Digital microfinance and algorithmic bias: Implications for financial inclusion in Morocco

Résumé

This research explores the effect of digital microfinance and algorithmic biases on financial inclusion in Morocco. The objective of this study is to develop an integrated model taking into account perception of utility (according to the Technology Acceptance Model – TAM), digital skills, algorithmic fairness mechanisms, and biases induced by algorithms, to assess and predict equitable access to digital financial services.

The methodology adopted is quantitative and hypothetico-deductive, based on a convenience sample of 250 digital microfinance users, including both individual borrowers and informal sector micro-entrepreneurs. The data were collected using a structured questionnaire and analyzed via PLS-SEM (SmartPLS 4), allowing to assess simultaneously the reliability of measures, structural relationships, as well as mediation and moderation effects.

The result concludes that digitalization of finance increases perceptions of utility and trust and indirectly improves financial inclusion. However, algorithmic bias limits these positive impacts while digital literacy and equitable mechanisms will mitigate these effects. Sequential mediation supports the conclusion that perceptions of utility and trust are the most important channels to obtain these results, which have significant implications for policymakers and managers of financial institutions, by demonstrating the importance of creating inclusive digital infrastructure, providing digital literacy education, and developing algorithmic equity mechanisms to increase access to credit and reduce financial inequality within Morocco.