports (fuel, machinery) Commodity laundering via gold smuggling; sanctions evasion Hawala & informal networks key for cross-border trade (Darfur, South Sudan) Post-sanctions reforms (2017+) improved AML laws, but enforcement remains weak Source: Completion Author,2026 Table 3 illustrates data from 2010 to 2024, highlighting trade misinvoicing, commodity laundering, and informal value transfer systems (IVTS) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Ethiopia consistently undervalued coffee and livestock exports, overinvoiced imports, and engaged in gold smuggling. Somalia's weak customs systems led to widespread misinvoicing, while Eritrea lacked transparency and external audits. Djibouti's port upgrades improved customs enforcement, whereas Sudan faced issues with mispricing of gold exports and smuggling. Key findings reveal trade misinvoicing, commodity laundering, and the use of informal value transfer systems (IVTS) throughout the Horn of Africa. In Ethiopia and Sudan, trade misinvoicing is particularly prevalent in the agricultural and gold sectors, whereas in Somalia, invoice manipulation is widespread. Djibouti functions as a transshipment hub. Commodity laundering is standard in Sudan and Eritrea with gold, in Ethiopia and Somalia with livestock and coffee, and in Djibouti and Sudan with fuel. Somalia's Hawala system dominates trade and remittance flows, with Ethiopia and Sudan also seeing significant diaspora remittances. The region has shifted from reliance on informal systems (2010–2015) to the adoption of AML laws (2016–2020) and digital customs systems (2021–2024), along with improved regional cooperation, although enforcement gaps persist. Recommended measures include modernizing customs, improving commodity transparency, regulating IVTS, and strengthening regional collaboration. Sudan and Somalia are high-risk due to gold smuggling and reliance on hawala, whereas Djibouti and Ethiopia have stronger institutions but still face vulnerabilities. This section explores how macro trade detection, customs audits, social network analysis, and qualitative tracing identify trade-based money laundering (TBML) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Findings indicate persistent trade deficits, particularly in high-value commodities, with Sudan and Djibouti exhibiting the most significant discrepancies. The region exhibits trade misinvoicing and operational vulnerabilities. The TBML risk index varies across countries, with Somalia and Eritrea relying on remittances. Social network analysis reveals decentralized facilitator networks and chokepoints in major ports. Enforcement actions can precipitate rapid shifts in networks, and TBML techniques, such as trade misinvoicing and commodity laundering, are examined. Displacement effects are evident: enforcement shifts illicit activities to areas with weaker oversight, thereby affecting households that rely on formal remittances. Table 4 Cross-Case Comparative Synthesis of Trade-Based Money Laundering (TBML) Dimension Dominant TBML modality Primary enablers Most effective disruption point Ethiopia Fuel and textile misinvoicing; IVTS layering Large internal market; mixed customs capacity Mirror-trade monitoring + IVTS pilots Somalia IVTS-enabled layering; port commodity smuggling Clan networks; weak port customs Community-led IVTS engagement + port audits Eritrea Opaque export routes; commodity concealment Sanctions environment; state control Multilateral targeted asset measures Djibouti Transit misinvoicing; free-zone absorption Strategic port; free-zone opacity Port analytics + customs valuation Sudan Gold and livestock commodity laundering Extractive rents; patronage networks Asset recovery + commodity chain audits Source: Completion Author,2026 Table 4 shows that trade-based money laundering (TBML) persists in the Horn of Africa through methods like trade misinvoicing and IVTS. Ethiopia primarily misinvoices fuel and textiles, monitors mirror trades, and pilots IVTS. Somalia's TBML involves layering via IVTS and smuggling, using clan networks and weak customs, with community engagement and port audits recommended. Eritrea's TBML encompasses opaque export routes and commodity concealment, often driven by sanctions, and multilateral asset measures have been proposed to address these. Djibouti faces transit misinvoicing at a key port, supported by analytics and valuation assistance. Sudan's TBML involves the laundering of gold and livestock through patronage; asset recovery and commodity audits are recommended. The passage highlights the crucial role of social legitimacy in IVTS, emphasizing how institutional weaknesses can be exploited, and stresses the importance of policy measures targeting chokepoints rather than just channels. It advocates asset recovery strategies and phased pilots for IVTS registration, combined with evidence-based enforcement, to reduce political bias. Challenges such as data gaps and detection biases—particularly toward invoice fraud rather than physical concealment—point to the need for ongoing research. The analysis concludes that TBML is a complicated, cross-border issue that demands regional coordination and safeguards to protect legitimate remittance flows. POLICY RESPONSE The regional policy promotes initiatives to improve financial inclusion and combat trade-based money laundering (TBML). It includes engaging with informal value transfer systems (IVTS), updating customs procedures, and strengthening community resilience. Key focus areas involve protecting remittances, pinpointing intervention points, and ensuring fair asset-disruption practices. The strategy outlines six actions: 1) Simplify IVTS registration and training, 2) Apply trade analytics and audits to detect misinvoicing, 3) Facilitate data sharing among financial intelligence units (FIUs), 4) Target assets through legal channels, 5) Boost community resilience with cash aid and financial literacy, 6) Secure donor funding for pilot projects and assessments. These actions will be implemented in sequence to assess impact, promote local ownership, and minimize displacement risks. Table 5 Comparative Implementation Matrix (Related to Remittances) Measure Ethiopia Somalia Eritrea Djibouti Sudan IVTS formalization Pilot urban registration Community-led onboarding Confidential onboarding Mobile money KYC Border corridor pilots Customs analytics Fuel/textiles focus Port audits in Mogadishu Export verification Free-zone container scoring Gold/livestock audits FIU cooperation Active participant Donor-supported nodes Selective, multilateral Port-FIU integration Transitional FIU strengthening Asset disruption Targeted freezes Narrow sanctions on facilitators Multilateral evidence-based freezes Port facilitator sanctions Asset-recovery task force Source: Completion Author,2026 Table 5 details remittance efforts in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Ethiopia pilots urban registration for IVTS; Somalia uses community onboarding; Eritrea employs confidential onboarding; Djibouti uses mobile-money KYC; and Sudan's border projects. For customs, Ethiopia targets fuel and textiles; Somalia audits Mogadishu ports; Eritrea verifies exports; Djibouti assesses free-zone containers; and Sudan audits gold and livestock. FIU cooperation is active in Ethiopia, donor-supported in Somalia, selective in Eritrea, port-integrated in Djibouti, and transitional in Sudan. Asset disruptions include targeted freezes in Ethiopia, narrow sanctions in Eritrea, evidence-based freezes in Djibouti, sanctions on port facilitators in Sudan, and an asset recovery task force across all countries. It also emphasizes risks related to remittances, such as driving them underground, which can be mitigated through tiered thresholds, exemptions, and incentives for formalization; politicized enforcement, which can be addressed by independent review panels and multilateral evidence standards; and capacity gaps, which can be bridged with donor-funded, phased technical assistance and pooled procurement. LEGAL FRAMEWORK AND THE JUSTICE SYSTEM This section examines the legal structures, institutional functions, and the interactions among justice systems that impact the detection, investigation, and prosecution of trade-based money laundering (TBML) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. It emphasizes how statutory laws, Financial Intelligence Units (FIUs), customs authorities, prosecutorial powers, mutual legal assistance (MLA), and judicial protections work together. The goal is to identify legal methods to effectively disrupt TBML while ensuring that legitimate remittances and due process are not compromised. Table 6 Overview of the Legal Framework Dimension Ethiopia Somalia Eritrea Djibouti Sudan AML/CFT statute National AML/CFT law; asset-forfeiture provisions Fragmented/uneven across federal/regional levels Limited public transparency; state control over finance Fundamental AML law; gaps in enforcement Mixed legacy laws; transitional reforms underway FIU Operational FIU with donor support Nascent/weak FIU presence; donor nodes Limited FIU engagement; selective cooperation Small FIU; constrained resources FIU exists but is politicized; its capacity is uneven Customs & trade law Formal customs code; valuation gaps Weak port controls; informal customs practices Centralized export controls; opaque documentation Port/free-zone legal regime; valuation vulnerabilities Customs weakened by conflict and patronage Prosecution & courts Formal prosecutorial units; capacity gaps Hybrid justice; weak formal prosecution Centralized, politicized judiciary Minor judiciary; limited financial crime experience Courts affected by instability; selective enforcement MLA & cross-border cooperation Growing bilateral MLAs; regional engagement Reliant on UN/NGO channels; ad hoc MLAs Selective, confidential cooperation Strategic partner for regional trade; limited MLAs Improving MLAs under transition; fragile mechanisms Key legal risk Implementation and politicization Criminalizing IVTS risks harming remittances Sanctions and state embedding hinder transparency Free-zone opacity and transit risks State capture of illicit trade resists reform Source: Completion Author,2026 Table 6 summarizes AML/CFT legal frameworks in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Ethiopia has a comprehensive asset-forfeiture law, whereas Somalia's system is fragmented, and Eritrea lacks transparency. Djibouti has fundamental laws but enforcement issues, and Sudan's system is mixed, undergoing reforms. Ethiopia's FIU is functional but weak; Somalia's is limited; Djibouti's is small; and Sudan's is politicized. Customs laws vary widely—from Ethiopia's formal code to Somalia's weak port controls and Eritrea's centralized export controls. Prosecution systems face challenges: Ethiopia has formal units but capacity gaps; Somalia’s justice system is hybrid; Eritrea's judiciary is centralized and politicized. Cross-border cooperation is improving but still faces regional issues. Legal risks include gaps in law enforcement, politicization, criminalization of IVTS, sanctions, and opacity within free zones. Ethiopia criminalizes money laundering and terrorist financing, with support from the Central Bank and a functional FIU, but implementation remains problematic. Somalia's fragmented system complicates enforcement; Eritrea's lack of transparency hampers reforms, though centralized control offers some potential. Djibouti's robust legal framework and port support for enforcement, but free-zone opacity poses vulnerabilities. Sudan struggles with enforcement due to legacy laws and ongoing reforms. Key needs include operationalizing FIUs, integrating customs systems, and enhancing asset recovery. It provides model legal clauses on Trade-Based Money Laundering (TBML) and describes legal frameworks in the Horn of Africa, including Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Key clauses address the registration of informal value transfer systems, asset freezes, and mutual legal assistance, with metrics for assessing enforcement. Ethiopia's system blends civil and common law with AML regulations, while Somalia faces enforcement issues due to state fragility. Colonial legacies continue to influence Eritrea and Djibouti, which require international aid, while Sudan is undergoing reform amid instability. The document emphasizes harmonizing legal definitions, improving reporting, and adopting risk profiling, with regional cooperation showing that combining legal reforms and technology enhances enforcement. This result covers legal and judicial responses to Trade-Based Money Laundering (TBML) in the Horn of Africa, focusing on Ethiopia while also examining Somalia, Eritrea, Djibouti, and Sudan. Ethiopia's legal system, as set out in the constitution, supports anti-money laundering efforts by combining civil-law and customary practices, criminalizing money laundering in the financial and trade sectors, and aligning with FATF and UN standards. Somalia's fragile state weakens law enforcement; Eritrea faces enforcement issues due to limited information and a government-controlled banking sector. Djibouti employs civil-law systems for ports and trade zones, with international AML support. Sudan's recent reforms aim to boost financial transparency despite ongoing political instability. The findings highlight the importance of global frameworks, such as the FATF and the WCO, in setting TBML standards, with emphasis on reporting, cross-border cooperation, and risk assessment tools. The report also notes transnational challenges and legal gaps, showcasing successful enforcement collaborations and legislative alignment among regional countries. Enhancing justice systems in the Horn of Africa to combat Trade-Based Money Laundering (TBML) involves strengthening investigative skills, addressing capacity gaps, and establishing procedural protections. Key tools include Suspicious Transaction Reporting (STR), Mutual Legal Assistance (MLA), and asset forfeiture. Currently, weaknesses exist in forensic expertise, customs enforcement, and judicial independence. Reforms should focus on quick asset freezes with clear timelines, evidentiary standards, and witness protections. SPECIAL PROGRAMS, ENFORCEMENT, AND INSTITUTIONAL MECHANISMS Enhancing justice systems in the Horn of Africa to combat Trade-Based Money Laundering (TBML) involves improving investigative and prosecutorial expertise, addressing capacity gaps, and implementing procedural safeguards. Key instruments such as Suspicious Transaction Reporting (STR), Mutual Legal Assistance (MLA), and asset forfeiture are essential, yet challenges persist in forensic capabilities, customs enforcement, and judicial independence. Reforms should include asset freezes, clear evidentiary standards, and the protection of witnesses. Legal frameworks need to align with international norms, bolster financial intelligence units, utilize technology for monitoring, and engage communities. A phased, regional strategy should focus on formalizing informal value transfer systems, employing targeted customs analytics, and establishing joint task forces. Recommendations emphasize capacity development in the banking and customs sectors, the adaptation of STR procedures, and the strengthening of regional cooperation to combat TBML across Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. A phased regional approach is proposed to combat trade-based money laundering (TBML) in the Horn of Africa. It involves formalizing informal value transfer systems (IVTS) and strengthening cooperation between financial and customs agencies through programs such as compliance plans, port trade initiatives, joint teams, and a community resilience fund. Structures such as a regional FIU platform and fusion cells for cross-border intelligence are planned over 36 months, with a focus on risk assessments, pilot registration, and investigations, and with metrics for monitoring. Challenges such as capacity gaps, the informal sector, and enforcement issues call for improved regional cooperation, adapted suspicious transaction reporting, and targeted efforts to address informal financial systems to tackle TBML in Ethiopia and neighboring regions. CONCLUSION AND POLICY RECOMMENDATIONS Trade-Based Money Laundering (TBML) in the Horn of Africa is a widespread and adaptable network that exploits porous borders and informal transfer methods such as hawala. It involves practices such as trade misinvoicing and commodity laundering across countries, including Ethiopia, Somalia, Eritrea, Djibouti, and Sudan, with regional networks adapting in response to enforcement efforts. The study highlights that punitive measures alone are insufficient; a coordinated, evidence-based approach is necessary to disrupt illicit financing while protecting legitimate economic activities. Key insights include the interconnected tactics of TBML, the concentration of facilitators, the network's resilience despite enforcement actions, societal acceptance of informal systems, and institutional disparities that enable arbitrage. Effective strategies should incorporate customs analytics, collaboration among financial intelligence units, targeted legal measures, and community resilience programs. Policy guidance on combating trade-based money laundering (TBML) in the Horn of Africa emphasizes the importance of regional cooperation, improved customs procedures, and strengthening community resilience. Key measures include creating a Horn FIU and Customs Coordination Platform for data exchange, applying mirror trade analysis to identify misinvoicing, and deploying proportional IVTS with minimal registration. This entails analytics, customs inspections, formalizing IVTS, boosting data sharing, and conducting pilot tests. It is vital to align laws with international standards, bolster financial intelligence units, utilize technology, and engage communities. A cohesive regional strategy is crucial for dismantling TBML networks and maintaining economic stability across Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. The strategy involves TBML risk assessments, joint task forces, and the expansion of pilot programs over 36 months, with success indicators including remittance shares, trade discrepancies, and community trust. Risks are addressed through regular reviews and exemptions. Declarations Ethical Approval and Consent to Participate : Not applicable. Ethical approval was secured, and all research activities received protocol approval from the MU College of Health Sciences, Institutional Review Board MU-IRB2624/2025. Consent for Publication : Not applicable. Conflict of interest: No conflicts of interest have been reported. Funding: No sources have funded either the research or this article. Author Contribution Berihu Teweldebirhan Gebresilassie, as the corresponding author, drafted the main manuscript References ASSESSMENT, A. R. (2025). ILLICIT FINANCE AND AFRICA. Ayalew, B. B. (2026). Curbing Illicit Financial Flows from Developing to Developed Nations: A Call for Global Accountability and Legal Reform. Bojic, B. (2022). LEGAL CHALLENGES IN CROSS-BORDER TRADE IN GLOBALISATION. Economic and Social Development: Book of Proceedings , 197–208. Carbonnier, G., & Marur, S. (2024). Drivers of abnormal pricing in Switzerland's commodity trade. Cramaro, A. (2024). Economic Security Through Diplomatic Strategies: Insights from International Relations and Political Science. Fakih, M. (2022). Trade-Based Money Laundering (Doctoral dissertation, Lebanese American University). Hamadeh, M., Khoueiri, R., Bitar, N., & Rizk, R. (2025). Political risk, institutional quality, and financial drivers of diaspora remittances. Review of Accounting and Finance , 24 (5), 714–731. Iyandaa, D. E. (2024). A legal framework for combating trade-based money laundering in the African continental free trade area (Doctoral dissertation, University of the Western Cape). Jayasekara, S. D. (2023). Trade-based money laundering and informal remittance services: implications for the sustainability of a small open economy's balance of payments. Journal of Money Laundering Control , 26 (4), 877–891. Kibochi, R. K. (2022). Collective Security Institutions and Stabilization of the Eastern Africa Subregion, 1990–2018 (Doctoral dissertation, Robert Kariuki Kibochi). Makmur, K. L. (2024). Why only scrutinise formal finance? Money laundering and informal remittance regulations in Indonesia. Journal of Economic Criminology , 6 , 100111. Malik, G. M. (2025). Theoretical foundations of money laundering and terror financing: conceptual analysis of legal frameworks and global challenges. Muse, M. A. (2025). The ambiguity, opaqueness, and consequences of FATF’s remittance regulatory strategies: The case studies of Somalia and Nigeria. Journal of Economic Criminology , 8 , 100156. Ohinok, S., & Kopylchak, M. (2024). International Cooperation in Combating Corruption and Money Laundering. Економіка розвитку систем, 6 (2), 156–162. Olivie, I., & O'SHEA, M. S. (2022). The role of remittances in promoting sustainable development. Prasad, R. (2023). Cyber borderlines: exploring the interplay between E-commerce and international trade law. Studies in Law and Justice , 2 (4), 1–9. Rodima-Taylor, D. (2022). Sending money home in conflict settings: Revisiting migrant remittances. Georgetown Journal of International Affairs , 23 (1), 43–51. Sivaguru, D., & Tilakasiri, K. (2023). The phenomenon of trade-based money laundering (TBML)–a critical review in the Sri Lankan context. Journal of Money Laundering Control , 26 (6), 1088–1099. Taha, S., & Abdallah, R. A. Q. (2025). Leveraging artificial intelligence in social media analysis: enhancing public communication through data science. Journalism and Media , 6 (3), 102. Webb, N. J. (2025). Money Laundering and the Globalisation of Informal Value Transfer Systems (IVTS) (Doctoral dissertation, Sheffield Hallam University). Webb, N. J. (2025). Money Laundering and the Globalisation of Informal Value Transfer Systems (IVTS) (Doctoral dissertation, Sheffield Hallam University). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8768531","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":589147982,"identity":"a2315a6e-2f44-4265-ab87-ad4f2020c17b","order_by":0,"name":"Berihu Teweldebirhan Gebresilassie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACAyA+zMBgwcDA3gDiWhCtRYKBgecAiCtBnBZmsBaJBBCfCC3m7L0PDxe2Scgb3Hx+dcOPAgkG/vbuBLxaLHuOGxye2SZhuOF2TtnNHqDDJM6c3YDfYTfSGA7ztkkwArWk3eABajGQyCWg5f4zsBb7DTfPpN38Q5SWG2xgLYkbbrAfu02ULZY9QIfxnJNInnkmh+22jIEED0G/mLMfY/7MU2Zj23f8+LObb/7YyPG39+LXAgcKB3hAccTAQ5xyEJBvYH9AvOpRMApGwSgYUQAAcLNJU83J1cAAAAAASUVORK5CYII=","orcid":"","institution":"Mekelle University","correspondingAuthor":true,"prefix":"","firstName":"Berihu","middleName":"Teweldebirhan","lastName":"Gebresilassie","suffix":""}],"badges":[],"createdAt":"2026-02-02 19:53:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8768531/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8768531/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108349825,"identity":"9866b962-f78f-45c2-acf3-d8a605363edb","added_by":"auto","created_at":"2026-05-03 09:55:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":353364,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8768531/v1/5881bf5c-f004-4d2c-82f3-cc1751b58997.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Uncovering Trade-Related Money Laundering and Financial Networks in the Horn of Africa","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCross-border financial activities are essential to the global economy and encompass both legitimate trade and illicit transactions (Prasad, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Shadow networks, such as IVTS (e.g., hawala), pose risks but also facilitate remittances (ASSESSMENT, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Practices such as TBML exploit regulatory gaps, enabling illicit flows that threaten stability and trust (Webb, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Organizations, including the UN and the FATF, emphasize the importance of international cooperation in combating smuggling and financial crimes (Ohinok \u0026amp; Kopylchak, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Although diaspora remittances support households, their informal transfers often avoid regulation, increasing the risk of organized crime (Rodima-Taylor, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Horn of Africa is highly vulnerable to trade-based money laundering (TBML) because of its key maritime corridors, land borders, and widespread diaspora networks (Iyandaa, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). TBML operates as a regional system that integrates illicit financial activities with legitimate trade in commodities such as gold, fuel, and livestock (Sivaguru \u0026amp; Tilakasiri, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Issues such as weak customs enforcement, inadequate AML infrastructure, and reliance on informal remittance channels exacerbate these laundering pathways (Jayasekara, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis article examines practices, financial inclusion, and security, emphasizing a cross-border approach to TBML, as policies in one country impact laundering elsewhere. It addresses three questions: standard TBML methods; how capacity and conflicts shape networks; and strategies to reduce risks while protecting remittances. Using trade analysis, social network mapping, and interviews, it aims to inform policies for regional cooperation and customs reforms. The article reviews theories, country comparisons, network analyses, policy options, and proposes a roadmap to enhance remittance security and capacity, urging policymakers to balance economic and security priorities.\u003c/p\u003e\n\u003ch3\u003eTHEORETICAL AND EMPIRICAL LITERATURE REVIEW\u003c/h3\u003e\n\u003cp\u003eCross-border financial activities impact the global economy through both legitimate trade and illegal transactions (Bojic, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Informal value transfer systems (IVTS), such as hawala, support essential remittances but pose risks, including trade-based money laundering (TBML), regulatory gaps, and large illicit financial flows (IFFs), which can threaten economic stability (Webb, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The UN and the FATF highlight the importance of international cooperation to combat economic crimes, acknowledging that diaspora remittances are crucial to household well-being yet are often unregulated, raising concerns about potential criminal activity (Muse, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe literature describes trade-based money laundering (TBML) in the Horn of Africa as a complex and adaptable system that involves trade misinvoicing, commodity smuggling, and informal value transfer systems (IVTS) (Fakih, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It underscores the importance of mixed detection strategies, regional cooperation, and engagement with remittance channels (Olivie \u0026amp; O'SHEA, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Insights from political economy, network theory, and informal finance illuminate TBML's resilience by highlighting legal gaps, social legitimacy, and flexible networks (Malik, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Empirical studies identify trade misinvoicing and commodities such as gold and fuel as primary TBML techniques, with country-specific research highlighting unique vulnerabilities and operational dynamics (Carbonnier \u0026amp; Marur, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Africa, remittances and IVTS both demonstrate community resilience and reveal system vulnerabilities (Webb, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The African Union estimates that IFFs siphon more than USD 50\u0026nbsp;billion annually and supports regional efforts through initiatives such as the AU Convention on Preventing Corruption (Ayalew, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). Sub-regional groups, such as the East African Community, aim to standardize regulations to protect legitimate funds and to close gaps in the criminal justice system (Kibochi, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Recent studies combine trade gap analysis, social network mapping, and fieldwork despite limited data (Taha \u0026amp; Abdallah, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Evidence indicates laundering techniques adapt with enforcement, often involving intermediaries and larger cash transfers (Makmur, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These findings underscore the need for further research, especially on transaction-level IVTS data and long-term analyses (Hamadeh et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). They also emphasize the interconnectedness of these issues and call for balanced policies that address both economic and security concerns (Cramaro, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e "},{"header":"METHODOLOGY","content":"\u003cp\u003eThis methodology employs a mixed-methods comparative approach to identify trade-based money laundering (TBML) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. It combines mirror trade analysis, customs audits, social network mapping, and fieldwork, with a focus on reproducible indicators and the safeguarding of informants. Covering 2010 to 2024, it compares similar systems and examines trade misinvoicing, commodity laundering, and their connections to informal value transfer systems (IVTS). The research produces a CSV matrix of illicit flow estimates, including country, year, estimate, confidence, quality, methods, and notes from UN COMTRADE, IMF, and the World Bank. Data collection involves macro trade data, customs audits, interviews, and open-source investigations. Analytical techniques include quantitative detection, social network analysis, process tracing, and qualitative comparative analysis (QCA). The study maintains reliability and reproducibility through detailed codebooks and dual independent coding. Ethical practices encompass informed consent and bias reduction via triangulation. Results comprise case reports, vulnerability indices, and policy briefs, which are validated through back testing and audits.\u003c/p\u003e"},{"header":"RESULTS AND DISCUSSIONS","content":"\u003cp\u003eThis framework analyzes trade data, customs audit records, and insights from Ethiopia, Somalia, Eritrea, Djibouti, and Sudan from 2010 to 2024, highlighting trade anomalies and institutional issues. It covers: 1. Macro Trade Data (2010–2024): Identifies misinvoicing and irregularities, like Ethiopia undervaluing coffee and livestock, Somalia's phantom trade, Eritrea's opaque mineral exports, Djibouti’s invoicing issues, and Sudan’s underreporting of fuel and machinery to evade sanctions. Indicators include price gaps, trade spikes, and trade-to-GDP discrepancies. 2. Customs Audits: Focus on cargo and financial checks. Ethiopia’s ASYCUDA detects undervaluation; Somalia relies on external audits; Eritrea’s customs are rarely audited; Djibouti’s digital, risk-based port audits are improved; Sudan reforms target gold and fuel. Findings include undervaluation, phantom shipments, and misclassification. 3. Qualitative Insights: Cover institutional and social networks like Ethiopia’s trader groups and diaspora remittances; Somalia’s clan-based hawala networks; Eritrea’s family remittances; Djibouti’s shipping firms; and Sudan’s gold traders and smuggling routes, highlighting reliance on informal systems and hotspots for TBML. 4. Cross-Cutting Insights: Ethiopia and Sudan show mispricing; Somalia’s flows are opaque. Djibouti has stronger audits; Somalia’s are weakest. Networks underpin TBML in Somalia, Eritrea, and Sudan. 5. Protective Measures: Suggest linking customs data with UN Comtrade, increasing audits, applying social network analysis, and regional joint audits. Overall, Sudan and Somalia face high risks; Djibouti and Ethiopia have better capacity but are vulnerable. Eritrea’s opacity raises mineral trade risks.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative Matrix for TBML Detection in the Horn of Africa\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eKey Vulnerabilities\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eDetection Mechanisms\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eInstitutional Capacity\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eRegional Cooperation\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eEthiopia\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e- Large informal trade networks\u003c/p\u003e \u003cp\u003e- Weak customs valuation controls\u003c/p\u003e \u003cp\u003e- High cash-based economy\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e- Customs modernization (ASYCUDA system)\u003c/p\u003e \u003cp\u003e- FIU under the National Bank of Ethiopia\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e- FIU operational, but with limited resources\u003c/p\u003e \u003cp\u003e- AML laws are aligned with FATF, but there is weak enforcement\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e- Member of ESAAMLG\u003c/p\u003e \u003cp\u003e- IGAD cooperation on AML/CFT\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSomalia\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e- Predominantly informal economy\u003c/p\u003e \u003cp\u003e- Hawala networks dominate\u003c/p\u003e \u003cp\u003e- Weak border control\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e- Limited customs oversight\u003c/p\u003e \u003cp\u003e- Reliance on informal reporting\u003c/p\u003e \u003cp\u003e- UN-supported AML frameworks\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e- FIU exists but is fragile\u003c/p\u003e \u003cp\u003e- AML law (2016) is weakly enforced\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e- IGAD member\u003c/p\u003e \u003cp\u003e- Regional AML training initiatives\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eEritrea\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e- Isolated financial system\u003c/p\u003e \u003cp\u003e- Heavy reliance on cash\u003c/p\u003e \u003cp\u003e- Weak trade transparency\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e- Customs oversight is limited\u003c/p\u003e \u003cp\u003e- FIU under the Ministry of Finance\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e- AML/CFT framework recently evaluated (2025 MER)\u003c/p\u003e \u003cp\u003e- Weak compliance culture\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e- ESAAMLG member\u003c/p\u003e \u003cp\u003e- Limited regional integration\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eDjibouti\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e- Strategic port hub vulnerable to over/under-invoicing\u003c/p\u003e \u003cp\u003e- High volume of transshipment\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e- Customs risk profiling\u003c/p\u003e \u003cp\u003e- FIU under the Central Bank\u003c/p\u003e \u003cp\u003e- Port monitoring systems\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e- FIU is relatively stronger\u003c/p\u003e \u003cp\u003e- AML law aligned with FATF\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e- ESAAMLG member\u003c/p\u003e \u003cp\u003e- Regional AML/CFT projects\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSudan\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e- Sanctions legacy → informal trade\u003c/p\u003e \u003cp\u003e- Gold smuggling\u003c/p\u003e \u003cp\u003e- Weak customs valuation\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e- FIU under the Central Bank\u003c/p\u003e \u003cp\u003e- Customs reforms are ongoing\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e- AML law exists, but enforcement is weak\u003c/p\u003e \u003cp\u003e- FIU capacity limited\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e- ESAAMLG member\u003c/p\u003e \u003cp\u003e- IGAD AML/CFT cooperation\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eSource: Completion Author,2026\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e outlines key indicators of Trade-Based Money Laundering (TBML), including over- and under-invoicing, phantom shipments, misclassification of goods, circular trade routes, and informal systems such as hawala. It also presents a comparative matrix that analyzes TBML vulnerabilities and detection strategies in the Horn of Africa. Common weaknesses in these countries include informal trade networks, inadequate customs procedures, and a high degree of dependence on cash economies. Detection methods, including customs modernization and Financial Intelligence Units (FIUs), differ by country, with Ethiopia and Djibouti demonstrating greater capacity. While all countries participate in regional initiatives such as ESAAMLG and IGAD, their institutional capacity and enforcement of Anti-Money Laundering (AML) laws remain limited, particularly in Somalia and Sudan, where frameworks are poorly implemented.\u003c/p\u003e \u003cp\u003eThe methodology combines trade analysis, audits, network mapping, and fieldwork for effective TBML prevention. The region faces challenges such as weak customs infrastructure, informal economies, limited resources for FIUs, and political instability. Areas for improvement include regional data sharing, capacity building for customs and FIU staff, the use of technology, and the fostering of public-private partnerships. Ethiopia and Djibouti have stronger arrangements, whereas Somalia and Eritrea are more vulnerable due to their informal economies. Sudan faces specific risks related to gold smuggling and sanctions, underscoring the need for regional cooperation to enhance the detection of TBML.\u003c/p\u003e \u003cp\u003eThis framework presents strategies to identify and prevent trade-based money laundering (TBML) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. It encompasses trade analysis, customs audits, social network mapping, and field investigations. Core activities include identifying anomalies in trade values and routes, validating invoices and shipments through customs checks, mapping TBML networks, and confirming trade flows through field research. Additional safeguards include regional data sharing and engaging local communities.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative Matrix for the TBML Detection and Protection Framework\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eEthiopia\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eSomalia\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eEritrea\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eDjibouti\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eSudan\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eTrade Analysis\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eUse ASYCUDA customs data to compare declared vs. global market prices; monitor coffee \u0026amp; livestock exports.\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eFocus on hawala-linked trade flows; monitor consumer-goods imports relative to remittance inflows.\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eLimited transparency; track discrepancies in mineral exports\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eHigh-volume port trade; monitor transshipment \u0026amp; re-export patterns\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eGold exports \u0026amp; imports of machinery; compare declared vs. actual flows\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eCustoms Audits\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eRandomized audits of invoices; cross-check with banks\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eWeak customs → rely on NGO/UN-supported audits\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eState-controlled customs; limited external audits\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eStronger port customs; risk-based audits possible\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eCustoms reforms underway; audits needed for gold \u0026amp; fuel\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSocial Network Mapping\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eMap trader networks in Addis Ababa \u0026amp; border towns; identify clusters of repeated undervaluation\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eHawala operators \u0026amp; clan-based trade networks; map remittance corridors\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eMap diaspora-linked trade flows; identify family-based networks\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eShipping companies \u0026amp; freight forwarders; map links to regional hubs\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eMap gold traders \u0026amp; informal networks; identify cross-border smuggling routes\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eFieldwork\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eBorder studies (Kenya, Sudan, Djibouti) to observe informal trade\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eField surveys of hawala operators \u0026amp; traders in Mogadishu\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eOn-the-ground interviews are limited; diaspora fieldwork abroad\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003ePort observation \u0026amp; interviews with freight handlers\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eFieldwork in gold markets \u0026amp; border towns (Darfur, South Sudan)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eReproducible Indicators\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e- Price gaps vs. UN Comtrade\u003c/p\u003e \u003cp\u003e- Repeated undervaluation\u003c/p\u003e \u003cp\u003e- Cash-heavy transactions\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e- Hawala remittance vs. trade mismatch\u003c/p\u003e \u003cp\u003e- Phantom shipments\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e- Mineral export discrepancies\u003c/p\u003e \u003cp\u003e- Cash vs. declared trade\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e- Over/under-invoicing\u003c/p\u003e \u003cp\u003e- Transshipment anomalies\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e- Gold export mismatch\u003c/p\u003e \u003cp\u003e- Sanctions evasion patterns\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eProtective Measures\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eStrengthen FIU \u0026amp; customs IT systems\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eBuild AML capacity via UN/World Bank projects\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eIncrease transparency \u0026amp; external audits\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eEnhance port monitoring \u0026amp; FIU cooperation\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eFocus on gold trade transparency \u0026amp; sanctions compliance\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eSource: Completion Author,2026\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents key insights into the reproducibility of trade analysis, comparing customs value data across five countries. It features a matrix for the TBML (Trade-Based Money Laundering) detection and protection framework involving Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Core strategies include using customs data, monitoring remittance-related trade, and identifying export discrepancies. Customs audits vary from Ethiopia's random procedures to Sudan's need for reforms. Social network mapping involves tracing trader networks and remittance paths. Fieldwork encompasses border studies and interviews to observe informal trade. Preventive efforts focus on strengthening financial intelligence units and enhancing transparency across sectors, with indicators such as price gaps and trade mismatches being key for reproducibility.\u003c/p\u003e \u003cp\u003eIt highlights the significance of conducting randomized audits despite varying capacity levels. Mapping social networks is crucial for identifying trade-based money laundering (TBML), particularly in Somalia and Eritrea, with fieldwork corroborating the observed patterns. Indicators like price differences and phantom shipments are measurable. To address these challenges, it is advisable to share data across regions to standardize customs databases, strengthen training for customs officials, upgrade trade-monitoring technology, and involve communities to build trust.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative Matrix (2010–2024) of Trade Misinvoicing, Commodity Laundering, and Informal Value Transfer Systems (IVTS)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eTrade Mis-invoicing\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eCommodity Laundering\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eIVTS Interactions\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eTrend 2010–2024\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eEthiopia\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003ePersistent undervaluation of coffee \u0026amp; livestock exports; over-invoicing of imports (machinery, fuel)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eLaundering via agricultural commodities (coffee, khat); some gold smuggling\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eHawala networks linked to diaspora remittances; overlap with trade flows\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eGradual customs modernization (ASYCUDA); FIU capacity improved, but enforcement is uneven\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSomalia\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003ePhantom imports/exports common; weak customs → misinvoicing rampant\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eLaundering through livestock exports \u0026amp; consumer goods imports\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eHawala dominates; clan-based IVTS central to trade \u0026amp; remittances\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eAML law (2016) was introduced but weakly enforced; reliance on informal systems persists\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eEritrea\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eLimited transparency; misinvoicing in mineral exports (gold, copper)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eCommodity laundering via the state-controlled mining sector\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eDiaspora remittances via hawala-like channels; family-based IVTS\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eIsolation limited external audits; AML/CFT framework slowly evolving post-2015\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eDjibouti\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eOver/under-invoicing in port transshipment; misdeclared re-exports\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eLaundering via shipping \u0026amp; logistics, the fuel/oil trade is vulnerable\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eIVTS is less dominant; formal banking is stronger, but informal cash is still used\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003ePort modernization strengthened customs; FIU is relatively stronger than its neighbors\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSudan\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eMispricing in gold exports; under-invoicing of imports (fuel, machinery)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eCommodity laundering via gold smuggling; sanctions evasion\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eHawala \u0026amp; informal networks key for cross-border trade (Darfur, South Sudan)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003ePost-sanctions reforms (2017+) improved AML laws, but enforcement remains weak\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eSource: Completion Author,2026\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates data from 2010 to 2024, highlighting trade misinvoicing, commodity laundering, and informal value transfer systems (IVTS) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Ethiopia consistently undervalued coffee and livestock exports, overinvoiced imports, and engaged in gold smuggling. Somalia's weak customs systems led to widespread misinvoicing, while Eritrea lacked transparency and external audits. Djibouti's port upgrades improved customs enforcement, whereas Sudan faced issues with mispricing of gold exports and smuggling.\u003c/p\u003e \u003cp\u003eKey findings reveal trade misinvoicing, commodity laundering, and the use of informal value transfer systems (IVTS) throughout the Horn of Africa. In Ethiopia and Sudan, trade misinvoicing is particularly prevalent in the agricultural and gold sectors, whereas in Somalia, invoice manipulation is widespread. Djibouti functions as a transshipment hub. Commodity laundering is standard in Sudan and Eritrea with gold, in Ethiopia and Somalia with livestock and coffee, and in Djibouti and Sudan with fuel. Somalia's Hawala system dominates trade and remittance flows, with Ethiopia and Sudan also seeing significant diaspora remittances. The region has shifted from reliance on informal systems (2010–2015) to the adoption of AML laws (2016–2020) and digital customs systems (2021–2024), along with improved regional cooperation, although enforcement gaps persist. Recommended measures include modernizing customs, improving commodity transparency, regulating IVTS, and strengthening regional collaboration. Sudan and Somalia are high-risk due to gold smuggling and reliance on hawala, whereas Djibouti and Ethiopia have stronger institutions but still face vulnerabilities.\u003c/p\u003e \u003cp\u003eThis section explores how macro trade detection, customs audits, social network analysis, and qualitative tracing identify trade-based money laundering (TBML) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Findings indicate persistent trade deficits, particularly in high-value commodities, with Sudan and Djibouti exhibiting the most significant discrepancies. The region exhibits trade misinvoicing and operational vulnerabilities. The TBML risk index varies across countries, with Somalia and Eritrea relying on remittances. Social network analysis reveals decentralized facilitator networks and chokepoints in major ports. Enforcement actions can precipitate rapid shifts in networks, and TBML techniques, such as trade misinvoicing and commodity laundering, are examined. Displacement effects are evident: enforcement shifts illicit activities to areas with weaker oversight, thereby affecting households that rely on formal remittances.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCross-Case Comparative Synthesis of Trade-Based Money Laundering (TBML)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eDimension\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eDominant TBML modality\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003ePrimary enablers\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eMost effective disruption point\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eEthiopia\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eFuel and textile misinvoicing; IVTS layering\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eLarge internal market; mixed customs capacity\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eMirror-trade monitoring + IVTS pilots\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSomalia\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eIVTS-enabled layering; port commodity smuggling\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eClan networks; weak port customs\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eCommunity-led IVTS engagement + port audits\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eEritrea\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eOpaque export routes; commodity concealment\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eSanctions environment; state control\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eMultilateral targeted asset measures\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eDjibouti\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eTransit misinvoicing; free-zone absorption\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eStrategic port; free-zone opacity\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003ePort analytics + customs valuation\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSudan\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eGold and livestock commodity laundering\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eExtractive rents; patronage networks\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eAsset recovery + commodity chain audits\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSource: Completion Author,2026\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that trade-based money laundering (TBML) persists in the Horn of Africa through methods like trade misinvoicing and IVTS. Ethiopia primarily misinvoices fuel and textiles, monitors mirror trades, and pilots IVTS. Somalia's TBML involves layering via IVTS and smuggling, using clan networks and weak customs, with community engagement and port audits recommended. Eritrea's TBML encompasses opaque export routes and commodity concealment, often driven by sanctions, and multilateral asset measures have been proposed to address these. Djibouti faces transit misinvoicing at a key port, supported by analytics and valuation assistance. Sudan's TBML involves the laundering of gold and livestock through patronage; asset recovery and commodity audits are recommended.\u003c/p\u003e \u003cp\u003eThe passage highlights the crucial role of social legitimacy in IVTS, emphasizing how institutional weaknesses can be exploited, and stresses the importance of policy measures targeting chokepoints rather than just channels. It advocates asset recovery strategies and phased pilots for IVTS registration, combined with evidence-based enforcement, to reduce political bias. Challenges such as data gaps and detection biases—particularly toward invoice fraud rather than physical concealment—point to the need for ongoing research. The analysis concludes that TBML is a complicated, cross-border issue that demands regional coordination and safeguards to protect legitimate remittance flows.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePOLICY RESPONSE\u003c/h3\u003e\n\u003cp\u003eThe regional policy promotes initiatives to improve financial inclusion and combat trade-based money laundering (TBML). It includes engaging with informal value transfer systems (IVTS), updating customs procedures, and strengthening community resilience. Key focus areas involve protecting remittances, pinpointing intervention points, and ensuring fair asset-disruption practices. The strategy outlines six actions: 1) Simplify IVTS registration and training, 2) Apply trade analytics and audits to detect misinvoicing, 3) Facilitate data sharing among financial intelligence units (FIUs), 4) Target assets through legal channels, 5) Boost community resilience with cash aid and financial literacy, 6) Secure donor funding for pilot projects and assessments. These actions will be implemented in sequence to assess impact, promote local ownership, and minimize displacement risks.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative Implementation Matrix (Related to Remittances)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eMeasure\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eEthiopia\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eSomalia\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eEritrea\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eDjibouti\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eSudan\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eIVTS formalization\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003ePilot urban registration\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eCommunity-led onboarding\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eConfidential onboarding\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eMobile money KYC\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eBorder corridor pilots\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eCustoms analytics\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eFuel/textiles focus\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003ePort audits in Mogadishu\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eExport verification\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eFree-zone container scoring\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eGold/livestock audits\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eFIU cooperation\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eActive participant\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eDonor-supported nodes\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eSelective, multilateral\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003ePort-FIU integration\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eTransitional FIU strengthening\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eAsset disruption\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eTargeted freezes\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eNarrow sanctions on facilitators\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eMultilateral evidence-based freezes\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003ePort facilitator sanctions\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eAsset-recovery task force\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eSource: Completion Author,2026\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e details remittance efforts in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Ethiopia pilots urban registration for IVTS; Somalia uses community onboarding; Eritrea employs confidential onboarding; Djibouti uses mobile-money KYC; and Sudan's border projects. For customs, Ethiopia targets fuel and textiles; Somalia audits Mogadishu ports; Eritrea verifies exports; Djibouti assesses free-zone containers; and Sudan audits gold and livestock. FIU cooperation is active in Ethiopia, donor-supported in Somalia, selective in Eritrea, port-integrated in Djibouti, and transitional in Sudan. Asset disruptions include targeted freezes in Ethiopia, narrow sanctions in Eritrea, evidence-based freezes in Djibouti, sanctions on port facilitators in Sudan, and an asset recovery task force across all countries.\u003c/p\u003e \u003cp\u003eIt also emphasizes risks related to remittances, such as driving them underground, which can be mitigated through tiered thresholds, exemptions, and incentives for formalization; politicized enforcement, which can be addressed by independent review panels and multilateral evidence standards; and capacity gaps, which can be bridged with donor-funded, phased technical assistance and pooled procurement.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLEGAL FRAMEWORK AND THE JUSTICE SYSTEM\u003c/h2\u003e \u003cp\u003eThis section examines the legal structures, institutional functions, and the interactions among justice systems that impact the detection, investigation, and prosecution of trade-based money laundering (TBML) in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. It emphasizes how statutory laws, Financial Intelligence Units (FIUs), customs authorities, prosecutorial powers, mutual legal assistance (MLA), and judicial protections work together. The goal is to identify legal methods to effectively disrupt TBML while ensuring that legitimate remittances and due process are not compromised.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverview of the Legal Framework\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eDimension\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eEthiopia\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eSomalia\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eEritrea\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eDjibouti\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eSudan\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAML/CFT statute\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNational AML/CFT law; asset-forfeiture provisions\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eFragmented/uneven across federal/regional levels\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eLimited public transparency; state control over finance\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eFundamental AML law; gaps in enforcement\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eMixed legacy laws; transitional reforms underway\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eFIU\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eOperational FIU with donor support\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eNascent/weak FIU presence; donor nodes\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eLimited FIU engagement; selective cooperation\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eSmall FIU; constrained resources\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eFIU exists but is politicized; its capacity is uneven\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eCustoms \u0026amp; trade law\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eFormal customs code; valuation gaps\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eWeak port controls; informal customs practices\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eCentralized export controls; opaque documentation\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003ePort/free-zone legal regime; valuation vulnerabilities\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eCustoms weakened by conflict and patronage\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eProsecution \u0026amp; courts\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eFormal prosecutorial units; capacity gaps\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eHybrid justice; weak formal prosecution\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eCentralized, politicized judiciary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eMinor judiciary; limited financial crime experience\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eCourts affected by instability; selective enforcement\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eMLA \u0026amp; cross-border cooperation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eGrowing bilateral MLAs; regional engagement\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eReliant on UN/NGO channels; ad hoc MLAs\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eSelective, confidential cooperation\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eStrategic partner for regional trade; limited MLAs\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eImproving MLAs under transition; fragile mechanisms\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eKey legal risk\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eImplementation and politicization\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eCriminalizing IVTS risks harming remittances\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eSanctions and state embedding hinder transparency\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eFree-zone opacity and transit risks\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eState capture of illicit trade resists reform\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSource: Completion Author,2026\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e summarizes AML/CFT legal frameworks in Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Ethiopia has a comprehensive asset-forfeiture law, whereas Somalia's system is fragmented, and Eritrea lacks transparency. Djibouti has fundamental laws but enforcement issues, and Sudan's system is mixed, undergoing reforms. Ethiopia's FIU is functional but weak; Somalia's is limited; Djibouti's is small; and Sudan's is politicized. Customs laws vary widely—from Ethiopia's formal code to Somalia's weak port controls and Eritrea's centralized export controls. Prosecution systems face challenges: Ethiopia has formal units but capacity gaps; Somalia’s justice system is hybrid; Eritrea's judiciary is centralized and politicized. Cross-border cooperation is improving but still faces regional issues. Legal risks include gaps in law enforcement, politicization, criminalization of IVTS, sanctions, and opacity within free zones. Ethiopia criminalizes money laundering and terrorist financing, with support from the Central Bank and a functional FIU, but implementation remains problematic. Somalia's fragmented system complicates enforcement; Eritrea's lack of transparency hampers reforms, though centralized control offers some potential. Djibouti's robust legal framework and port support for enforcement, but free-zone opacity poses vulnerabilities. Sudan struggles with enforcement due to legacy laws and ongoing reforms. Key needs include operationalizing FIUs, integrating customs systems, and enhancing asset recovery.\u003c/p\u003e \u003cp\u003eIt provides model legal clauses on Trade-Based Money Laundering (TBML) and describes legal frameworks in the Horn of Africa, including Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Key clauses address the registration of informal value transfer systems, asset freezes, and mutual legal assistance, with metrics for assessing enforcement. Ethiopia's system blends civil and common law with AML regulations, while Somalia faces enforcement issues due to state fragility. Colonial legacies continue to influence Eritrea and Djibouti, which require international aid, while Sudan is undergoing reform amid instability. The document emphasizes harmonizing legal definitions, improving reporting, and adopting risk profiling, with regional cooperation showing that combining legal reforms and technology enhances enforcement.\u003c/p\u003e \u003cp\u003eThis result covers legal and judicial responses to Trade-Based Money Laundering (TBML) in the Horn of Africa, focusing on Ethiopia while also examining Somalia, Eritrea, Djibouti, and Sudan. Ethiopia's legal system, as set out in the constitution, supports anti-money laundering efforts by combining civil-law and customary practices, criminalizing money laundering in the financial and trade sectors, and aligning with FATF and UN standards. Somalia's fragile state weakens law enforcement; Eritrea faces enforcement issues due to limited information and a government-controlled banking sector. Djibouti employs civil-law systems for ports and trade zones, with international AML support. Sudan's recent reforms aim to boost financial transparency despite ongoing political instability. The findings highlight the importance of global frameworks, such as the FATF and the WCO, in setting TBML standards, with emphasis on reporting, cross-border cooperation, and risk assessment tools. The report also notes transnational challenges and legal gaps, showcasing successful enforcement collaborations and legislative alignment among regional countries.\u003c/p\u003e \u003cp\u003eEnhancing justice systems in the Horn of Africa to combat Trade-Based Money Laundering (TBML) involves strengthening investigative skills, addressing capacity gaps, and establishing procedural protections. Key tools include Suspicious Transaction Reporting (STR), Mutual Legal Assistance (MLA), and asset forfeiture. Currently, weaknesses exist in forensic expertise, customs enforcement, and judicial independence. Reforms should focus on quick asset freezes with clear timelines, evidentiary standards, and witness protections.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSPECIAL PROGRAMS, ENFORCEMENT, AND INSTITUTIONAL MECHANISMS\u003c/h2\u003e \u003cp\u003eEnhancing justice systems in the Horn of Africa to combat Trade-Based Money Laundering (TBML) involves improving investigative and prosecutorial expertise, addressing capacity gaps, and implementing procedural safeguards. Key instruments such as Suspicious Transaction Reporting (STR), Mutual Legal Assistance (MLA), and asset forfeiture are essential, yet challenges persist in forensic capabilities, customs enforcement, and judicial independence. Reforms should include asset freezes, clear evidentiary standards, and the protection of witnesses. Legal frameworks need to align with international norms, bolster financial intelligence units, utilize technology for monitoring, and engage communities. A phased, regional strategy should focus on formalizing informal value transfer systems, employing targeted customs analytics, and establishing joint task forces. Recommendations emphasize capacity development in the banking and customs sectors, the adaptation of STR procedures, and the strengthening of regional cooperation to combat TBML across Ethiopia, Somalia, Eritrea, Djibouti, and Sudan.\u003c/p\u003e \u003cp\u003eA phased regional approach is proposed to combat trade-based money laundering (TBML) in the Horn of Africa. It involves formalizing informal value transfer systems (IVTS) and strengthening cooperation between financial and customs agencies through programs such as compliance plans, port trade initiatives, joint teams, and a community resilience fund. Structures such as a regional FIU platform and fusion cells for cross-border intelligence are planned over 36 months, with a focus on risk assessments, pilot registration, and investigations, and with metrics for monitoring. Challenges such as capacity gaps, the informal sector, and enforcement issues call for improved regional cooperation, adapted suspicious transaction reporting, and targeted efforts to address informal financial systems to tackle TBML in Ethiopia and neighboring regions.\u003c/p\u003e \u003c/div\u003e "},{"header":"CONCLUSION AND POLICY RECOMMENDATIONS","content":"\u003cp\u003eTrade-Based Money Laundering (TBML) in the Horn of Africa is a widespread and adaptable network that exploits porous borders and informal transfer methods such as hawala. It involves practices such as trade misinvoicing and commodity laundering across countries, including Ethiopia, Somalia, Eritrea, Djibouti, and Sudan, with regional networks adapting in response to enforcement efforts. The study highlights that punitive measures alone are insufficient; a coordinated, evidence-based approach is necessary to disrupt illicit financing while protecting legitimate economic activities. Key insights include the interconnected tactics of TBML, the concentration of facilitators, the network's resilience despite enforcement actions, societal acceptance of informal systems, and institutional disparities that enable arbitrage. Effective strategies should incorporate customs analytics, collaboration among financial intelligence units, targeted legal measures, and community resilience programs.\u003c/p\u003e\u003cp\u003ePolicy guidance on combating trade-based money laundering (TBML) in the Horn of Africa emphasizes the importance of regional cooperation, improved customs procedures, and strengthening community resilience. Key measures include creating a Horn FIU and Customs Coordination Platform for data exchange, applying mirror trade analysis to identify misinvoicing, and deploying proportional IVTS with minimal registration. This entails analytics, customs inspections, formalizing IVTS, boosting data sharing, and conducting pilot tests. It is vital to align laws with international standards, bolster financial intelligence units, utilize technology, and engage communities. A cohesive regional strategy is crucial for dismantling TBML networks and maintaining economic stability across Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. The strategy involves TBML risk assessments, joint task forces, and the expansion of pilot programs over 36 months, with success indicators including remittance shares, trade discrepancies, and community trust. Risks are addressed through regular reviews and exemptions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003cstrong\u003eEthical Approval and Consent to Participate\u003c/strong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNot applicable.\u003c/em\u003e\u003c/p\u003e\n\u003ch2\u003eEthical approval\u003c/h2\u003e\n\u003cp\u003e\u003cem\u003ewas secured, and all research activities received protocol approval from the MU College of Health Sciences, Institutional Review Board MU-IRB2624/2025.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003cstrong\u003eConsent for Publication\u003c/strong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNot applicable.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo conflicts of interest have been reported.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNo sources have funded either the research or this article.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eBerihu Teweldebirhan Gebresilassie, as the corresponding author, drafted the main manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eASSESSMENT, A. 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Leveraging artificial intelligence in social media analysis: enhancing public communication through data science. \u003cem\u003eJournalism and Media\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(3), 102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWebb, N. J. (2025). \u003cem\u003eMoney Laundering and the Globalisation of Informal Value Transfer Systems (IVTS)\u003c/em\u003e (Doctoral dissertation, Sheffield Hallam University).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWebb, N. J. (2025). \u003cem\u003eMoney Laundering and the Globalisation of Informal Value Transfer Systems (IVTS)\u003c/em\u003e (Doctoral dissertation, Sheffield Hallam University).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cross-border smuggling, Diaspora remittances, Illicit financial flows, Informal value transfer systems (IVTS) / hawala, Trade-based money laundering","lastPublishedDoi":"10.21203/rs.3.rs-8768531/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8768531/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTrade-based money laundering (TBML) in the Horn of Africa occurs across open borders and informal networks, affecting Ethiopia, Somalia, Eritrea, Djibouti, and Sudan. Using macroeconomic data, trade records, social network analysis, and interviews, the article illustrates how practices such as trade misinvoicing, commodity smuggling\u0026mdash;particularly gold, fuel, and livestock\u0026mdash;and informal value transfer systems enable money laundering. Key methods include employing third-party intermediaries, exploiting free zones and diaspora routes, and leveraging country-specific vulnerabilities, such as Ethiopia's market risks, Somalia's clan-based IVTS, Eritrea's covert pathways, Djibouti's role as a transit hub, and Sudan's patronage linked to extractive industries. TBML remains a widespread challenge worldwide; enforcement in one nation often shifts illicit activities elsewhere. Money launderers adapt to evolving global AML/CFT regulations. To combat TBML effectively, strategies should include regional cooperation, enhanced trade transparency, reform of customs procedures, and the development of community-based IVTS that extend beyond enforcement.\u003c/p\u003e","manuscriptTitle":"Uncovering Trade-Related Money Laundering and Financial Networks in the Horn of Africa","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-13 14:24:20","doi":"10.21203/rs.3.rs-8768531/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2f9e144a-3d86-4bc4-8868-9e7bc6d2d215","owner":[],"postedDate":"February 13th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-03T09:37:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T08:15:35+00:00","index":78,"fulltext":""},{"type":"reviewerAgreed","content":"39838651782347002526208156385966200277","date":"2026-05-01T11:38:07+00:00","index":76,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-03T09:54:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-13 14:24:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8768531","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8768531","identity":"rs-8768531","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}