Site Reliability Engineer at Moniepoint, building payment infrastructure that moves money for millions of Nigerians. Building RiskSense, an AI-driven credit risk scoring platform for African fintech.
I’m an SRE on the Card Payment team at Moniepoint, one of Africa’s leading fintech unicorns. My work sits at the intersection of reliability engineering and product impact — from card BIN management and terminal configurations to the playbooks that keep payment rails alive under pressure.
Before Moniepoint, I worked at Indicina Technologies in credit analytics and technical operations & engineering, where my obsession with credit risk scoring began. That thread runs through my independent research in AI and directly into RiskSense.
Completed independent research in Advanced Artificial Intelligence, with published work comparing Mamdani and Sugeno fuzzy inference systems applied to credit scoring in emerging markets.
Own the reliability and operational integrity of Moniepoint’s card payment infrastructure. Responsible for card BIN management, transaction processing systems, terminal PTSP configuration migrations, Kubernetes orchestration, and the Ansible automation layer that underpins safe deployments at scale. Directly contributes to payment success rates across millions of daily transactions.
Worked on credit risk analytics, technical operations, and automation development for one of Nigeria’s leading credit infrastructure companies. Built automations to improve operational efficiency and gained deep familiarity with the Nigerian lending landscape, alternative data scoring, and the infrastructure challenges of consumer credit at scale—forming the foundation of the RiskSense thesis.
AI-driven credit risk scoring engine for African fintech. Combines fuzzy inference systems with alternative data to score creditworthiness where traditional bureau data is sparse. Targeting 60M+ financially underserved Nigerians.
View on GitHub →
Open-sourced Ansible playbooks for card BIN management, terminal configurations, and payment infrastructure rollbacks. Battle-tested patterns from production fintech environments.
GitHub →Comparative study of Mamdani vs Sugeno fuzzy inference systems applied to credit risk scoring. Published on SSRN with ORCID: 0009-0006-0870-6798. Includes MATLAB simulation models.
Read paper →Open to conversations about fintech infrastructure, AI in credit risk, and opportunities in the tech ecosystem.