A Hybrid Stacked Ensemble Framework for Fraud Detection in Nigerian Financial Ecosystems: Evaluation with Localized Synthetic Data
This study contributes a localized Nigerian fraud dataset, a hybrid stacked ensemble architecture that exploits classifier diversity for improved fraud detection, and an explainable AI framework that enhances transparency, accountability, and regulatory compliance.