Artificial intelligence is moving from controlled pilots to enterprise infrastructure at NatWest Group, and for QA and software testing teams the message from the top is clear: AI must be governed, tested and trusted at scale.
In a recent NatWest blog, the bank’s chief information officer Scott Marcar framed technology not as a side programme but as the foundation of future banking.
“Being a trusted partner for tomorrow’s banking through technology,” he wrote, arguing that customer confidence and digital capability are now inseparable.
Marcar said NatWest is investing heavily in data and AI to strengthen that trust. “Technology is central to our strategy,” he wrote, positioning AI not simply as efficiency tooling but as a core enabler of safer, more responsive services.
In fact, “we’ve spent the last few years simplifying and removing complexity across our technology estate, quietly transforming the bank from the inside out as we move away from legacy platforms,” he added.
That framing lands after NatWest spent £1.2bn on technology last year, with Marcar signalling that while progress has been made, the “true AI transformation” is still to come.
In addition to the investments in the bank’s tech, data and AI transformation, the London-based executive went on to claim that NatWest is the first UK bank to sign a strategic collaboration with OpenAI.
Moreover, he said the bank currently has more than 12,000 coders using AI for software development, writing around 35% of the bank’s code.
In addition, Marcar and his team hired Maja Pantic as the bank’s first Chief AI Research Officer and established a AI research office at the end of 2025.
Finally, he also pointed out NatWest launched roughly 100 new features in its retail app and tested and deployed AI tools for all 60,000 staff to use in their daily work.
“In 2025 alone, we hired almost 1,000 software engineers and, the opening of our new India Hub in Bengaluru widens our access to specialist talent,” Marcar said.
At the same time, he stressed NatWest has been transforming its data estate to create a single, connected view of each customer so “we can anticipate needs faster, remove friction from everyday banking, and make onboarding more seamless.”
Through a deal with Amazon Web Services (AWS) and Accenture, the bank has been able to accelerate this further. “Our move to the cloud has supported this shift, giving us real time access and the ability to scale quickly as demand grows,” he explained.
“These improvements have a direct impact on the speed of innovation,” Marcar said.
He disclosed that the bank is currently testing new features “to put into the hands of customers”, such as new budget pots and a new subscription manager in NatWest’s banking app. “Our Retail app NPS is at an all time high,” he added.
Regulatory scrutiny
As NatWest deepens AI adoption across retail banking, embedded finance and internal operations, it is doing so against a backdrop of intensifying regulatory focus on AI assurance.
The UK’s Financial Conduct Authority has launched AI Live Testing, a programme designed to move artificial intelligence “out of the lab and into controlled real-world environments” for firms ready to deploy AI systems in production.
“We’re providing a structured but flexible space where firms can test AI-driven services in real-world conditions, all with our regulatory support and oversight and help from our technical partner, Advai,” explained Ed Towers, head of department in the FCA’s advanced analytics and data science unit.
A central concern for the regulator is that firms become stuck in pilots. “Through live testing we want to help UK innovators move safely beyond ‘POC paralysis’, or what is often described as ‘perpetual pilots’,” Towers said.
Crucially for QA teams, the FCA is explicit that AI assurance is no longer about isolated model checks.
“We broadly define the AI system as: the actual AI model, information on the deployment context and core risks … governance and human in-the-loop considerations, evaluation techniques as well as the input and output controls,” Towers said.
“We focus on both quantitative and qualitative factors to get a truly holistic understanding of the AI system.”
For a bank like NatWest, which is embedding AI across customer journeys and operational processes, that definition pulls testing, governance, data controls and monitoring into a single assurance perimeter.
Supercharged Sandbox
Alongside live testing for near-production systems, the FCA has also launched its Supercharged Sandbox in collaboration with NVIDIA, providing high-performance AI infrastructure and regulatory support for experimentation.
Jessica Rusu, the FCA’s chief data, intelligence and information officer, said the initiative is designed to lower the barrier to responsible testing. “This collaboration will help those that want to test AI ideas but who lack the capabilities to do so,” Rusu explained.
“We will help firms harness AI to benefit our markets and consumers, while supporting economic growth.”
The sandbox enables firms to simulate high-volume, real-time environments for training and testing models, creating conditions where reproducibility, bias detection and performance under variable data can be examined before production rollout.
For QA and DevOps teams inside large banks, the combination of early-stage sandbox experimentation and supervised live testing marks a structural shift: AI must now demonstrate robustness under scrutiny, not just promise value in internal demos.
Operational resilience
NatWest’s technology agenda extends beyond core banking into embedded finance and generative AI initiatives.
Reporting has highlighted how the bank’s Boxed technology team is driving business on the embedded finance wave, while partnerships to build generative AI capability signal further automation across customer and internal functions.
In a separate interview with the website CW, NatWest’s retail digital leadership described a transformation programme that places data and digital experience at the centre of customer strategy, reinforcing the need for disciplined release management and controlled experimentation as AI features are introduced.
For QA teams, that translates into testing not only models but end-to-end customer journeys, API integrations and third-party dependencies. As the FCA stresses, the “AI system” includes deployment context, governance and input-output controls, not just code.
The regulator’s stance reflects a broader shift in supervisory thinking. Whether through AI Live Testing or the Supercharged Sandbox, the FCA is signalling that observable behaviour in live or simulated environments matters more than theoretical validation.
“Collaboration and communication is at the heart of what we are doing,” Towers said.
“AI is fundamentally reshaping the financial sector by automating processes, enhancing data analysis, and improving decision-making, which leads to greater efficiency, accuracy, and risk management across a wide range of financial activities,” said Dr Jochen Papenbrock, EMEA head of financial technology at NVIDIA.
“The FCA’s Supercharged Sandbox provides firms with a secure environment to explore AI innovations using NVIDIA’s full stack accelerated computing platform, supporting industry-wide growth and efficiency.”
“We quietly transform the bank from the inside out as we move away from legacy platforms.”
– Scott Marcar
For NatWest, whose CIO has anchored the bank’s strategy in trust and technology, the implication is clear. AI ambition must be matched by measurable assurance.
In practice, that means QA and software testing teams become central actors in the bank’s AI strategy. They are the ones expected to generate the artefacts regulators can interrogate, to validate performance under stress, to document governance decisions and to evidence that AI systems are “safe, governed and ready for real customers”.
As AI shifts from innovation layer to operational backbone, NatWest’s strategy, and the FCA’s testing frameworks around it, point toward a future where AI testing sits alongside resilience testing and cyber assurance as a core discipline of modern banking.
Marcar said in agreement that “as we look beyond 2026, we see a future where digital and physical banking experiences blend seamlessly, enabled by a complete customer memory as we accelerate the pace of innovation and show up in the right places.”
He foressees “a future where the expertise of our colleagues is augmented by the intelligence and ease of modern technology … shaping the future responsibly through technology, data and AI.”
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