Context-Aware Pre-Deployment Evaluation of AI Systems: A Regulatory Framework for Nigerian Fintech

The deployment of commercial large language models (LLMs) within African fintech infrastructure, particularly in Nigeria for tasks like fraud detection and customer communication, is expanding rapidly. However, current regulatory instruments at Nigerian and continental African levels lack specific requirements for pre-deployment evaluation of these AI systems. While safety is acknowledged as a core principle in existing governance frameworks, operational guidance for evaluating AI prior to its implementation remains undefined. Generic safety benchmarks are inadequate for identifying failure modes specific to this domain, as they do not account for Nigerian institutional contexts or test for critical issues like false positive misclassifications of legitimate financial communications.

The rapid adoption of AI, particularly LLMs, in critical sectors like fintech necessitates robust and context-specific governance. The current regulatory gap concerning pre-deployment evaluation in Nigerian and African fintech poses significant operational risks and could undermine public trust, impacting financial stability and innovation.

Commercial LLMs are increasingly being integrated into African fintech, including Nigerian operations, for critical functions such as fraud detection and customer communication.

Forward consideration, not a verified fact.