Generative AI is reshaping how banks modernise payments, helping them manage complex change faster, more accurately, and at scale. Oliver St Clair-Stannard from RedCompass Labs highlights that combining human expertise with AI and measuring impact by what’s Built-By-AI (BBaiI) can help banks industrialise successfully.
Few of us have ever heard of a bank’s back office before the internet: the clatter of keys, the whirr of printers, the soft folding of warm paper.
Payments were manually typed, line by line, into telex machines. Each transaction was an act of faith: enter the beneficiary’s name, amount, currency, test key, press “send” and hope no errors occurred.
But as volumes grew, so did the stakes. Errors became expensive. As an industry, we did something: we removed the human bottleneck and built payments engines.
We began to measure ourselves with a metric—STP, straight-through processing. We redesigned processes, standardised payments messaging across the world, and codified validation and remittance.
We have come a long way. And yet when it comes to modernising our payment systems, rails, platforms, gateways —updating, upgrading, maintaining—we are stuck in the telex era.
Analysts, testers, and architects still translate rulebooks, reconcile code, and reformat test cases by hand. It is slow, costly, and prone to errors.
And the impact is significant. Over a fifth of financial institutions report struggling to keep up with modernisation demands. Most projects are delayed, over budget, or fail to meet specifications, with an average loss of nearly $500,000 per troubled project.
The surge in new rails, formats, and regulatory demands has made change constant and high stakes. ISO 20022 migrations, 24/7 instant payments, and evolving fraud risks have stretched systems and teams to their limits.
Recent outages at the European Central Bank, the UK, and the US highlight what is at stake: these systems are now too complex to modernise manually.
The solution is not simply faster change. It is a new way of changing, powered by generative AI.
AI and the change factory
Generative AI can now read, map, test, and even code. It enables the “change factory” – the processes behind system updates – to be industrialised, taking on repetitive, error-prone tasks so that experts can focus on critical decisions.
Built-by-AI (BBai) provides a measurable way to track AI’s contribution to change delivery.
So, why a new metric?
To understand AI’s real impact on modernisation, we need a clear way to measure it. Without a defined metric, the value of automation is impossible to separate from human effort.
BBai provides a common language for tracking progress, efficiency, and expectations across teams, clients, and regulators. Over time, it will show how hybrid intelligence – experts working alongside AI – is moving critical work from fully manual to AI-assisted and how far we’ve come.
BBai asks a simple question: “What percentage of your system change was generated by AI and accepted by humans?”
Today, almost every financial organisation’s answer is 0%. But early pilots are already achieving 5–10%. And within five years, leading institutions could reach 70%, with humans supervising, steering, and signing off.
To get there, a few governance principles are key:
- Coverage: Count only artefacts that meet your acceptance criteria.
- Correctness: Require peer review; defects reduce your BBai score.
- Control: Maintain a signed audit trail of prompts, models, reviewers, and approvals.
Together, these principles create a defensible metric – something boards, auditors, and regulators can rely on.
Start small. Pilot BBai in one area, such as ISO 20022 variant adjustments or sanction screening updates, and set bold, credible goals: 10% in 12 months, 30% in 24 months, and 70% in five years.
Expert-in-the-loop for safe modernisation
AI does not replace human expertise; it amplifies it. In highly regulated environments, accountability, oversight and auditability are non-negotiable.
Hybrid intelligence ensures that critical judgment remains human-led while AI handles the heavy lifting of documentation, reconciliation, and coding.
Modernisation today consumes vast resources. Banks spend upwards of $100 million on multi-year payment transformation programmes, often with teams of more than 50 business analysts. Yet two-thirds of their time is spent on project analysis, testing, and business or system mapping – exactly the areas ripe for AI-driven efficiency.
Skills shortages are adding to the strain. Over half of banks have delayed or scaled back payments projects due to a lack of expertise, while three-quarters believe AI agents could help close these gaps.
By taking on repetitive, low-value work, AI frees experts to focus on what matters most, improving accuracy, accelerating delivery, and reducing operational risk.
Let’s retire the telex twice
The future of payments modernisation is hybrid. Humans supervise, steer, and approve, while AI takes on the heavy lifting.
With this partnership, banks can industrialise their “change factory” with the same conviction that drives payment automation.
Built-By-AI provides a defensible, auditable metric that helps institutions demonstrate progress and governance while scaling safely.
We once trusted humans to type every payment over telex. Then we built engines and measured straight-through processing. Now, with AI, we can transform how those systems evolve, safely, at scale, and with measurable results.
The defining metric of this new era is Built-By-AI: not AI instead of us, but AI alongside us.
The future we want is one where modernisation is as automatic as settlement, as measurable as STP, and as safe as the systems we already trust with trillions.
In other words, let’s retire the telex twice.
