The financial services sector is at a pivotal crossroads. The industry is facing mounting pressures to modernize following rapid data growth, stringent regulatory requirements, and accelerating artificial intelligence (AI) adoption.

According to Gartner, by 2026, more than 80 percent of banks will have adopted generative AI. With 66 percent of enterprises across the wider financial services sector already building AI capabilities into their products and services, according to our Global Data Insights Survey.

This push towards AI and other advanced technologies demands globally connected, scalable infrastructure that can handle increasing complexity. Addressing these challenges is essential for financial institutions striving to stay competitive in a fast-evolving digital economy.

This blog explores the role of colocation in enabling financial institutions to overcome these growing challenges, future-proof their infrastructure, and achieve data and AI success.

AI’s impact on the financial services sector

As AI continues to evolve, its impact on financial services is becoming both broader and deeper – moving beyond high-level innovation into the operational core of the enterprise.

Today’s financial institutions face a dual mandate: to accelerate AI adoption in pursuit of competitive advantage, and to do so within the constraints of an increasingly complex digital and regulatory environment.

From risk modelling and fraud prevention to real-time analytics and customer personalization, AI is being embedded into mission-critical functions. Realising its full potential, however, isn't solely a matter of algorithms – it hinges on having a data-first strategy, with the right infrastructure and governance in place.

Financial institutions often use high-density data workflows. These include high-performance computing (HPC) systems for algorithmic trading, high-frequency trading (HFT), risk management, and pricing derivatives. These workflows require low-latency, high availability, and scalability, especially the closer they are to trade execution. Some of the key challenges include:

• Managing compliance with data residency, transfer, and protection regulations – including general data protection regulation (GDPR), anti-money laundering (AML), fraud detection, and binding corporate rules (BCRs).
• Maintaining high-density power and cooling to support demanding workloads.
• Ensuring multi-layered redundancy to guarantee operational resilience.
• Accessing a rich connectivity ecosystem to facilitate data exchange and collaboration.
• Balancing costs with the need for flexible infrastructure that can adapt to changing business needs.

While AI offers transformative potential for financial services, fully realising its benefits requires more than just technological readiness. Institutions must navigate these complex regulatory landscapes, ensuring data sovereignty, and upholding fairness and transparency in AI-driven decision-making.

By combining robust, scalable infrastructure – enabled through solutions like colocation – with a proactive, responsible approach to AI governance, financial services firms can harness AI in ways that are not only innovative but also compliant, resilient, and aligned with long-term business objectives.

Unlocking pinnacle performance with colocation

Colocation facilities enable financial services firms to achieve proximity to market data feeds and exchange connectivity, cloud on-ramps, and network service providers. Thereby reducing latency and optimizing executional trading speeds, operational efficiencies, and workflow connections. The benefits of colocation extend to:

• Enhanced performance: Financial institutions can deploy their infrastructure in proximity to key data sources and markets, reducing latency and improving overall performance.
• Operational resilience: Access to robust infrastructure and redundancy frameworks ensures high availability and minimizes the risk of downtime.
• Access to ecosystem: Enables connection to dense ecosystems of network and cloud service providers, facilitating data exchange and collaboration.
• Security and compliance: Colocation provides secure and compliant environments, often designed to meet – or beat – the highest security, efficiency, and performance standards.
• Supporting high-density workloads: Colocation facilities are equipped to handle the power and cooling demands of AI and high-performance computing.

To successfully colocate, financial services companies should first identify their business locations, users, and applications. Our recent survey found that 79 percent of financial services companies are tying a data location strategy to their AI roadmaps. AI strategy success is shifting towards distributed inference, requiring low-latency for real-time decision making.

This foundational step is crucial in understanding the infrastructure needs that'll drive data and AI initiatives. By starting a dialogue about these needs, financial institutions can create a differentiated experience in the new AI and data-driven era.

Leveraging colocation for distributed data strategy

Digital Realty's high-density colocation and ServiceFabric solutions are designed for enterprises seeking to deploy low-latency, power-intensive applications such as AI, machine learning (ML), and data analytics. Our global data center platform, PlatformDigital, offers standardized, HPC-ready infrastructure configurations to support high-density workloads.

With exponential data growth presenting challenges, customers gain access to a secure, compliant, resilient, and performant foundation. This foundation enables the implementation of new technologies and seamless orchestration of data flows. Our goal is to simplify data management complexity and serve as the single, trusted, global data center partner for our customers.

As organizations optimize their AI strategies, many are exploring cloud repatriation – the process of moving certain workloads from the cloud back to on-premises or colocation environments. This strategic move can be crucial for AI success, as it allows for better control over sensitive data, reduced latency, and improved performance for demanding AI workloads.

By providing a turn-key infrastructure solution built for HPC, Digital Realty enables financial institutions to scale beyond limits and achieve a distributed data strategy. This is achieved by using high-throughput processing – moving large amounts of data in and out of HPC environments efficiently.

Additionally, our energy-efficient infrastructure reduces overall costs by lowering power usage effectiveness (PUE) and minimizing total cost of ownership. The solution also supports low-latency applications, such as AI training and real-time processing. Our fast deployment capabilities enable customers to quickly deploy robust HPC environments, ensuring they stay ahead of the curve and meet critical timelines.

Future-proofing your IT infrastructure

Financial services continue to respond to technological advancements and changing market dynamics. To stay competitive, financial institutions must future-proof their IT infrastructure to support emerging technologies such as AI, blockchain, and even quantum computing.

Colocation plays a critical role in this effort, providing the flexibility and scalability needed to adapt to changing business needs.

Partnering with a colocation provider like Digital Realty, enterprises can ensure they have the infrastructure necessary to deploy faster and reduce risk – turning your physical infrastructure into a competitive edge.

Trusted by the world’s most ambitious companies, Digital Realty’s global footprint spans 300+ data centers in 50+ metros, 5,000+ customers, and more than a decade of 99.999 percent uptime.

Learn more about Digital Realty’s colocation solutions today and future-proof your digital deployment for tomorrow.