London’s reputation as a global financial hotspot is unrivaled. Its strong regulatory framework, access to capital and range of financial services make it a hub for innovation while attracting top financial talent, institutions and investors.

In this complex sector that deals with vast amounts of data and intricate processes, organizations are turning to AI-enhanced automation and analytics to operate more efficiently, reduce costs and gain a competitive edge.

In the insurance industry, for example, GenAI-based advisor enablement tools – which enable personalized engagement – are expected to lead to a 15% spike in distribution sales volume by 2027.

And, in banking, 80% of CIOs and technology executives plan to increase their investment in AI and machine learning in 2024*, as do 79% of CIOs and technology executives in insurance**, according to Gartner®.

The Gartner Banking and Investment Services: 2024 CIO Agenda Insights and Data research also identifies generative AI, AI (unspecified) and AI (machine learning) as the top three game-changing technologies in this industry – in that order – in the next three years.*

How AI makes a difference in financial services

AI-driven solutions can analyze data fast and accurately, and make data-driven decisions. For example:

  • Trading: AI algorithms are revolutionizing trading strategies by analyzing huge volumes of market data, identifying patterns and executing trades with precision and speed. This helps traders make informed decisions, optimize their portfolios and mitigate risk.
  • Risk management: AI-powered risk management systems can analyze historical data, market trends and real-time information to identify potential risks and predict market fluctuations. According to an IDC FutureScape report on banking, more than 25% of banks will use AI to monitor and assess banking risks in real time by 2025. These systems are also being used to identify fraud. Cybercriminals also have access to AI tools, so financial service providers cannot afford to fall behind in this regard.

    Meanwhile, more than half of IT security heads say AI-driven automation has improved compliance and process adherence – and, in turn, reduced business risks, according to research for NTT DATA’s 2023 Global Customer Experience Report.
  • Credit approvals: The IDC report also finds that 33% of financial institutions will integrate some form of intelligence in their lending operations to speed up credit decisioning – the process of evaluating borrowers’ creditworthiness and determining whether to approve a credit application.
  • Customer service: AI-driven chatbots and virtual assistants are transforming customer experience (CX) in the financial industry. These intelligent systems can provide personalized recommendations, answer queries and help customers with transactions.

Our CX report finds that 92% of financial services institutions say that CX improvements will directly affect their net profit. These improvements include using AI and automation to roll out hyperpersonalization. Also, 7 in 10 of these institutions say AI and automation are making a significant impact on removing drudgery from interactions with contact-center agents.

By 2026, 50% of the top 100 banks will hyperpersonalize customer rewards and loyalty programs, according to the IDC report. This will include real-time sentiment analytics, which are expected to feature in 33% of customer engagements.

What’s under the hood matters greatly

AI is clearly ushering in a new era of smart business for financial services in London and beyond. But none of these benefits can be realized if the underlying IT infrastructure isn’t robust enough to cope with the considerable demands of AI tools and services – and data centers play a key role in this regard:

  • AI applications need significant computational power. Data centers provide infrastructure such as high-performance servers and graphics processing units to handle these requirements, along with high-speed, low-latency network connections for efficient and secure data transfer between AI tools and data sources.
  • To cope with dynamic AI workloads, data centers can scale computing power up or down on demand. This allows organizations to benefit from optimal performance and cost-efficiency.
  • AI also relies heavily on large volumes of data for training and inference, and data centers’ storage systems can handle these massive datasets while guaranteeing data integrity, security and accessibility, as well as compliance with data protection regulations.
  • And, at a time when sustainability is high on every financial services CEO’s agenda, data centers are designed to be water- and energy-efficient by using advanced cooling systems, power management techniques and renewable energy sources. This helps data center customers reduce their carbon footprint in turn.

Work with the best

Bringing together the business use cases in financial services for AI and machine learning with the necessary IT infrastructure can be a daunting task.

One way for organizations to meet this challenge is to work with a colocation provider with extensive experience in the sector.

NTT DATA’s data centers in London – including the London 1 Data Center in Dagenham, the Slough 3 Data Center and the Hemel Hempstead 2 Data Center – and in many other countries around the world are AI-ready or already hosting AI workloads for leading organizations. For example:

  • Americas: We manage a multi-MW installation for a global client, using air cooling with physical barriers and high-velocity perforated tiles (for raised floor) to reach densities of up to 50kW per rack.
  • Americas and India: We installed a multi-MW installation for a leading high-density infrastructure manufacturer, using direct-to-chip cooling technology to extract heat from the chip level and reach up to 100kW per rack.
  • India: Working with PhonePe, the Indian fintech provider, we deployed a combination of liquid immersion cooling and direct contact liquid cooling This shift has improved our facilities’ overall energy efficiency by almost 30%.

With state-of-the-art facilities, robust security measures and reliable connectivity, our scalable platforms can bring any AI initiative to life.

* Gartner, Banking and Investment Services: 2024 CIO Agenda Insights and Data, December 2023
** Gartner, Insurance: 2024 CIO Agenda Insights and Data, January 2024
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

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