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Evidence record 1552 · automatically gathered

Neutralizing Structural Inequality in the Nigerian FinTech Sector

arXiv:2607.10317v1 Announce Type: cross Abstract: 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

Record details

Published: 14 July 2026
Source: arXiv cs.CY
Category: Research
Topics: Bias & fairness · Finance, VC & PE
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Bias & fairness · Shared topic: Finance, VC & PE

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How to cite this record

ethics.ai (14 July 2026), “Neutralizing Structural Inequality in the Nigerian FinTech Sector,” evidence record 1552, https://ethics.ai/record/1552 (originally published by arXiv cs.CY).

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