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Eco-friendly algorithms: Artificial intelligence and green finance in European intelligent nations

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  • Wang, Canghong
  • Nazar, Raima
  • Ali, Sajid
  • Meo, Muhammad Saeed

Abstract

Artificial intelligence enhances green finance by improving environmental risk assessment, optimizing sustainable investment portfolios, and facilitating innovative financial instruments. This research assesses the asymmetric impact of artificial intelligence on green finance in ten leading European economies supporting artificial intelligence (the UK, Denmark, the Netherlands, Finland, Switzerland, Sweden, Germany, Ireland, France, and Italy). Unlike previous studies primarily using symmetric panel models, this investigation applies a novel Quantile-on-Quantile approach to reveal nuanced, asymmetric, and country-specific relationships. The findings demonstrate that artificial intelligence significantly influences green finance across different quantiles, with varying effects among countries—most showing a strong positive relationship, while Italy reflects a mixed pattern. The study's innovation lies in its dual-quantile methodological design, which captures heterogeneous effects missed by conventional tools. The results offer vital implications for policymakers, suggesting that tailored artificial intelligence adoption strategies can amplify sustainable green finance and support environmental targets. Encouraging artificial intelligence integration in financial systems could be a strategic lever for promoting green finance and achieving long-term sustainability goals.

Suggested Citation

  • Wang, Canghong & Nazar, Raima & Ali, Sajid & Meo, Muhammad Saeed, 2025. "Eco-friendly algorithms: Artificial intelligence and green finance in European intelligent nations," Technology in Society, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:teinso:v:83:y:2025:i:c:s0160791x25001502
    DOI: 10.1016/j.techsoc.2025.102960
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