AI deployment in financial services has crossed a critical threshold, with only 2% of institutions globally reporting no AI use whatsoever—a dramatic indicator that the technology has moved decisively from boardroom discussion to operational reality.
New research from Finastra surveying 1,509 senior leaders across 11 markets reveals that Singapore financial institutions are leading this transition, with nearly two-thirds already deploying AI in production environments rather than confining it to experimental pilots.
The Financial Services State of the Nation 2026 report shows 73% of Singapore institutions have deployed or improved AI use cases in their payments technology over the past 12 months—nearly double the 38% global average.
“Singapore institutions are showing what AI execution at scale really looks like. This is not about isolated pilots. It is about embedding AI into core operations, supported by modern infrastructure, strong data foundations, and disciplined governance,” said Chris Walters, CEO of Finastra.
From experimentation to enterprise AI deployment
Globally, 31% of institutions report scaled deployment across multiple functions, while 30% have achieved limited production deployment. A further 27% are piloting or testing in limited functions, with only 8% still in the exploration phase.
This represents a fundamental shift in how AI deployment is approached within financial services. The technology is no longer confined to innovation labs or proof-of-concept projects but has become integral to core banking operations.
In Singapore specifically, an additional 35% are piloting or researching AI applications beyond their current production deployments, indicating a robust innovation pipeline that positions the city-state as a regional AI leader.
The primary objectives driving this deployment vary by market. In Singapore and the US, 43% of institutions are using AI to improve compliance and regulatory processes—reflecting the technology’s ability to navigate increasingly complex oversight requirements while maintaining operational resilience.
Globally, the top AI implementation objectives are improving accuracy and reducing errors (40%), increasing employee productivity (37%), and enhancing risk management capabilities (34%). Vietnam prioritises speed, with 49% using AI to accelerate processing in payments and lending services, while Mexico emphasises customer experience and personalisation at 43%.
Cloud infrastructure enables AI at scale
Singapore’s AI deployment success is underpinned by advanced cloud adoption. The research shows 55% of Singapore institutions host all or most infrastructure in the cloud, with a further 30% operating hybrid environments—an 85% total that significantly exceeds many global peers.
This cloud-first approach provides the scalable, resilient infrastructure required for enterprise AI deployment. Without modern data architectures and elastic compute capabilities, AI remains confined to small-scale…
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