Neutralizing Structural Inequality in the Nigerian FinTech Sector
Algorithmic decision systems in financial services often rely on data proxies that inadvertently encode structural inequalities. This paper introduces a hierarchical human-AI triage model for Point of Sale fraud detection in the Nigerian FinTech sector. Adopting a We Are All Equal worldview, we address the challenge of discrimination laundering, wherein the system misinterprets infrastructure related aleatoric noise such as rural network timeouts as fraudulent intent. We implement a three-tier routing policy utilizing a calibrated ensemble model as a primary filter. The policy routes transactions characterized by epistemic uncertainty such as cold start new accounts to specialist analysts...
| Authors | Muhammad Abdullahi Said |
|---|---|
| Primary category | cs.CL |
| Published | 11 July 2026 |
| Last updated at source | 11 July 2026 |
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