Today’s financial services engineer has two needs. One is cutting-edge tech and frictionless access, and the other is robust security and risk management. Balancing both is tricky.
“We might be a highly regulated, centuries-old bank, but when engineers join us, their expectations are cutting-edge tech and fast access to data, with a self-serve process,” explains Hilary Lanham, Head of Engineering Excellence at Lloyds Banking Group. “In a highly-regulated environment, that’s difficult.”
As financial organizations progress their digital and AI programs, engineering leaders face more complex challenges than their peers in less-regulated industries.
This article takes a deeper dive into topics discussed in Stack Overflow’s Leaders of Code podcast sequence. Hilary Lanham, Head of Engineering Excellence, and Tom Kelk, Senior Product Proprietor, Productiveness Intelligence, from Lloyds Banking Group, be part of Stack Overflow CEO Prashanth Chandrasekar and host Ben Popper to debate the distinctive challenges going through tech and engineering groups in monetary providers.
Established banks typically run on infrastructure constructed over many years. Mergers, acquisitions, and layered functions add complexity.
In Deloitte’s Future of Software Engineering in Banks report, 78% of engineers say engaged on legacy programs hurts morale, resulting in workers loss and impacting enterprise efficiency. However including new software program to legacy code can really feel daunting.
Engineers who’re accustomed to self-service should adapt to safety evaluations and compliance checks. The endurance of engineers and administration can put on skinny. Gifted technologists might depart for much less restrictive environments so organizations face inside strain to modernize quick.
Some establishments are taking motion. In accordance with McKinsey’s productivity study, banks that observe software program companies’ cues have seen measurable impacts. The most effective performers can obtain 50% extra capability for innovation than common banks with the identical price range.
Some have upgraded their workplaces to attract tech expertise. Insurance coverage model Aviva’s Digital Garage introduced collectively product, tech and digital groups in a creative-agency model house, far faraway from the standard metropolis financial institution workplace.
Many monetary establishments discover innovation begins by simplifying present tech. They need to shore up in the present day’s programs earlier than including AI or different new instruments.
“The largest problem we’re going through in the meanwhile is simplification,” explains Kelk. “How will we improve the expertise of 1 or two issues versus the expertise of lots of?”
Gartner’s research on monetary providers IT spending exhibits 58% of budgets in 2024 go to modernization and debt discount, versus 31% for brand new capabilities. A McKinsey case study encompasses a financial institution that elevated group capability by 30% by means of steady enchancment, with out further sources. As a part of transformation, tech groups routinely analyze productiveness knowledge to seek out smarter methods of working and unlock main productiveness beneficial properties.
In addition to simplifying operations, Lloyds Banking Group focuses on standardization to ease the trail to automation. They’re merging a number of GitHub organizations and round 80 artifact repositories right into a single pipeline for automated governance.
“We’re going by means of a multi-year journey. The main target is on engineering excellence,” explains Lanham. “We have to get our engineers working extra easily, decreasing the friction and cognitive load.”A single information platform helps engineers transfer between groups with out relearning instruments. “When an engineer desires to maneuver from group A to group B, it will not really feel like becoming a member of a brand new group. There will be familiarity, which is able to improve their productiveness,” notes Lanham.
Past the know-how, monetary establishments face one other persistent problem: information silos. Compliance and threat administration necessities create knowledgeable clusters dotted throughout the group.
“Earlier than implementing Stack Overflow for Teams, we had 30-plus totally different platforms with hundreds of customers. 60% of individuals hadn’t spoken to anybody outdoors their group since becoming a member of. We wanted to interrupt down the obstacles and improve the information throughout the group.” —Tom Kelk, Senior Product Proprietor, Productiveness Intelligence, Lloyds Banking Group
Data silos result in misaligned objectives and duplicated work. For Lloyds Banking Group, a centralized information platform created surprising advantages. “We can provide product house owners an unfiltered view of what persons are trying to find about their product and what questions are being requested to create a wealthy persona,” notes Kelk.
Groups can establish ache factors shortly relatively than ready for formal suggestions cycles. As an alternative of counting on essentially the most senior stakeholders’ viewpoint, selections may be based mostly on product use patterns and ceaselessly requested questions.
AI guarantees innovation and productiveness beneficial properties for monetary organizations, however their threat urge for food is decrease than many different industries.
“Daily, a brand new LLM comes out that beats the earlier one,” says Kelk. “How do you design round what you present to your engineers when our precedence needs to be how we defend our clients?”
Banks must construct a strong basis for safety whereas matching evolving buyer expectations like personalization and ease of use, Kelk explains.
In accordance with McKinsey’s research, the highest tech development into account for monetary organizations is cloud and edge computing (84%), with utilized AI at 78%. AI adoption continues to be within the early days; in 2024, 70% of groups have been nonetheless on the pilot stage. McKinsey advises constructing sturdy safety, governance, and knowledge privateness practices earlier than stricter rules just like the EU AI Act take impact, which affect organizations with customers within the EU.
AI additionally raises questions on expertise, coaching, and the worth of expertise versus AI output. “There’s going to be an fascinating level the place you need to decipher between actual expertise and information, what’s discovered expertise, and what’s AI. We have to guarantee that it’s focused in the precise means. Valuing actual expertise is paramount,” displays Kelk.
Whereas monetary providers rules aren’t prone to get easier, banks are discovering methods to innovate with out compromising safety.
“We’re seeing a tradition change with our safety workplace and regulators,” explains Lanham. “As cloud tech, AI, and LLMs arrive, our engineers and safety colleagues must upskill.”
Gartner’s 2025 predictions say GenAI is shifting knowledge safety to guard unstructured knowledge. Slightly than cybersecurity taking a gatekeeper function, safety by design is constructed into growth processes.
“As an alternative of claiming “no”, the tradition is, how can we be extra assured in saying “sure”?” notes Lanham. “We’re seeing an enormous change in our safety posture, whereas preserving our clients’ security on the forefront.”
As monetary organizations fastidiously tread a path by means of digital and AI transformation, essentially the most profitable will steadiness innovation with compliance, pace with safety, and standardization with flexibility.
Engineering excellence in monetary providers wants leaders who can set a transparent imaginative and prescient whereas balancing tech potential with rules.
The trail received’t be easy, however by investing in simplification, standardization and a shared information and safety tradition, monetary providers engineering groups can drive constructive change for tens of millions of banking clients.
