In the world of global financial services, fragmented infrastructure can be an innovation killer. Financial institutions are now facing the critical question of how to modernize and consolidate their foundations for an AI-driven future.

In today’s landscape, artificial intelligence and real-time processing are no longer mere advantages but table stakes. Financial services organizations worldwide are confronting an unpleasant truth: a fragmented technology footprint not only limits growth but also puts their very ability to compete at risk.

Michael Yeo

In an IDC report titled “Shaping Resilient Financial Services for the Digital Future,” Associate Research Director Michael Yeo identified three key foundations: hyperscalable connectivity, new data dimensions, and AI-ready infrastructure. “These foundations are essential for enabling the next wave of transformation, positioning financial institutions to achieve greater resilience and drive innovation in an ever-evolving landscape.”

Scalable Real-Time Connectivity

The Asia-Pacific region enjoys a vibrant fintech ecosystem that has witnessed region-wide initiatives such as Project Nexus’s cross-border payment system. Collaborative platforms like APIX and Proxtera are spurring payment innovation and there is an exponential surge in digital payment methods, including cryptocurrencies and central bank digital currencies (CBDCs).

According to Yeo, the ability to rapidly and dynamically implement scalable connectivity at real-time speeds has become the standard for both internal and external operations in the financial services sector. Research shows that 36% of respondents from the financial services sector recognize the significance of sharing data insights for co-innovation, with this figure rising to 44% for security and fraud reduction.

This level of data sharing requires infrastructure optimized for edge computing and real-time data processing to generate actionable insights.

When deploying business or technology capabilities, organizations need to choose network solutions that fit their specific needs, whether to increase speed-to-market, enhance control and visibility, or ensure business continuity. For BFSI, the requisite of being able to customize and integrate solutions within existing environments and comply with specific regulatory and licensing requirements would be vital for the business.

Trust in Data

The region is primed for Open Finance and it demands real-time transactions at scale. This functionality requires trust to be embedded in the technology infrastructure that stores sensitive data and feeds AI training systems. This built-in trust requirement is mandated by regulators, for example the Hong Kong Monetary Authority (HKMA), which has extended its 2019 guiding principles for AI usage to encompass Generative AI applications.

Regarding data privacy and protection, the country’s Privacy Commissioner (PCPD) has recommended practices that now focus on organizational compliance in the procurement and implementation of third-party AI systems that process personal data.

Beyond implementing a zero-trust approach to address third-party risk, organizations must protect against numerous data privacy and integrity threats. A significant concern is data poisoning, where AI query results become unreliable due to training datasets being compromised by malicious attackers.

Data poisoning poses a serious threat to AI systems’ integrity and reliability as their adoption grows in financial services. Regulators like HKMA recommend continuous monitoring of AI models to track performance and detect anomalies. Stringent data governance, including access control measures and regular log audits, helps protect dataset integrity and prevent unauthorized access.

AI-Ready Digital Infrastructure

When one of Europe’s largest financial institutions established its presence in the Asia-Pacific region, it faced a critical challenge. Despite serving millions of corporate and small business customers, the bank reached an inflection point: its ageing technology backbone, once a reliable foundation, had become an obstacle to scaling growth and participating in innovation.

An international telco conducted a comprehensive infrastructure study for this European bank client, employing a vendor-neutral approach to evaluate data center partners. The selection criteria focused on advanced technological capabilities, proven experience with sensitive data handling, and robust security measures that meet regulatory standards.

The rigorous process that financial services organizations follow when migrating, consolidating, or modernizing their infrastructure’s capabilities reveals an important truth: successful implementation of emerging technologies like AI depends heavily on current decisions about foundational infrastructure and services.

For example, a recent IDC report has revealed that Asia-Pacific organizations are deploying significantly more GenAI workloads at edge locations (23%) to leverage storage and processing power closer to consumers, reducing both latency and data transfer costs.

Also, businesses that deployed cloud initially, find themselves repatriating workloads to private or on-premises environments. However, a happy balance can be kept with a hybrid cloud approach that offers the best of both private and public cloud environments. Today, solutions provide visibility into workload performance and resource usage, enabling financial institutions to adopt multi-cloud confidently while gaining benefits of economies-of-scale and maintaining data sovereignty.

Conclusion

Industry observers say a golden opportunity is looming in the horizon for this region. The number of organizations deploying GenAI workloads at edge locations in this region is higher than in the U.S or EMEA, highlighting that APAC is actively embracing next-generation infrastructure solutions. This adoption signals a broader shift in how financial institutions approach their digital infrastructures.

For financial institutions establishing or expanding their presence in APAC, the message is clear: tomorrow’s success requires today’s infrastructure revolution. Those who invest strategically in flexible, scalable, and AI-ready infrastructure while building robust trust frameworks will be in position to capitalize on the region’s growth opportunities. The future of financial services belongs to those who start to build it today.