The Prospects and Dangers of Algorithmic Credit Scoring in Vietnam: Regulating a Legal Blindspot

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. This 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.

This study addresses these concerns from a legal and policy angle. After describing the promises and perils of algorithmic credit scoring in Vietnam, it suggests novel ways to regulate it. It aims to provide oversight over algorithmic credit scoring, ensuring that the process from data collection to credit decision is transparent, accessible, accurate, and fair. The study's central argument is that adequate regulation is vital to delivering big data and machine learning's promises in the financial services market while ensuring fairness and public interest. The proposal calls for amending credit and data privacy legislation and develop ethical guidelines for responsible AI.

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By Nicolas Lainez