The prospects and dangers of algorithmic credit scoring in Vietnam: regulating a legal blindspot

Nicolas Lainez
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Nicolas Lainez: CESSMA UMRD 245 - Centre d'études en sciences sociales sur les mondes africains, américains et asiatiques - IRD - Institut de Recherche pour le Développement - Inalco - Institut National des Langues et Civilisations Orientales - UPCité - Université Paris Cité

Working Papers from HAL

Abstract: Artificial intelligence (AI) and big data are transforming the credit market in Vietnam. Lenders increasingly use 'algorithmic credit scoring' to assess borrowers' creditworthiness or likelihood and willingness to repay loan. This technology gleans non-traditional data from smartphones and analyses them through machine learning algorithms. Algorithmic credit scoring promises greater efficiency, accuracy, cost-effectiveness, and speed in predicting risk compared to traditional credit scoring systems that are based on economic data and human discretion. These technological gains are expected to foster financial inclusion, enter untapped credit markets, and deliver credit to 'at-risk' and financially excluded borrowers. However, this technology also raises public concerns about opacity, unfair discrimination, and threats to individual privacy and autonomy. In Vietnam, the lending industry deploys this technology at scale but in legal limbo. Regulation is vital to delivering big data and AI promises in the financial services market while ensuring fairness and public interest.

Keywords: VIET; NAM (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-04720798

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