Hierarchical Human-AI Triage Model Reduces Structural Bias in Nigerian FinTech Fraud Detection

Jul 14, 2026

A new preprint introduces a hierarchical human-AI triage model for point-of-sale fraud detection in Nigeria, targeting discrimination laundering where infrastructure-related noise is misclassified as fraud. The model uses a three-tier routing policy and dynamic human oversight, reducing the regional performance gap from 19.43 to 2.88 percentage points and significantly improving fraud recall. This approach aims to neutralize structural bias, particularly benefiting rural accounts.

Why it matters: This research offers a practical method to mitigate algorithmic bias in financial services, supporting more equitable digital financial inclusion in developing economies.

Full story at: arXiv Computation and Language ↗