The devil in the church: can tax authorities be able to untangle sophisticated money laundering schemes in developing countries?
Edmore Munjeyi & Danie Schutte
Abstract
Purpose This study aims to explore how Botswana’s tax authorities address sophisticated money laundering through churches, examining their detection and intervention strategies. Design/methodology/approach This paper opted for a qualitative research framework, specifically utilising purposive interviews with a sample of eight officials of the Botswana Unified Revenue Service (BURS). The methodological choice was strategically made to elicit in-depth insights into the tax authorities’ methodologies and the complexities encountered in addressing money laundering. Findings Research demonstrates that money launderers often exploit Pentecostal churches to conceal illicit funds, leveraging their perceived legitimacy and lax financial oversight. It also finds that current anti-money laundering (AML) strategies are insufficient, emphasising the critical need for integrating digital transformation tools to enhance detection and intervention. Practical implications The study highlights the need for advanced digital tools and stricter oversight in AML frameworks to better detect and prevent financial crimes involving religious organisations. Originality/value This paper offers pioneering insights into money laundering within religious organisations, with a focus on Pentecostal churches in Botswana. It critically analyses the BURS strategies, establishes a historical record and lays the foundation for future research in corporate governance and AML practices. By addressing a significant gap in the discourse, it advocates for enhanced AML measures and a deeper understanding of the role of religious institutions in financial crime.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.