DETECTING TRADE FRAUD RISK AND ASSESSING REVENUE LOSS – THE CASE OF KENYA

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dc.contributor.authorJohn Rand
dc.contributor.authorNathan Carter Remcho
dc.contributor.authorFinn Tarp
dc.contributor.authorThomas Westergaard-Kabelmann
dc.contributor.authorClement Otindo
dc.date.accessioned2026-07-06T10:48:51Z
dc.date.available2026-07-06T10:48:51Z
dc.date.issued2026
dc.description.abstractThis paper examines cross-country distributional patterns in CIF-FOB trade unit value ratios to identify risks of import undervaluation and overvaluation. Building on these patterns, we develop a Trade Fraud Risk Index (TFRI) that ranks countries by their exposure to trade fraud and allows tracking of risk over time and across sectors. Using trade unit values and trade volumes, and incorporating WTO tariff rates, we assess both the magnitude of CIF-FOB value gaps and the associated potential customs revenue losses at the HS 4-digit level. To complement the quantitative analysis, we incorporate qualitative fieldwork conducted at the Port of Mombasa in 2024, including interviews with clearing agents, CFS personnel, truck drivers, and port workers. These field insights illuminate the mechanisms through which misreporting, undervaluation, misclassification, and bribery occur in practice. The qualitative evidence helps explain how fraud persists despite improvements in Kenya’s overall TFRI performance and provides context for sector-specific value gaps identified in the data. Applied to Kenya, the TFRI shows a marked improvement in trade fraud risk between 2005 and 2019, accompanied by a decline in estimated tariff revenue losses. The fieldwork findings, however, highlight persistent vulnerabilities within customs verification and inspection processes. Together, the TFRI and qualitative assessment offer actionable tools for customs administrations seeking to identify, understand, and mitigate trade fraud both internationally and domestically.
dc.identifier.urihttps://publication.aercafricalibrary.org/handle/123456789/4122
dc.publisherAERC
dc.titleDETECTING TRADE FRAUD RISK AND ASSESSING REVENUE LOSS – THE CASE OF KENYA
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