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The nexus between artificial intelligence and financial resilience: a time-varying correlation

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  • Qin, Zhilong
  • Ren, Wei
  • Peng, Qingqing

Abstract

Amid the accelerating digital transformation of global industries and the increasing frequency of cross-domain uncertainty shocks, this paper investigates the time-varying nexus between artificial intelligence (AI) and financial resilience across the energy, economic, and industrial domains. AI is operationalized by the S&P’s Kensho New Economy RAIC Index, while financial resilience is measured via three key indicators: the Global Energy-Related Uncertainty Index (ERU), Global Economic Condition Index (GECON), and Worldwide Industrial Production Index (WIP). Using monthly data spanning January 2014 to November 2023, the time-varying Granger causality test is adopted to capture dynamic causal linkages that may evolve over time. The results reveal that AI has statistically significant positive or negative time-varying effects on all three indicators, with more pronounced impacts after 2020 amid heightened global volatility. Energy-related resilience does not significantly influence the other two indicators; GECON affects ERU and WIP but has a transient effect on AI; and industrial production resilience does not affect AI but does affect ERU and GECON. These findings offer valuable insights for policy-makers formulating targeted financial stability strategies and market participants optimizing risk management practices.

Suggested Citation

  • Qin, Zhilong & Ren, Wei & Peng, Qingqing, 2026. "The nexus between artificial intelligence and financial resilience: a time-varying correlation," Finance Research Letters, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:finlet:v:90:y:2026:i:c:s1544612325025863
    DOI: 10.1016/j.frl.2025.109337
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