Filling the Credit Gap: The Inclusive Potential, Risk Challenges and Governance Framework of Big Data Finance

Finance，Wenzhou-Kean University, 325060 88 Daxue Road, Li’ao Street, Ouhai District, Wenzhou, Zhejiang Province, China

^* Corresponding author: Yuhaoy@kean.edu

Abstract

The data-driven credit scoring model is not an all-singing, all-dancing panacea. First of all, it does not eliminate the traditional bank’s huge amount of documents; a large number of micro entrepreneurs and village farmers fall into the abyss due to this ‘credit gap’. At the same time, Internet finance represented by Alipay faces difficulties in obtaining loans and starting businesses for independent people who cannot be mortgaged or used as proof of income — but still require them from traditional bank ideas about credits — while converting ordinary people’s daily behavioral tracks into real credit signals through big data, process substitution, and artificial intelligence technology. It changes what? It also turns the user’s ‘invisible property’ into true credit values so that their value can return within some limits after being abandoned by most banks. I use these discoveries to examine how Internet finance solves the problem of the missing middle-income strata between China’s ultra-poor and super-rich. Finally, I argue that technology-aided risk evaluation has altered our perspective on credit with increasing emphasis placed on behavioral values instead of security/pledge values.