As technology moves forward, and artificial intelligence (AI) initiatives begin to be further woven into the fabric of financial services enterprises.

From automating workflows to streamline tasks, improving risk management, detecting fraud, and making customer experiences more seamless, AI is influencing nearly every part of the business world. But to make the most of all these advancements, companies need to adopt data-first strategies and invest in the right infrastructure.

Why AI needs a strong foundation in financial services

A common misconception is that AI and the business applications we see today are new, but it’s been around in financial services for over a decade. The difference is that these systems come with strict regulations and transparency rules, which don’t apply to every new AI product on the market. In the financial world, even proprietary technology needs to be clear and open to meet regulatory standards. Adopting AI in financial services isn’t just about installing new software. AI models require infrastructure that supports high-performance computing, vast data sets, and airtight security to work properly. Whether AI is being used to catch fraud, make smarter trading decisions, or deliver personalised banking, it demands serious processing power and a resilient infrastructure to keep up with real-time data analysis – all while remaining compliant. With Digital Realty's AI-ready data centres, financial firms gain the speed, flexibility, and security they need to manage the complex workloads that come with AI - something traditional on-premises solutions often can’t handle.

Overcoming AI challenges in financial services

There can be a lot of fear surrounding AI, and there isn't any less of that anxiety around its involvement in our finances. However, whilst there are some consequences of the tech, in general, it's improving many processes and operational efficiencies in the sector. As AI innovation in the sector increases, and new processes are implemented, some new challenges are emerging. These aren’t just technical problems - we’re talking about everything from legal and ethical concerns to issues with infrastructure that could slow things down. Let’s break down some of the key challenges:

Latency issues: Financial services have relied on AI for real-time tasks like fraud detection and algorithmic trading for years. But as these processes get more complicated, low-latency environments are becoming even more critical to keeping things running smoothly. Data localisation matters more than ever, and financial institutions are acting on this — our State of Data and AI in Financial Services 2024 study shows that 70% of financial services companies are tying a data location strategy to their AI strategic plans so that data is located in proximity to where they do business.
Computing power: The increasing number of AI-powered operations in financial services means businesses need massive computing power and flexibility. As AI continues to grow, it’s vital to have the right infrastructure to handle the increased demands.
Data privacy and security: As AI handles more financial data, keeping that information safe is more important than ever. This means that businesses must find a way to protect sensitive data while still unlocking AI-driven insights to keep up with their competitors.

Navigating regulatory compliance and data sovereignty

One of the biggest challenges for financial institutions using new AI technologies is staying on top of strict regulations. While AI can bring huge benefits, it’s important to stay compliant with changing laws and protect data to keep operations running smoothly and avoid risks.

EU AI Act

The EU AI Act regulates the use of AI in high-risk sectors, including finance. Businesses in the financial sector must be able to demonstrate that their AI technologies comply with established rules, regulations and guidelines. These are designed to protect both consumers and businesses and to promote the ethical use of AI. While these regulations help prevent misuse, they can also increase the compliance burden on financial institutions.

EU FIDA and UK DUA Bill

The EU’s Financial Data Access (FIDA) framework and the UK’s Data Utilisation and Access (DUA) Bill aim to improve data-sharing and access laws. They ensure that data is shared securely and that privacy is upheld. However, the challenge lies in adhering to these rules across the different jurisdictions where a company operates or shares data, making compliance more complex.

These rules are in place to ensure technology is not misused within the sector, however, complying with these regulations can create additional pressure on the financial services sector.

How Digital Realty unlocks AI for financial institutions

Financial institutions need more than advanced AI tools to succeed in a complex regulatory environment. They need a strong digital foundation that supports secure, scalable, and high-performance infrastructure. At Digital Realty, we help financial firms unlock AI by focusing on four key pillars: Network, Compute, Security, and Data.

PlatformDIGITAL™ offers a trusted foundation for scaling AI, managing Data Gravity, and maintaining compliance across global operations.

Network

We support direct, efficient connections between clouds, data, users, and applications. Our architecture consolidates and segments traffic while enabling seamless interconnectivity with partners and platforms.

Compute

Our infrastructure is built for AI workloads. With GPU acceleration, container support, and scalable processing, firms can host and run AI close to their data sources.

Security

With threats and regulations on the rise, our platform provides secure, compliance-ready environments. We enable control at ingress and egress points and offer direct connections to trusted SaaS and security services.

Data

We help localise and optimise data for real-time analytics. Our infrastructure supports efficient data exchange, streaming, and staging at key global business locations.

With Digital Realty, financial institutions gain the infrastructure they need to scale AI confidently and securely.

The real-world impact of PlatformDIGITAL™

Measuring competitive differentiation in milliseconds can make a big difference. Low-latency connectivity is a key component for any financial services company’s data centre strategy, including a leading European financial services firm that was able to scale its risk calculation capabilities for market, credit, liquidity, and legal risk analysis by leveraging Digital Realty’s AI-ready infrastructure. Rather than invest in a costly new data centre, they opted for a high-density colocation solution with direct liquid cooling, ensuring low-latency AI processing while also remaining compliant with financial regulations.

By retrofitting an existing Digital Realty facility, the company deployed its AI-driven risk calculation workloads in just four months, far faster than waiting for years to build new infrastructure. Plus, the direct liquid cooling solution increased energy efficiency by 30%, supporting both the AI workloads and the firm’s sustainability goals.

Digital Realty's solutions facilitate high-performance computing (HPC) workloads with the speed and processing power necessary for real-time data analysis, all while maintaining regulatory compliance. In fact, with 99.999% uptime and 100% renewable energy matching, we ensured the highest level of security, compliance, and data sovereignty, allowing the company to remain fully compliant while harnessing the power of AI.

By providing this AI-ready infrastructure, Digital Realty enables financial institutions to unlock the full potential of their AI-driven initiatives.

Future-proofing you AI strategy in financial services

AI is undoubtedly changing the game in financial services, but to truly thrive, you need the right data-first strategy and digital infrastructure foundations. Digital Realty’s AI-ready data centres give financial firms the speed, security, and scalability they need to truly unlock the value of AI and reap the benefits of data-driven initiatives. With PlatformDIGITAL™, you can set your AI strategy up for long-term success and stay one step ahead of the competition.

FAQS

How is AI transforming financial services?
Streamlining processes, improving decision-making, and enhancing customer service -whether it’s through fraud detection, predictive analytics, or personalising customer experiences.

What are the biggest challenges of using AI in finance?
Ensuring data security, staying compliant with regulations, managing implementation costs, and integrating AI into existing systems.

How does Digital Realty support AI in financial services?
By providing secure, scalable data centre solutions that support the computational power and infrastructure required for AI-driven financial operations.

Why do financial firms need AI-ready data centres?
To provide the necessary infrastructure to handle the demand for large amounts of data processing and storage securely and efficiently.

What are some real-world examples of AI in finance?
Fraud detection systems, robo-advisors for investment management, and automated credit risk or loan approvals.

How does AI help with compliance in financial services?
By automating tasks like transaction monitoring and risk assessment, making it easier for firms to comply with regulations while reducing manual effort.

GoGrid Case Study: Key Colocation Site in the Heart of San Francisco’s Financial District