AI adoption in financial services has reached a critical inflection point, with a mere 2% of global institutions reporting no AI initiatives. This statistic underscores a significant shift from theoretical discussions to tangible, operational integration of artificial intelligence.
New research from Finastra, based on a survey of 1,509 senior leaders across 11 markets, indicates that financial institutions in Singapore are spearheading this transformation. Nearly two-thirds of these Singaporean entities have already implemented AI in production environments, moving beyond experimental phases. The report, “The Financial Services State of the Nation 2026,” highlights that 73% of Singaporean financial institutions have either deployed or enhanced AI applications within their payments technology over the past 12 months. This figure nearly doubles the global average of 38%.
“Singapore’s financial institutions are demonstrating what large-scale AI execution truly entails. This isn’t about isolated pilot projects; it’s about integrating AI into core operations, supported by robust modern infrastructure, a strong data foundation, and disciplined governance,” stated Chris Walters, CEO of Finastra.
Globally, 31% of institutions report widespread AI deployment across multiple functions, while 30% have achieved limited production deployment. An additional 27% are currently piloting or testing AI in specific functions, with only 8% remaining in the exploration phase. This signifies a fundamental change in the approach to AI implementation within the financial sector, with the technology now being an integral part of core banking operations rather than being confined to innovation labs or proof-of-concept projects.
In Singapore, a further 35% of institutions are actively piloting or researching AI applications beyond their current production deployments, indicating a strong pipeline for future innovation and positioning the city-state as a regional leader in AI adoption.
The primary drivers for AI deployment vary across markets. In Singapore and the U.S., 43% of institutions are leveraging AI to improve compliance and regulatory processes, reflecting the technology’s capacity to navigate increasingly intricate oversight requirements while maintaining operational resilience. Globally, the leading objectives for AI implementation include improving accuracy and reducing errors (40%), increasing employee productivity (37%), and enhancing risk management capabilities (34%). Vietnam is prioritizing speed, with 49% utilizing AI to accelerate processing in payments and lending services, while Mexico focuses on customer experience and personalization, cited by 43% of its institutions.
The success of AI deployment in Singapore is significantly bolstered by its advanced adoption of cloud infrastructure. The research reveals that 55% of Singaporean institutions host all or most of their infrastructure in the cloud, with an additional 30% operating hybrid environments, resulting in an 85% cloud-native or hybrid approach that substantially surpasses many global peers. This cloud-first strategy provides the scalable and resilient infrastructure essential for enterprise-level AI deployment. Without modern data architectures and elastic compute capabilities, AI implementations tend to remain confined to small-scale experiments that cannot deliver enterprise-wide value. The correlation between infrastructure modernization and AI deployment is evident in the data, with nearly nine in ten institutions (87%) globally planning to increase their modernization investments over the next 12 months. Singapore is at the forefront of this trend, with planned spending increases exceeding 50%. Furthermore, institutions in Singapore express strong confidence in their technological foundations, with 71% rating their core infrastructure, security, and reliability as superior to their peers, the highest globally and well above the average of 72%.
As AI deployment accelerates, so too do AI-enabled security threats. The research forecasts an average increase of 40% in global security spending for 2026, with institutions responding to what 43% describe as continuously evolving risks. Singapore is leading in the deployment of advanced fraud detection and transaction monitoring systems, with 62% having implemented or upgraded these systems in the past year, compared to a global average of 48%. This highlights Singapore’s recognition that AI-powered fraud necessitates AI-powered defenses.
Similarly, 60% of Singaporean institutions have modernized their Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) capabilities—again, the highest globally. This enables real-time threat monitoring and automated response at scale. The deployment of multi-factor authentication and biometrics has reached 54% in Singapore, as institutions strengthen identity verification against increasingly sophisticated attack vectors that leverage generative AI and deepfake technologies. Looking ahead, API security and gateway hardening are emerging as key priorities, cited by 34% globally as a focus area for the next 12 months. This reflects a growing understanding that as financial ecosystems expand and AI systems interact across organizational boundaries, securing access points becomes paramount.
Despite significant progress in AI adoption, several barriers to deployment persist. Talent shortages are the most prominent global challenge, cited by 43% of institutions. In Singapore, this figure rises to 54%, the highest among all surveyed markets, tied only with the UAE. This intense competition for specialized AI, cloud, and security expertise underscores the gap between institutional ambition and available human capital. The demand for professionals capable of architecting AI systems, ensuring model governance, and integrating AI into existing workflows far outstrips the supply.
Budget constraints also present a significant hurdle, with 52% of Singaporean institutions citing them, again the highest globally. Even well-funded organizations face difficult prioritization decisions as they balance AI deployment, security investments, modernization efforts, and customer experience initiatives. In response to these challenges, 54% of institutions globally are partnering with fintech providers as their preferred method for accessing AI capabilities, thereby mitigating the full burden of talent acquisition and system development. These strategic partnerships enable organizations to accelerate AI deployment while maintaining control over critical data and compliance requirements.
The research indicates a sector that has definitively crossed the AI adoption threshold but now faces the more complex challenge of scaling responsibly. As Chris Walters noted, future success will be defined not by the breadth of AI experiments but by the ability to embed intelligence into operations while strengthening, rather than compromising, trust.
The study surveyed managers and executives from financial institutions across France, Germany, Hong Kong, Japan, Mexico, Saudi Arabia, Singapore, the UAE, the UK, the US, and Vietnam, representing organizations that collectively manage over $100 trillion in assets.
Original article, Author: Samuel Thompson. If you wish to reprint this article, please indicate the source:https://aicnbc.com/17389.html
