S&P: Banks' use of AI will impact credit ratings in the coming years.

Artificial intelligence is evolving from a strategic option into a key variable in credit ratings. S&P Global Ratings released a report on Monday stating that in the coming years, the extent to which banks apply AI will increasingly directly impact their credit ratings, with the pace of adoption and the maturity of governance determining the strength or weakness of financial institutions in terms of credit quality.

S&P points out that the uneven progress of AI applications, the maturity of governance frameworks, and operational readiness will "increasingly drive improvements or deteriorations in the credit quality of financial institutions." In other words, banks lagging behind in the AI race may face additional pressure from rating agencies.

According to a June survey by S&P of 179 financial institutions worldwide, respondents expect AI to reduce costs by up to 4% this year, and this figure is expected to rise to 6% to 8% by 2028. The prospect of cost savings is gradually being incorporated into the assessment framework of institutional competitiveness.

Applications remain concentrated in the backend, and product innovation is constrained by regulations.

Despite the anticipated continued expansion of AI applications, most financial institutions are currently limiting their AI deployments to support functions and automation. Surveys show that approximately 84% of respondents reported using AI in these areas, but less than a third are using AI to develop new products and services, primarily due to regulatory restrictions and reputational risks.

This structural difference means that AI's current value contribution to most banks is mainly in cost reduction, with its incremental revenue benefits yet to be fully realized. How to leap from an efficiency tool to a business innovation engine remains a core challenge for the industry.

Credit outcomes depend on the ability to translate efficiency into sustainable advantages.

S&P emphasizes that the credit impact of AI applications does not depend on the adoption of the technology itself, but on whether institutions can translate cost savings and additional revenue into sustainable improvements in profitability and create a structural advantage in industry competition.

Miriam Fernandez, head of AI research and applications at S&P, said:

"Net credit outcomes will largely depend on an institution's ability to translate cost efficiencies and additional revenue into sustainable profit improvements, creating a competitive advantage over its peers, while maintaining robust risk management."

This statement places sound risk management on an equal footing with efficiency improvement, implying that while pursuing the benefits of AI, a lack of a governance framework may actually become a drag on credit ratings.

Risk Warning and DisclaimerInvesting involves risk; please exercise caution. This article does not constitute personal investment advice and does not take into account the specific investment objectives, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article are suitable for their specific circumstances. Any investment decisions made based on this information are at your own risk.