An alternative credit bureau for Nigeria's informal economy

Trace is an alternative credit bureau serving the ~60% of Nigeria's workforce that operates in the informal economy — traders, gig workers, and small-business owners who transact in cash and remain invisible to traditional credit systems like FICO or CRC.

I led the machine learning workstream. The platform issues each user a Squad-powered virtual bank account; the resulting real-time transaction stream becomes the data foundation for a calibrated credit score (300–850, FICO-comparable), delivered via a shared "Score-as-a-Service" API to microfinance lenders. The same identity model supports gig workers, whose completed jobs feed back into both credit scoring and job-matching in a single unified signal.

The system integrates five Squad API surfaces (Virtual Accounts, Webhooks, Transfer, Direct Debit, Payment Gateway) and runs five ML systems across the platform: credit scoring, fraud detection, cash-flow forecasting, fairness auditing, and a multilingual job-matching engine supporting Yoruba, Igbo, Hausa, and Nigerian Pidgin.