When Firms Go Smart: Causal Evidence on AI Adoption and Corporate Credit Risk

The global credit outlook is worsening for various industries as international trade tensions intensify. As AI becomes more embedded in business processes, it is crucial to understand its impact on a company’s creditworthiness to ensure financial stability. This research empirically investigates how enterprise-level AI adoption affects credit risk, using data from Chinese A-share-listed firms from 2012 to 2024. Fixed-effects regression analysis indicates that adopting AI significantly reduces the firm’s credit risk. Further examination of underlying mechanisms identifies three primary channels through which AI reduces credit risk: asset volatility, internal control quality, and financial leverage. Heterogeneity tests indicate that the credit risk reduction effect is stronger in firms within highly digitalized, high-tech industries, and with lower financing constraints. The AI adoption is significantly correlated with reduced credit risk exposure, providing valuable insights for existing research on organizational digitalization and risk mitigation strategies. Furthermore, these findings hold key implications for stakeholders, suggesting that corporate managers can align AI adoption with risk management, especially internal control, and governments can provide more support for the AI adoption of innovative, digitally strong firms.

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Publication Details

Journal
International Journal of Financial Engineering
Published
2026-06-12
DOI
https://doi.org/10.1142/s2424786326500337
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
Field-Weighted Citation Impact
0.00
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article

When Firms Go Smart: Causal Evidence on AI Adoption and Corporate Credit Risk

Weiming Ou
International Journal of Financial Engineering
Financial Distress and Bankruptcy Prediction
article

When Firms Go Smart: Causal Evidence on AI Adoption and Corporate Credit Risk

Weiming Ou
article en

Abstract

The global credit outlook is worsening for various industries as international trade tensions intensify. As AI becomes more embedded in business processes, it is crucial to understand its impact on a company’s creditworthiness to ensure financial stability. This research empirically investigates how enterprise-level AI adoption affects credit risk, using data from Chinese A-share-listed firms from 2012 to 2024. Fixed-effects regression analysis indicates that adopting AI significantly reduces the firm’s credit risk. Further examination of underlying mechanisms identifies three primary channels through which AI reduces credit risk: asset volatility, internal control quality, and financial leverage. Heterogeneity tests indicate that the credit risk reduction effect is stronger in firms within highly digitalized, high-tech industries, and with lower financing constraints. The AI adoption is significantly correlated with reduced credit risk exposure, providing valuable insights for existing research on organizational digitalization and risk mitigation strategies. Furthermore, these findings hold key implications for stakeholders, suggesting that corporate managers can align AI adoption with risk management, especially internal control, and governments can provide more support for the AI adoption of innovative, digitally strong firms.

International Journal of Financial Engineering
Hebei University of Technology (CN), Hebei Science and Technology Department (CN)
Partnerships for the goals
Openalex Percentile: Top 3%
Financial Distress and Bankruptcy Prediction
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