Automation has changed a great deal about how payments are processed. It handles transactions at volume, it has taken over much of the rule-based work that used to tie up operations teams, and it has made collections, payments and reconciliations faster and more efficient. Most of the conversation about it stops there, at speed and cost.
It hasn’t done away with those moments, though, and those moments are when a client decides whether a payments partner is one they can rely on. What they remember is how quickly the problem was picked up, who took ownership of it, and whether that person could actually fix it. That part still comes down to people.
Once the routine work is automated, what’s left is the work the rules don’t cover. People understand context, they apply judgement, they can work in the grey, and they can move a client forward before every answer is in. They bring empathy, solve problems that fall outside standard processes, and when trust has taken a knock, they’re the ones who rebuild it.
Spotting a problem before the client does takes real-time visibility, data the team can trust, clear decision frameworks and defined escalation paths. It also takes capacity, and this is where automation does the most for people.
In our own operation, automating case creation, improving reporting and visibility, categorising incoming demand more precisely, and backing all of that with documented procedures, training and cross-skilling has changed how the team spends its time. Each specialist now handles roughly 40% more cases than in 2024, with the same level of judgement applied to each one.
The figure I watch most closely is the share of cases our team opens itself, rather than having them raised by a client. Through closer monitoring of payments, account verifications, mandates, collections, DebiCheck transactions and exceptions, it has grown from 5% in 2024 to 15% in the third quarter of this year.
Clients have felt the difference. In just two years, resolution time has halved. Same-day resolution is up 19% and first-response service levels are up 28%, while around 90% of cases are now resolved within agreed service levels.
The capacity that’s been freed up hasn’t gone to waste. People with years of experience now spend more of their time predicting and managing exceptions, getting properly to the root cause of failures, and finding better ways for processes to run, both on our side and the client’s. Above all, they have room to understand each client’s business, how its money flows and what it needs.
That shifts the skills a payments operations team needs. Alongside a deep understanding of payment flows, people now need data literacy to interpret what the numbers are saying, fluency with digital tools and AI, and a sharp eye for understanding and diagnosing operational risk. The operations professional I want on a difficult case thinks critically, makes decisions on evidence, and solves the problem without compromising controls or resilience.
First-contact resolution tends to be discussed as a service metric. In practice, it comes down to whether people are allowed to make decisions. To resolve an issue at the first contact, someone needs the right information, the authority to act, clear accountability and the skills to fix the problem rather than log it and pass it on.
In many organisations, capable people are held back by fragmented systems, unclear decision rights, overlapping roles and internal processes so complex that nobody feels able to make the call. Clients experience all of that as delay.
When an issue can’t be fixed straight away, how you communicate matters as much as the fix. A client waiting on a problem wants to know who their point of contact is, what happened in business terms, how it affects them now and may affect them later, what’s being done about it, and when they’ll hear next. Updates should come as often as the client needs them, not as often as it suits the team. A clear, honest conversation can carry a lot of weight when there’s no immediate solution on the table.
I’m not arguing against automation. My concern is how it’s done. Automate a flawed process and you get the same poor result, only faster.
The two mistakes I see most often are automating before fixing the process underneath, and putting money into use cases that do little for the business commercially or for its clients. In payments, knowing where and how to automate matters as much as the technology itself. It works best as part of a broader plan that combines better processes, client self-service, intelligent automation, AI and smarter use of data, with every step measured by whether it improves the outcome for the business and the client.
In my view, what really sets an operation apart is the ability to combine automation, process excellence and people, and culture is what holds them together. The people in my team are committed to learning, passionate about the clients we serve and deeply invested in the role they play. They understand that behind every query logged is a person depending on us to get it right. We don’t get it right every time, not yet, but what we do get right every day is a culture of accountability and ownership. I believe culture should be the north star for any operations team. It guides how we think, act and serve, and it’s what turns operational efficiency into operational excellence.
The data will keep improving, and so will the automation behind it, but it won’t always tell the whole story. When a credible client says something is wrong and the systems say it isn’t, the right response is to keep looking until the root cause is found. As payments become more automated, I think operations teams will increasingly be judged on what they do when the data and the client disagree, and on whether their people have the visibility, the authority and the time to find out which one is right.
