AI is transforming the banking industry, but the expected benefits and savings come at great human cost with the impact on finance jobs.
The report, a collaboration between digital bank Zopa and Juniper Research, forecasts that generative AI will deliver £1.8 billion in cost savings by 2030, driven by an equivalent level of investment. However, this 100 percent investment return comes at a large human cost—placing an estimated 27,000 finance industry jobs at risk.
The findings suggest that AI technologies are moving beyond experimental pilots and becoming deeply embedded in the core processes of banking, from customer service to the unseen functions of the back office.
Peter Donlon, Chief Technology Officer at Zopa, said: “GenAI marks a paradigm shift in applied computing. Its influence on productivity, software creation, and decisionmaking systems could rival the advent of the internet or cloud computing.
“At Zopa, we’ve been operationalising machine learning for over a decade, well before LLMs became mainstream. That depth of experience has shaped our belief that GenAI isn’t a feature add-on, but a foundational capability. For Zopa technologists, it’s a rare chance to build entirely new intelligence layers, at a level that will redefine the industry.”
The silent AI revolution in the back offices of banks
While customer-facing chatbots and personalised app experiences often capture the headlines, the report reveals that the most dramatic impact of AI is occurring behind the scenes. 82 percent of all time saved through this technology, amounting to 154 million hours by 2030, will come from back office operations.
These functions – which include regulatory compliance, fraud detection, and risk management – are traditionally labour-intensive and highly complex. AI is expected to automate vast swathes of this important finance work, helping with everything from Know Your Customer (KYC) checks to anti-money laundering (AML) monitoring.
The financial implications of AI for these back office functions are immense, with projected cost savings in this area alone reaching £923 million annually by the end of the decade; representing more than half of the total savings across the entire sector.
This automation is not merely about cutting costs. With regulations such as the Authorised Push Payment (APP) fraud reimbursement rules increasing banks’ liability, the ability of AI to detect novel fraud patterns in real-time and reduce human error is becoming a competitive and financial necessity.
As we often hear about AI across industries, by automating routine checks and analysis, the technology frees up human experts. For the finance industry, these experts can focus their skills on the most complex investigations to improve both efficiency and effectiveness in the fight against financial crime.
Hyper-personalising the banking experience with AI
The drive for hyper-personalisation in the finance industry is fuelling a massive investment in customer service AI. The report projects that UK banks will pour over £1.1 billion into customer-facing AI by 2030, the largest share of investment across all segments.
This capital inflow for personalisation is being used to develop sophisticated virtual assistants and chatbots capable of handling complex queries; offering personalised financial advice and even anticipating customer needs.
The goal is to move far beyond the rules-based bots of the past towards a truly conversational and intelligent interface. This shift is expected to yield large efficiencies, saving £540 million in operational costs and freeing up 26 million hours of human agents’ time annually by 2030. These employees can also be redeployed to handle more complex and high-value interactions that require a human touch.
Portfolio management is also set to benefit. Investment in this area is projected to grow to £145 million by 2030. Here, AI is being positioned not as a replacement for human advisors but as a powerful augmentation tool. It can synthesise vast market data, simulate portfolio performance, and automate routine reporting, allowing human experts to focus on decisionmaking and client relationships.
The impact of AI on finance jobs
The efficiency gains delivered by AI inevitably raise urgent questions about the future of the financial workforce. The report’s projection that 27,000 roles could be displaced by 2030 is a concerning figure. Customer service and back-office positions are expected to bear the brunt of this change, with nearly 14,000 and 10,000 jobs at risk respectively.
However, the authors of the report suggest this is not simply a story of job losses but one of fundamental role redefinition. The displacement of finance jobs centred on repetitive, manual tasks creates an opportunity to upskill the banking workforce for new positions focused on AI governance, data strategy, and overseeing these complex automated systems.
Donlon emphasises this point, viewing the technological shift as a catalyst for positive change. He notes that “this investment ushers in a once-in-a-generation opportunity to re-skill and reimagine the workforce that powers our financial system.”
The challenge for the industry, Donlon suggests, is to proactively manage this transition. “Above all, our aim is to equip banks, fintechs, regulators, and policymakers with the insight needed to seize this historic moment-to shape the jobs of the future, not simply react to them.”
The report concludes with a clear warning for established institutions. A notable capability gap is already emerging between technologically advanced challenger banks, which have built their platforms around AI, and legacy banks encumbered by older systems.
Nick Maynard, VP of Fintech Market Research at Juniper Research, commented: “The UK banking sector stands at a tipping point, with GenAI being set to reshape how banking fundamentally works. GenAI creates risk and opportunity—the risk of a major shift in the skills workers will need to thrive, but the opportunity to create a better banking experience.
“Digital-only brands like Zopa already have deep experience with AI in their operations and will be less impacted by this shift. As such, digital banks and their experiences will be critical to leading the banking market through this revolution.”
For the high street banking giants, the message is unequivocal: adapt to the AI revolution or risk losing relevance in a finance industry being redefined by efficiency, personalisation, and intelligent automation.
See also: Gen AI makes no financial difference in 95% of cases
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