<![CDATA[FinTech lending utilizes alternative credit scoring (ACS) based on digital footprints to expand financial inclusion for Micro, Small, and Medium Enterprises (MSMEs). However, this approach risks excluding marginalized MSMEs that lack extensive digital data. This study explores the paradoxical digital divide in MSME credit assessment and examines the potential of Accounting Information Systems (AIS) to bridge this gap. Employing a descriptive-exploratory qualitative approach, multiple case studies were conducted involving 15 MSME actors with varying digitalization levels in Parepare City, Indonesia. The findings reveal a "signal recognition gap": although most MSMEs possess adequate digital footprints and disciplined financial records, they still receive disproportionately low FinTech financing limits. Current FinTech algorithms appear to assess basic identity and loan history rather than actual business performance or structured accounting signals. Consequently, FinTech lending currently provides only "nominal inclusion" without substantive financial impact. Integrating AIS-generated financial reports into ACS algorithms is critical to provide accurate credit signals, mitigate information asymmetry, and achieve genuine financial inclusion for MSMEs]]>
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