Artificial Intelligence and Risk-Taking in Banking

Tudor-Andrei Drăgan, Wenjing Jiang, Simona Nistor and Steven Ongena
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Tudor-Andrei Drăgan: Babeş-Bolyai University of Cluj-Napoca
Wenjing Jiang: Babeş-Bolyai University of Cluj-Napoca
Simona Nistor: Babes-Bolyai University - Department of Finance

No 26-25, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We study how banks’ adoption of artificial intelligence (AI) affects risk-taking and stability using data on major listed Chinese banks (2013–2024). We construct an AI-intensity index from agent adoption, cloud computing, and big data measures. Higher AI intensity is associated with greater risk and lower stability: a one–standard deviation increase reduces the Z‑score by 0.25 units (about 22%) next year. This operates mainly via higher earnings volatility and lower profitability, not weaker capitalization. The effect is stronger for banks with low liquidity, unstable funding, and weak loss-absorption, implying AI can amplify risk and requires tighter prudential oversight.

JEL-codes: G01 G21 G28 O32 (search for similar items in EconPapers)
Pages: 67 pages
Date: 2026-03
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2625

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