SME Financial Health & Informal Economy Dataset

This is a synthetic dataset generated from high-quality expert-labelled seed data. All records are algorithmically derived — statistical distributions, inter-field correlations, and annotation characteristics faithfully replicate real-world patterns from the source data, while ensuring no real individual, organisation, or transaction can be identified or reconstructed.

The African SME Financial Health & Informal Economy Dataset captures the operational and financial reality of small and micro enterprises across Nigeria, Ghana, Rwanda, and South Africa — markets where 80–90 % of businesses operate outside formal financial infrastructure. Each record encodes monthly revenue, cost of goods, supplier credit utilisation, digital-payment share, and an annotated informal-economy score derived from field surveys and aggregated mobile-money transaction signatures.

Unlike corporate financial datasets, this collection reflects the seasonality, cash-flow irregularity, and asset-light nature of African informal commerce. Records span market traders, artisans, smallholder agri-processors, transport operators, and service micro-businesses. Each entry carries a manually validated credit-risk label and a data-completeness flag, enabling robust train / eval splits even when fields are partially observed.

The dataset is purpose-built for teams developing inclusive credit underwriting engines, embedded-finance products for neobanks and MNOs, and market-sizing models for B2SME SaaS platforms. Structural anonymisation removes all direct identifiers while preserving the statistical distributions needed for bias-aware model evaluation.