Configurational pathways from AI-enabled FinTech adoption to business financial inclusion in SMEs: the role of digital financial capability in northern Peru

Engineering notes

Key topics: autonomous driving. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Artificial intelligence-enabled financial technology is reshaping the ways in which small and medium-sized enterprises access, use, and evaluate formal financial services. The theoretical problem addressed in this study is that firms with comparable levels of AI-enabled FinTech adoption may achieve substantially different levels of business financial inclusion. This inconsistency suggests that adoption creates a technological opportunity structure, but does not by itself ensure effective access, use, quality, or value creation. Digital financial capability is therefore positioned as the capability-conversion mechanism through which SMEs transform AI-enabled financial tools into meaningful financial participation. This study identifies the configurational pathways through which AI-enabled FinTech adoption and digital financial capability are associated with high business financial inclusion among small and medium-sized enterprises in northern Peru. A quantitative, non-experimental, cross-sectional design was applied to 120 complete responses from owners, managers, and administrators with direct knowledge of their firms’ financial and digital operations. The analysis used fuzzy-set qualitative comparative analysis, incorporating six causal conditions: AI-enabled FinTech adoption, digital financial capability, perceived usefulness, AI familiarity and integration, digital financial skills, and digital financial self-efficacy. The findings show that no single condition is strictly necessary for high business financial inclusion. Nevertheless, digital financial capability emerged as the condition closest to necessity. The intermediate solution identified two equifinal configurations leading to high inclusion, both combining AI-enabled FinTech adoption, digital financial capability, perceived usefulness, and digital financial skills, while AI familiarity and digital financial self-efficacy operated as alternative reinforcing mechanisms. The results also confirmed causal asymmetry, as low inclusion was explained by configurations centred on deficits in capability and AI-FinTech adoption rather than by the simple inverse of high-inclusion pathways. The study extends FinTech and financial inclusion theory by demonstrating that business financial inclusion is not a direct result of AI-enabled FinTech adoption, but an outcome of capability conversion operating through multiple configurational pathways.

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