A Comparative Analysis of Artificial Neural Networks & Support Vector Machines in Predicting Money Laundering in Zimbabwean Commercial Banks: A Case Study of Banc ABC (Zimbabwe

Author(s)	Mr. Tendayi Nzombe
Country	Zimbabwe
Abstract	Money Laundering and terrorist financing pose significant threats to the stability and integrity of financial institutions worldwide. Traditional rule based anti money laundering systems are increasingly becoming inadequate to detect complex and evolving financial crimes. This paper presents a comparative study on the application of artificial neural networks and support vector machines in detecting money laundering using transaction data from BancABC, a leading Zimbabwean commercial bank
Keywords	Money Laundering, Artificial Neural Network, Support Vector Machines, Anti-Money Laundering, Machine Learning, Financial Crime Detection
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-04-16
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.50254

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