Just how much of a problem is legacy tech for financial services?

• Are outdated legacy systems, often referred to as ‘Frankenstein’s Monster’, hinder the financial services industry?
• Are poorly integrated technologies hindering the effectiveness of data optimisation and analysis?
• Unpack the challenges financial firms face in managing multiple software applications in an ever-expanding data universe

Described by some as “Frankenstein’s Monster”, outdated legacy systems and technologies in financial services are becoming harder to maintain. But are they holding back the sector’s approach to data optimisation?

For financial services companies to gather and analyse the volumes of data now available to them, they need modern data architecture. But take apart the tech stack of the average UK financial services company, and you are likely to find a patchwork of poorly integrated technologies and sprawling data feeds.

A recent study reported by the Financial Conduct Authority (FCA) showed that 92 per cent of the UK’s financial services companies still relied on legacy technology, and 78 per cent of their data sat in on-premise infrastructure. Of the 17 per cent that do favour the cloud, 11 percentage points use public, 5 percentage points private, and 1 percentage point hybrid.

Some of these institutions will have hundreds of different software applications (organisations in general have an average of 130) – all collecting and churning out data in different formats. This gives their teams the difficult task of trying to piece them all together to make them useful.

Solving the piecemeal problems of legacy systems is not as simple as just ripping it all up and starting again. Upgrading them in a way that maintains the existing value and roots out problems can take years.

So, more financial services companies are trying to strategically augment their existing tech stacks to create a flexible, unified data architecture that is capable of supporting artificial intelligence and machine learning projects, and which offers clearer data ownership across the client-facing, risk assessment and administrative departments.

Although some are retaining on-premise data storage to have closer control of their data and minimise data latency, a growing number are turning to cloud computing technologies and hybrid infrastructure models to help streamline their operations, enhance customer experience and increase scalability.

Schroders has invested significantly in its technology stack in recent years and according to Jeremy Hunt, Global Head of Data, Analytics, AI and CRM, the asset manager is now “largely cloud-based, with a strong data strategy to take advantage of the opportunity data brings”.

For Citibank UAE, “cloud access opens a world of opportunities to interact with clients, vendors and third-party data to co-create solutions,” says Mohamad Najmeddine, Head of Digital Platforms and Data. “For legacy businesses to avoid being left behind, they must start thinking and acting like start-ups: investing in new technologies and the right people to get the most value from those technologies.”

So, how can organisations modernise their tech stack to handle today’s data needs in a cost-efficient and agile manner?

“If I were building a tech stack from scratch today, I would definitely mirror it with a digital twin,” says Sarah Gadd, Chief Data Officer at Swiss private bank Julius Baer. She explains that by creating the code representation of the tech infrastructure alongside the hardware, the digital twin gives companies a safe domain where they can experiment and innovate.

“You can create simulations to inform your decision-making around questions like: ‘If I make this change, how will our productivity levels be impacted?’” says Gadd. “It enables you to test changes without touching anything on your physical infrastructure.”

Componentisation in tech stacks can also help with modernisation efforts, because organisations can lift and shift data architectures as technology evolves, with minimal disruption to the wider business. “The more there’s an open standard, the easier it is to lift and shift between things,” says Gadd. “Because you’re not as locked into a bespoke language or product.”

The FCA report finds that a sector-wide reliance on legacy technology means that financial services companies’ change-management processes still depend on manual review and actions. However, it is a myth to say that an organisation that operates with a legacy system cannot generate meaningful data insights.

For Schroders’, Hunt suggests the biggest myth about the impact of legacy systems on the performance of financial service companies is that they are difficult to integrate. “Modern abstraction approaches allow the data within these systems to be published easily using modern techniques,” he says. “This improves the accessibility of the data for internal consumers, operational third parties and customers.”

“And although legacy systems may capture data differently, have some workflow nuances and may be harder to fix than more modern technology, value can still be very much present,” echoes Karen Hiers, Chief Data and Analytics Officer – Enterprise at Northern Trust Corporation.

The single biggest opportunity for companies looking to move to more modern, cloud-based infrastructure, in her opinion? To get to know the data sitting behind the different components of existing infrastructure. She calls on companies “to evaluate the data housed in each component and look for opportunities to make the data more usable and add value”.