AI deployment in financial services has reached a turning point, with only 2% of institutions globally reporting no AI use. According to research by Finastra, Singapore financial institutions are at the forefront of this transition, with nearly two-thirds already deploying AI in production environments.

AI Adoption in Singapore

The "Financial Services State of the Nation 2026" report indicates that 73% of Singapore institutions have deployed or improved AI use cases in their payments technology over the past 12 months, nearly double the global average of 38%. Chris Walters, CEO of Finastra, emphasized how Singapore is demonstrating what AI execution at scale really looks like, embedding AI into core operations.

Objectives and Infrastructure

Globally, 31% of institutions have scaled AI deployment across multiple functions, while 30% have achieved limited production deployment. In Singapore and the US, 43% of institutions are using AI to improve compliance and regulatory processes. Singapore's success is supported by high cloud adoption, with 55% of institutions hosting all or most of their infrastructure in the cloud.

Challenges and Security

The acceleration of AI deployment brings new security threats. The research projects a 40% average increase in security spending globally in 2026. Singapore leads in deploying advanced fraud detection and transaction monitoring systems. Talent shortages represent a major barrier to AI deployment, with Singapore recording the highest figure (54%).

For those evaluating on-premise deployments, there are trade-offs to consider. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these aspects.