Can artificial intelligence mitigate greenwashed green credit? Evidence from loan contracts of Chinese listed firms

  • Mengmeng Zheng
  • , Lu Zhang*
  • , David Tripe
  • , Yuming Zhang
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Green credit is intended to support firms with truly environmental potential, but the widespread greenwashing by firms undermines its effectiveness and hinders progress toward sustainable development goals. This study investigates whether the adoption of artificial intelligence (AI) by banks can address this issue. Using a dataset of 1209 loan contracts issued in China between 2019 and 2023, which is one of the largest polluters and green finance implementors, we find that banks adopting AI impose significantly higher interest spreads on firms exhibiting signs of greenwashing. The effect is more prominent for loan contracts granted by green-experienced banks and those to non-polluting firms. Our analysis identifies two underlying mechanisms: AI enhances banks' capabilities for both risk identification and legitimacy. These findings offer novel insights into the role of technological advancement in green credit practices and contribute to the growing literature at the intersection of finance, sustainability, and digital transformation.

Original languageEnglish
Article number104948
JournalInternational Review of Financial Analysis
Volume110
DOIs
StatePublished - Feb 2026

Keywords

  • Artificial intelligence
  • Green credit
  • Greenwashing
  • Manipulation, loan contract

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