An Original Theoretical Model of Credit Market Segmentation and Financial Exclusion in Sub-Saharan Africa with Nigerian Evidence

Credit market segmentation, whereby formal credit is rationed away from low-income and informal sector borrowers despite willingness to pay, is a persistent structural feature of Nigerian financial markets that existing theoretical models incompletely explain. This study develops an original theoretical model of credit market segmentation that integrates information asymmetry theory, collateral channel theory, and social capital theory into a multi-segment credit market equilibrium framework with endogenous exclusion mechanisms. The model formally characterises the conditions under which formal credit markets in concentrated banking systems equilibrate at exclusionary interest rate-collateral schedules, producing a permanent informal sector excluded from formal finance. Original contributions include the derivation of a financial exclusion equilibrium condition based on a bank's optimisation problem under incomplete information and heterogeneous collateral quality, and the specification of conditions under which fintech credit scoring can shift this equilibrium toward inclusion. The theoretical framework is empirically tested using household-level data from the National Financial Inclusion Survey 2022, supplemented by a primary survey of 600 informal sector operators across Kano, Ibadan, and Onitsha. Structural equation modelling was employed. The empirical results confirm that social capital and fintech credit score access each independently shift formal credit market participation probabilities, consistent with the theoretical model's predictions. An original taxonomy of credit exclusion mechanisms is proposed, distinguishing demand-side, supply-side, and information failure exclusion. The study provides a theoretical foundation for targeted financial inclusion policy design in Nigeria and comparable sub-Saharan African economies.

Keywords: credit market segmentation, financial exclusion, information asymmetry, social capital, fintech credit scoring