The influence of AI-enabled tool adoption, digital footprints, and SME credibility on loan approvals: a quantitative study of South African SMEs

Abstract

Information asymmetry remains a critical barrier to Small and Medium Enterprises (SMEs) financing in South Africa, with traditional credit assessment mechanisms failing to recognise the creditworthiness of viable enterprises. Digital transformation and AI-enabled technologies present potential new signalling mechanisms that could bridge this gap. This quantitative study examined whether AI-enabled tool adoption, digital footprints, and SME credibility influence loan approval outcomes for South African SMEs that applied for loans within a 12-month period. Data were collected through structured surveys and analysed using Bayesian logistic regression to test four hypotheses grounded in signalling theory and information asymmetry theory. Results revealed that AI adoption demonstrated strong model-level evidence and moderate interaction effects with credibility, both receiving partial support/association. However, digital footprints and credibility independently showed insufficient evidence to reliably predict loan approval. Credibility functions as a complementary signal that gains relevance when combined with AI adoption or hard financial metrics. Traditional financial indicators such as firm size, operational maturity, and cash flow capacity remain primarily associated with lending decisions. The study concludes that while digital signals are acknowledged by lenders, they function as transitional indicators requiring institutional maturation before becoming decisive factors in South Africa's conservative banking environment.